astro-ph.IM - 仪器仪表和天体物理学方法

    cond-mat.mtrl-sci - 材料科学 cond-mat.stat-mech - 统计数学 cs.AI - 人工智能 cs.AR - 硬件体系结构 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DM - 离散数学 cs.DS - 数据结构与算法 cs.GR - 计算机图形学 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.PL - 编程语言 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 econ.GN - 一般经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 hep-ph - 高能物理现象学 math-ph - 数学物理 math.CO - 组合数学 math.CT - 范畴论 math.DS - 动力系统 math.NA - 数值分析 math.PR - 概率 math.ST - 统计理论 nlin.SI - 完全可解和可积系统 physics.ao-ph - 大气和海洋物理 physics.med-ph - 医学物理学 q-bio.MN - 分子网络 q-fin.RM - 风险管理 q-fin.ST - 统计金融学 q-fin.TR - 贸易与市场微观结构 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.IM]DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains
    • [cond-mat.mtrl-sci]Active learning based generative design for the discovery of wide bandgap materials
    • [cond-mat.stat-mech]Accelerated Jarzynski Estimator with Deterministic Virtual Trajectories
    • [cs.AI]A Bioinspired Retinal Neural Network for Accurately Extracting Small-Target Motion Information in Cluttered Backgrounds
    • [cs.AI]Differentiable Inductive Logic Programming for Structured Examples
    • [cs.AI]Distilling Causal Effect of Data in Class-Incremental Learning
    • [cs.AI]Expected Value of Communication for Planning in Ad Hoc Teamwork
    • [cs.AI]Explaining Adversarial Vulnerability with a Data Sparsity Hypothesis
    • [cs.AI]Fast threshold optimization for multi-label audio tagging using Surrogate gradient learning
    • [cs.AI]Generating Probabilistic Safety Guarantees for Neural Network Controllers
    • [cs.AI]KANDINSKYPatterns — An experimental exploration environment for Pattern Analysis and Machine Intelligence
    • [cs.AI]Knowledge-Guided Dynamic Systems Modeling: A Case Study on Modeling River Water Quality
    • [cs.AI]Learning Monopoly Gameplay: A Hybrid Model-Free Deep Reinforcement Learning and Imitation Learning Approach
    • [cs.AI]Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues
    • [cs.AI]Logic Embeddings for Complex Query Answering
    • [cs.AI]Measuring Inconsistency over Sequences of Business Rule Cases
    • [cs.AI]Neural Production Systems
    • [cs.AI]PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception
    • [cs.AI]Scaling up Mean Field Games with Online Mirror Descent
    • [cs.AI]Single and Parallel Machine Scheduling with Variable Release Dates
    • [cs.AI]Sparse Training Theory for Scalable and Efficient Agents
    • [cs.AI]TopicTracker: A Platform for Topic Trajectory Identification and Visualisation
    • [cs.AI]Using contrastive learning to improve the performance of steganalysis schemes
    • [cs.AI]Where the Action is: Let’s make Reinforcement Learning for Stochastic Dynamic Vehicle Routing Problems work!
    • [cs.AR]Acceleration of probabilistic reasoning through custom processor architecture
    • [cs.AR]Mitigating Edge Machine Learning Inference Bottlenecks: An Empirical Study on Accelerating Google Edge Models
    • [cs.AR]SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network
    • [cs.AR]SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM
    • [cs.CL]A Data-Centric Framework for Composable NLP Workflows
    • [cs.CL]A Data-driven Approach to Estimate User Satisfaction in Multi-turn Dialogues
    • [cs.CL]A Simple But Effective Approach to n-shot Task-Oriented Dialogue Augmentation
    • [cs.CL]A Survey on Stance Detection for Mis- and Disinformation Identification
    • [cs.CL]Adapting MARBERT for Improved Arabic Dialect Identification: Submission to the NADI 2021 Shared Task
    • [cs.CL]An End-to-End Network for Emotion-Cause Pair Extraction
    • [cs.CL]AraBERT and Farasa Segmentation Based Approach For Sarcasm and Sentiment Detection in Arabic Tweets
    • [cs.CL]BERT-based knowledge extraction method of unstructured domain text
    • [cs.CL]COVID-19 Tweets Analysis through Transformer Language Models
    • [cs.CL]CREATe: Clinical Report Extraction and Annotation Technology
    • [cs.CL]Citizen Participation and Machine Learning for a Better Democracy
    • [cs.CL]Combat COVID-19 Infodemic Using Explainable Natural Language Processing Models
    • [cs.CL]Contrastive Explanations for Model Interpretability
    • [cs.CL]Conversational Norms for Human-Robot Dialogues
    • [cs.CL]Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language
    • [cs.CL]Data Augmentation for Abstractive Query-Focused Multi-Document Summarization
    • [cs.CL]Decomposing lexical and compositional syntax and semantics with deep language models
    • [cs.CL]Deep Bag-of-Sub-Emotions for Depression Detection in Social Media
    • [cs.CL]Detecting Abusive Language on Online Platforms: A Critical Analysis
    • [cs.CL]Distributional Formal Semantics
    • [cs.CL]Dual Reinforcement-Based Specification Generation for Image De-Rendering
    • [cs.CL]Emotion Dynamics in Movie Dialogues
    • [cs.CL]Emotion Ratings: How Intensity, Annotation Confidence and Agreements are Entangled
    • [cs.CL]Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detection
    • [cs.CL]Hindi-Urdu Adposition and Case Supersenses v1.0
    • [cs.CL]Interpretable Multi-Modal Hate Speech Detection
    • [cs.CL]Long Document Summarization in a Low Resource Setting using Pretrained Language Models
    • [cs.CL]M6: A Chinese Multimodal Pretrainer
    • [cs.CL]MultiSubs: A Large-scale Multimodal and Multilingual Dataset
    • [cs.CL]NLP-CUET@DravidianLangTech-EACL2021: Offensive Language Detection from Multilingual Code-Mixed Text using Transformers
    • [cs.CL]NLP-CUET@LT-EDI-EACL2021: Multilingual Code-Mixed Hope Speech Detection using Cross-lingual Representation Learner
    • [cs.CL]On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions
    • [cs.CL]Probing Product Description Generation via Posterior Distillation
    • [cs.CL]RAGA: Relation-aware Graph Attention Networks for Global Entity Alignment
    • [cs.CL]RuSentEval: Linguistic Source, Encoder Force!
    • [cs.CL]Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP
    • [cs.CL]Sentiment Analysis of Users’ Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset
    • [cs.CL]The Rediscovery Hypothesis: Language Models Need to Meet Linguistics
    • [cs.CL]Token-Modification Adversarial Attacks for Natural Language Processing: A Survey
    • [cs.CL]Towards Conversational Humor Analysis and Design
    • [cs.CL]Towards Efficiently Diversifying Dialogue Generation via Embedding Augmentation
    • [cs.CL]ToxCCIn: Toxic Content Classification with Interpretability
    • [cs.CL]Unsupervised Word Segmentation with Bi-directional Neural Language Model
    • [cs.CL]Vyākarana: A Colorless Green Benchmark for Syntactic Evaluation in Indic Languages
    • [cs.CR]A Brief Survey on Deep Learning Based Data Hiding, Steganography and Watermarking
    • [cs.CR]ActiveGuard: An Active DNN IP Protection Technique via Adversarial Examples
    • [cs.CR]Blockchain-Based Federated Learning in Mobile Edge Networks with Application in Internet of Vehicles
    • [cs.CR]Constrained Differentially Private Federated Learning for Low-bandwidth Devices
    • [cs.CR]Cybersecurity Awareness
    • [cs.CR]Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering
    • [cs.CR]Dissecting the Performance of Chained-BFT
    • [cs.CR]Identification of Significant Permissions for Efficient Android Malware Detection
    • [cs.CR]Multi-Party Proof Generation in QAP-based zk-SNARKs
    • [cs.CR]Recovering or Testing Extended-Affine Equivalence
    • [cs.CR]Virus-MNIST: A Benchmark Malware Dataset
    • [cs.CV]A 3D model-based approach for fitting masks to faces in the wild
    • [cs.CV]A Comprehensive Study on Face Recognition Biases Beyond Demographics
    • [cs.CV]A Deep Emulator for Secondary Motion of 3D Characters
    • [cs.CV]A Driving Behavior Recognition Model with Bi-LSTM and Multi-Scale CNN
    • [cs.CV]A Little Energy Goes a Long Way: Energy-Efficient, Accurate Conversion from Convolutional Neural Networks to Spiking Neural Networks
    • [cs.CV]A Novel CNN-LSTM-based Approach to Predict Urban Expansion
    • [cs.CV]A Pose-only Solution to Visual Reconstruction and Navigation
    • [cs.CV]A Structurally Regularized Convolutional Neural Network for Image Classification using Wavelet-based SubBand Decomposition
    • [cs.CV]A Survey of Deep Learning Techniques for Weed Detection from Images
    • [cs.CV]ADAADepth: Adapting Data Augmentation and Attention for Self-Supervised Monocular Depth Estimation
    • [cs.CV]Achieving Competitive Play Through Bottom-Up Approach in Semantic Segmentation
    • [cs.CV]Adversarial Reciprocal Points Learning for Open Set Recognition
    • [cs.CV]All at Once Network Quantization via Collaborative Knowledge Transfer
    • [cs.CV]Am I a Real or Fake Celebrity? Measuring Commercial Face Recognition Web APIs under Deepfake Impersonation Attack
    • [cs.CV]An Interpretable Multiple-Instance Approach for the Detection of referable Diabetic Retinopathy from Fundus Images
    • [cs.CV]AttriMeter: An Attribute-guided Metric Interpreter for Person Re-Identification
    • [cs.CV]Auto-Exposure Fusion for Single-Image Shadow Removal
    • [cs.CV]Automatic Stockpile Volume Monitoring using Multi-view Stereo from SkySat Imagery
    • [cs.CV]Brain Programming is Immune to Adversarial Attacks: Towards Accurate and Robust Image Classification using Symbolic Learning
    • [cs.CV]Brain-inspired algorithms for processing of visual data
    • [cs.CV]Categorical Depth Distribution Network for Monocular 3D Object Detection
    • [cs.CV]Coarse-Fine Networks for Temporal Activity Detection in Videos
    • [cs.CV]Comparison of Methods Generalizing Max- and Average-Pooling
    • [cs.CV]Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation
    • [cs.CV]Contextually Guided Convolutional Neural Networks for Learning Most Transferable Representations
    • [cs.CV]Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training
    • [cs.CV]Counterfactual Zero-Shot and Open-Set Visual Recognition
    • [cs.CV]Cross Modal Focal Loss for RGBD Face Anti-Spoofing
    • [cs.CV]DF-VO: What Should Be Learnt for Visual Odometry?
    • [cs.CV]DR-TANet: Dynamic Receptive Temporal Attention Network for Street Scene Change Detection
    • [cs.CV]DST: Data Selection and joint Training for Learning with Noisy Labels
    • [cs.CV]Deep Perceptual Image Quality Assessment for Compression
    • [cs.CV]Deep learning based geometric registration for medical images: How accurate can we get without visual features?
    • [cs.CV]Depth from Camera Motion and Object Detection
    • [cs.CV]Detection and Rectification of Arbitrary Shaped Scene Texts by using Text Keypoints and Links
    • [cs.CV]Diffusion Probabilistic Models for 3D Point Cloud Generation
    • [cs.CV]Diversifying Sample Generation for Accurate Data-Free Quantization
    • [cs.CV]Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
    • [cs.CV]Embedded Knowledge Distillation in Depth-level Dynamic Neural Network
    • [cs.CV]Emotion pattern detection on facial videos using functional statistics
    • [cs.CV]Emotion recognition techniques with rule based and machine learning approaches
    • [cs.CV]Exploiting latent representation of sparse semantic layers for improved short-term motion prediction with Capsule Networks
    • [cs.CV]Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
    • [cs.CV]Exploring the high dimensional geometry of HSI features
    • [cs.CV]FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation
    • [cs.CV]Few-Shot Lifelong Learning
    • [cs.CV]Few-shot Open-set Recognition by Transformation Consistency
    • [cs.CV]FineNet: Frame Interpolation and Enhancement for Face Video Deblurring
    • [cs.CV]Fixing Data Augmentation to Improve Adversarial Robustness
    • [cs.CV]Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning
    • [cs.CV]Generative Adversarial Transformers
    • [cs.CV]Geometry-Guided Street-View Panorama Synthesis from Satellite Imagery
    • [cs.CV]HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline
    • [cs.CV]Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph
    • [cs.CV]IdentityDP: Differential Private Identification Protection for Face Images
    • [cs.CV]Image-to-image Translation via Hierarchical Style Disentanglement
    • [cs.CV]Image/Video Deep Anomaly Detection: A Survey
    • [cs.CV]Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation
    • [cs.CV]InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring
    • [cs.CV]Inter-class Discrepancy Alignment for Face Recognition
    • [cs.CV]Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing
    • [cs.CV]Learning Frequency Domain Approximation for Binary Neural Networks
    • [cs.CV]Learning for Visual Navigation by Imagining the Success
    • [cs.CV]Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
    • [cs.CV]MFST: Multi-Features Siamese Tracker
    • [cs.CV]Masked Face Recognition: Human vs. Machine
    • [cs.CV]Maximal function pooling with applications
    • [cs.CV]Medical Image Segmentation with Limited Supervision: A Review of Deep Network Models
    • [cs.CV]Model-Agnostic Defense for Lane Detection against Adversarial Attack
    • [cs.CV]Multiclass Burn Wound Image Classification Using Deep Convolutional Neural Networks
    • [cs.CV]Multiple Convolutional Features in Siamese Networks for Object Tracking
    • [cs.CV]NLP-CUET@DravidianLangTech-EACL2021: Investigating Visual and Textual Features to Identify Trolls from Multimodal Social Media Memes
    • [cs.CV]Network Pruning via Resource Reallocation
    • [cs.CV]NeuTex: Neural Texture Mapping for Volumetric Neural Rendering
    • [cs.CV]OMNet: Learning Overlapping Mask for Partial-to-Partial Point Cloud Registration
    • [cs.CV]OmniNet: Omnidirectional Representations from Transformers
    • [cs.CV]On the Generalisation Capabilities of Fisher Vector based Face Presentation Attack Detection
    • [cs.CV]OpenICS: Open Image Compressive Sensing Toolbox and Benchmark
    • [cs.CV]Over-sampling De-occlusion Attention Network for Prohibited Items Detection in Noisy X-ray Images
    • [cs.CV]P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching
    • [cs.CV]Panoramic Panoptic Segmentation: Towards Complete Surrounding Understanding via Unsupervised Contrastive Learning
    • [cs.CV]Part2Whole: Iteratively Enrich Detail for Cross-Modal Retrieval with Partial Query
    • [cs.CV]Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
    • [cs.CV]Perspectives on individual animal identification from biology and computer vision
    • [cs.CV]Predicting Video with VQVAE
    • [cs.CV]Predicting post-operative right ventricular failure using video-based deep learning
    • [cs.CV]Real Masks and Fake Faces: On the Masked Face Presentation Attack Detection
    • [cs.CV]Representation Learning for Event-based Visuomotor Policies
    • [cs.CV]SUM: A Benchmark Dataset of Semantic Urban Meshes
    • [cs.CV]Scalable Scene Flow from Point Clouds in the Real World
    • [cs.CV]Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations
    • [cs.CV]Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map
    • [cs.CV]Self-supervised Low Light Image Enhancement and Denoising
    • [cs.CV]Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection
    • [cs.CV]Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation
    • [cs.CV]Single-Shot Motion Completion with Transformer
    • [cs.CV]Snowy Night-to-Day Translator and Semantic Segmentation Label Similarity for Snow Hazard Indicator
    • [cs.CV]Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain
    • [cs.CV]Square Root Bundle Adjustment for Large-Scale Reconstruction
    • [cs.CV]Systematic Analysis and Removal of Circular Artifacts for StyleGAN
    • [cs.CV]There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
    • [cs.CV]Towards Continual, Online, Unsupervised Depth
    • [cs.CV]Towards Precise and Efficient Image Guided Depth Completion
    • [cs.CV]Training Generative Adversarial Networks in One Stage
    • [cs.CV]TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning
    • [cs.CV]Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery
    • [cs.CV]Universal-Prototype Augmentation for Few-Shot Object Detection
    • [cs.CV]Unmasking Face Embeddings by Self-restrained Triplet Loss for Accurate Masked Face Recognition
    • [cs.CV]Unsupervised Depth and Ego-motion Estimation for Monocular Thermal Video using Multi-spectral Consistency Loss
    • [cs.CV]Using CNNs to Identify the Origin of Finger Vein Image
    • [cs.CV]WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
    • [cs.CV]When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework
    • [cs.CY]An Analysis of Distributed Systems Syllabi With a Focus on Performance-Related Topics
    • [cs.CY]COVID-19 vs Social Media Apps: Does Privacy Really Matter?
    • [cs.CY]Current eHealth Challenges and recent trends in eHealth applications
    • [cs.CY]Dados Abertos Governamentais no contexto de Políticas Públicas de Saúde e Sistemas Prisionais: Realidade ou Utopia?
    • [cs.CY]Digital History and History Teaching in the Digital Age
    • [cs.CY]Language-agnostic Topic Classification for Wikipedia
    • [cs.CY]Morning or Evening? An Examination of Circadian Rhythms of CS1 Students
    • [cs.CY]Narratives and Counternarratives on Data Sharing in Africa
    • [cs.CY]Reasons, Values, Stakeholders: A Philosophical Framework for Explainable Artificial Intelligence
    • [cs.CY]Reflections on the Clinical Acceptance of Artificial Intelligence
    • [cs.CY]The Healthy States of America: Creating a Health Taxonomy with Social Media
    • [cs.CY]The Rise of a New Digital Third Space Professional in Higher Education: Recognising Research Software Engineering
    • [cs.CY]Understanding the Complexity of Detecting Political Ads
    • [cs.CY]Unsupervised Representations Predict Popularity of Peer-Shared Artifacts in an Online Learning Environment
    • [cs.DB]CARMI: A Cache-Aware Learned Index with a Cost-based Construction Algorithm
    • [cs.DC]A Soft Method for Outliers Detection at the Edge of the Network
    • [cs.DC]Accelerating Distributed-Memory Autotuning via Statistical Analysis of Execution Paths
    • [cs.DC]An HPC-Based Hydrothermal Finite Element Simulator for Modeling Underground Response to Community-Scale Geothermal Energy Production
    • [cs.DC]An intelligent Data Delivery Service for and beyond the ATLAS experiment
    • [cs.DC]Coffea-casa: an analysis facility prototype
    • [cs.DC]Design and Performance Characterization of RADICAL-Pilot on Leadership-class Platforms
    • [cs.DC]Efficient Soft-Error Detection for Low-precision Deep Learning Recommendation Models
    • [cs.DC]Inferring Unobserved Events in Systems With Shared Resources and Queues
    • [cs.DC]LEAF: Simulating Large Energy-Aware Fog Computing Environments
    • [cs.DC]Memory Reclamation for Recoverable Mutual Exclusion
    • [cs.DC]On the Utility of Gradient Compression in Distributed Training Systems
    • [cs.DC]Parallel In-Place Algorithms: Theory and Practice
    • [cs.DC]Parallel Machine Learning of Partial Differential Equations
    • [cs.DC]Performance Optimization of SU3_Bench on Xeon and Programmable Integrated Unified Memory Architecture
    • [cs.DC]Reasons behind growing adoption of Cloud after Covid-19 Pandemic and Challenges ahead
    • [cs.DC]Scalable communication for high-order stencil computations using CUDA-aware MPI
    • [cs.DC]Serverless Workflows with Durable Functions and Netherite
    • [cs.DC]The Difficulty in Scaling Blockchains: A Simple Explanation
    • [cs.DM]Nested Vehicle Routing Problem: Optimizing Drone-Truck Surveillance Operations
    • [cs.DS]An Introduction to Johnson-Lindenstrauss Transforms
    • [cs.GR]Mixture of Volumetric Primitives for Efficient Neural Rendering
    • [cs.GT]Better Together? How Externalities of Size Complicate Notions of Solidarity and Actuarial Fairness
    • [cs.GT]Information Discrepancy in Strategic Learning
    • [cs.HC]Anticipation Next — System-sensitive technology development and integration in work contexts
    • [cs.HC]Between Post-Flaneur and Smartphone Zombie Smartphone Users Altering Visual Attention and Walking Behavior in Public Space
    • [cs.HC]Towards a Better Understanding of Social Acceptability
    • [cs.HC]Visualizing Rule Sets: Exploration and Validation of a Design Space
    • [cs.IR]A Linguistic Study on Relevance Modeling in Information Retrieval
    • [cs.IR]An Efficient Indexing and Searching Technique for Information Retrieval for Urdu Language
    • [cs.IR]An open-source framework for ExpFinder integrating 今日学术视野(2021.3.4) - 图1-gram Vector Space Model and 今日学术视野(2021.3.4) - 图2CO-HITS
    • [cs.IR]Automated Creative Optimization for E-Commerce Advertising
    • [cs.IR]Cross-Domain Recommendation: Challenges, Progress, and Prospects
    • [cs.IR]Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure
    • [cs.IR]Explore User Neighborhood for Real-time E-commerce Recommendation
    • [cs.IR]High-Performance Training by Exploiting Hot-Embeddings in Recommendation Systems
    • [cs.IR]LRG at TREC 2020: Document Ranking with XLNet-Based Models
    • [cs.IR]On Estimating Recommendation Evaluation Metrics under Sampling
    • [cs.IR]Parallel Algorithms for Densest Subgraph Discovery Using Shared Memory Model
    • [cs.IR]Query Rewriting via Cycle-Consistent Translation for E-Commerce Search
    • [cs.IT]6G Downlink Transmission via Rate Splitting Space Division Multiple Access Based on Grouped Code Index Modulation
    • [cs.IT]Active Reconfigurable Intelligent Surface Aided Wireless Communications
    • [cs.IT]Adaptive Transmission Scheduling in Wireless Networks for Asynchronous Federated Learning
    • [cs.IT]Angle-Domain Intelligent Reflecting Surface Systems: Design and Analysis
    • [cs.IT]Burst-Error Propagation Suppression for Decision-Feedback Equalizer in Field-Trial Submarine Fiber-Optic Communications
    • [cs.IT]Channel-Driven Monte Carlo Sampling for Bayesian Distributed Learning in Wireless Data Centers
    • [cs.IT]Coded Computing via Binary Linear Codes: Designs and Performance Limits
    • [cs.IT]Dynamic Oversampling Tecniques for 1-Bit ADCs in Large-Scale MIMO Systems
    • [cs.IT]Dynamic Sample Complexity for Exact Sparse Recovery using Sequential Iterative Hard Thresholding
    • [cs.IT]Efficient Encoding Algorithm of Binary and Non-Binary LDPC Codes Using Block Triangulation
    • [cs.IT]Expectation-Maximization-Aided Hybrid Generalized Expectation Consistent for Sparse Signal Reconstruction
    • [cs.IT]Explicit Construction of Minimum Bandwidth Rack-Aware Regenerating Codes
    • [cs.IT]Gradient Coding with Dynamic Clustering for Straggler-Tolerant Distributed Learning
    • [cs.IT]Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role can RIS Play?
    • [cs.IT]Jamming Aided Covert Communication with Multiple Receivers
    • [cs.IT]Joint Location and Communication Study for Intelligent Reflecting Surface Aided Wireless Communication System
    • [cs.IT]Joint Radar and Communication: A Survey
    • [cs.IT]Learning Robust Beamforming for MISO Downlink Systems
    • [cs.IT]Learning-Based Phase Compression and Quantization for Massive MIMO CSI Feedback with Magnitude-Aided Information
    • [cs.IT]Low-Complexity Zero-Forcing Precoding for XL-MIMO Transmissions
    • [cs.IT]Millimeter Wave and sub-THz Indoor Radio Propagation Channel Measurements, Models, and Comparisons in an Office Environment
    • [cs.IT]On Energy Allocation and Data Scheduling in Backscatter Networks with Multi-antenna Readers
    • [cs.IT]On the Connectivity and Giant Component Size of Random K-out Graphs Under Randomly Deleted Nodes
    • [cs.IT]On the Size of Levenshtein Balls
    • [cs.IT]Optimal Communication-Computation Trade-Off in Heterogeneous Gradient Coding
    • [cs.IT]Passive Beamforming Design and Channel Estimation for IRS Communication System with Few-Bit ADCs
    • [cs.IT]Performance Analysis of OTFS Modulation with Receive Antenna Selection
    • [cs.IT]Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation
    • [cs.IT]Propagation Measurements and Path Loss Models for sub-THz in Urban Microcells
    • [cs.IT]Quantization for spectral super-resolution
    • [cs.IT]RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials
    • [cs.IT]Real-time error correction codes for deletable errors
    • [cs.IT]Secure UAV Random Networks With Minimum Safety Distance
    • [cs.IT]Signal recovery from a few linear measurements of its high-order spectra
    • [cs.IT]Sparse Activity Detection in Multi-Cell Massive MIMO Exploiting Channel Large-Scale Fading
    • [cs.IT]Stream Distributed Coded Computing
    • [cs.IT]Terahertz Ultra-Massive MIMO-Based Aeronautical Communications in Space-Air-Ground Integrated Networks
    • [cs.IT]Terahertz Wireless Communications: Research Issues and Challenges for Active and Passive Systems in Space and on the Ground above 100 GHz
    • [cs.IT]The Capacity Region of Distributed Multi-User Secret Sharing
    • [cs.IT]Towards 6G with Connected Sky: UAVs and Beyond
    • [cs.IT]UAV-Enabled Wireless Power Transfer: A Tutorial Overview
    • [cs.LG]A Biased Graph Neural Network Sampler with Near-Optimal Regret
    • [cs.LG]A Brief Summary of Interactions Between Meta-Learning and Self-Supervised Learning
    • [cs.LG]A HINT from Arithmetic: On Systematic Generalization of Perception, Syntax, and Semantics
    • [cs.LG]A Kernel Framework to Quantify a Model’s Local Predictive Uncertainty under Data Distributional Shifts
    • [cs.LG]A Minimax Probability Machine for Non-Decomposable Performance Measures
    • [cs.LG]A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness
    • [cs.LG]A Proof of Concept Neural Network Watchdog using a Hybrid Generative Classifier For Optimized Outlier Detection
    • [cs.LG]A Spectral Enabled GAN for Time Series Data Generation
    • [cs.LG]A Survey On Universal Adversarial Attack
    • [cs.LG]A Survey on Deep Semi-supervised Learning
    • [cs.LG]A survey on Variational Autoencoders from a GreenAI perspective
    • [cs.LG]Acceleration via Fractal Learning Rate Schedules
    • [cs.LG]Adaptive Regularized Submodular Maximization
    • [cs.LG]Adaptive Sampling for Minimax Fair Classification
    • [cs.LG]AdeNet: Deep learning architecture that identifies damaged electrical insulators in power lines
    • [cs.LG]Adversarial Examples for Unsupervised Machine Learning Models
    • [cs.LG]Adversarial Information Bottleneck
    • [cs.LG]Adversarial training in communication constrained federated learning
    • [cs.LG]Autobahn: Automorphism-based Graph Neural Nets
    • [cs.LG]Automated Machine Learning on Graphs: A Survey
    • [cs.LG]Automated data-driven approach for gap filling in the time series using evolutionary learning
    • [cs.LG]Botcha: Detecting Malicious Non-Human Traffic in the Wild
    • [cs.LG]Categorical Foundations of Gradient-Based Learning
    • [cs.LG]Challenges and Opportunities in High-dimensional Variational Inference
    • [cs.LG]Characterization of Neural Networks Automatically Mapped on Automotive-grade Microcontrollers
    • [cs.LG]Class Means as an Early Exit Decision Mechanism
    • [cs.LG]Computationally Efficient Wasserstein Loss for Structured Labels
    • [cs.LG]Computing the Information Content of Trained Neural Networks
    • [cs.LG]Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
    • [cs.LG]Coordination Among Neural Modules Through a Shared Global Workspace
    • [cs.LG]Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms
    • [cs.LG]DM algorithms in healthindustry
    • [cs.LG]DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing
    • [cs.LG]DTW-Merge: A Novel Data Augmentation Technique for Time Series Classification
    • [cs.LG]Data-driven MIMO control of room temperature and bidirectional EV charging using deep reinforcement learning: simulation and experiments
    • [cs.LG]Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality on Hölder Class
    • [cs.LG]DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers
    • [cs.LG]DeepReDuce: ReLU Reduction for Fast Private Inference
    • [cs.LG]Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization
    • [cs.LG]Distilling Knowledge via Intermediate Classifier Heads
    • [cs.LG]Domain Generalization via Inference-time Label-Preserving Target Projections
    • [cs.LG]Double Coverage with Machine-Learned Advice
    • [cs.LG]Ensemble Bootstrapping for Q-Learning
    • [cs.LG]Evaluating the Robustness of Geometry-Aware Instance-Reweighted Adversarial Training
    • [cs.LG]Extreme Volatility Prediction in Stock Market: When GameStop meets Long Short-Term Memory Networks
    • [cs.LG]Factoring out prior knowledge from low-dimensional embeddings
    • [cs.LG]Federated Learning without Revealing the Decision Boundaries
    • [cs.LG]FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs
    • [cs.LG]Financial Crime & Fraud Detection Using Graph Computing: Application Considerations & Outlook
    • [cs.LG]ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations
    • [cs.LG]GEBT: Drawing Early-Bird Tickets in Graph Convolutional Network Training
    • [cs.LG]Generative Particle Variational Inference via Estimation of Functional Gradients
    • [cs.LG]Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks
    • [cs.LG]Graph-Time Convolutional Neural Networks
    • [cs.LG]Heterogeneity for the Win: One-Shot Federated Clustering
    • [cs.LG]Hierarchical Inducing Point Gaussian Process for Inter-domain Observations
    • [cs.LG]Is Simple Uniform Sampling Efficient for Center-Based Clustering With Outliers: When and Why?
    • [cs.LG]Kernel-Based Models for Influence Maximization on Graphs based on Gaussian Process Variance Minimization
    • [cs.LG]Label-Imbalanced and Group-Sensitive Classification under Overparameterization
    • [cs.LG]Learning disentangled representations via product manifold projection
    • [cs.LG]Learning with Hyperspherical Uniformity
    • [cs.LG]Listening to the city, attentively: A Spatio-Temporal Attention Boosted Autoencoder for the Short-Term Flow Prediction Problem
    • [cs.LG]LocalDrop: A Hybrid Regularization for Deep Neural Networks
    • [cs.LG]Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database
    • [cs.LG]Machine learning on small size samples: A synthetic knowledge synthesis
    • [cs.LG]Manifold optimization for optimal transport
    • [cs.LG]Meta-Learning an Inference Algorithm for Probabilistic Programs
    • [cs.LG]Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search
    • [cs.LG]Mind the box: 今日学术视野(2021.3.4) - 图3-APGD for sparse adversarial attacks on image classifiers
    • [cs.LG]Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding
    • [cs.LG]Missing Value Imputation on Multidimensional Time Series
    • [cs.LG]Model-Agnostic Explainability for Visual Search
    • [cs.LG]Moment-Based Variational Inference for Stochastic Differential Equations
    • [cs.LG]Multi-Level Attention Pooling for Graph Neural Networks: Unifying Graph Representations with Multiple Localities
    • [cs.LG]Multi-label Classification via Adaptive Resonance Theory-based Clustering
    • [cs.LG]Non-Euclidean Differentially Private Stochastic Convex Optimization
    • [cs.LG]Offline Reinforcement Learning with Pseudometric Learning
    • [cs.LG]On the Fairness of Generative Adversarial Networks (GANs)
    • [cs.LG]On the Memory Mechanism of Tensor-Power Recurrent Models
    • [cs.LG]Online Orthogonal Dictionary Learning Based on Frank-Wolfe Method
    • [cs.LG]Online anomaly detection using statistical leverage for streaming business process events
    • [cs.LG]Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories
    • [cs.LG]Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
    • [cs.LG]Optimal Linear Combination of Classifiers
    • [cs.LG]PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization
    • [cs.LG]PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer
    • [cs.LG]Performance Variability in Zero-Shot Classification
    • [cs.LG]Persistent Message Passing
    • [cs.LG]Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers
    • [cs.LG]Posterior Meta-Replay for Continual Learning
    • [cs.LG]Predictive Maintenance Tool for Non-Intrusive Inspection Systems
    • [cs.LG]Private Stochastic Convex Optimization: Optimal Rates in 今日学术视野(2021.3.4) - 图4 Geometry
    • [cs.LG]Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
    • [cs.LG]Reinforcement Learning for Adaptive Mesh Refinement
    • [cs.LG]Robust learning under clean-label attack
    • [cs.LG]STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection
    • [cs.LG]SWIS — Shared Weight bIt Sparsity for Efficient Neural Network Acceleration
    • [cs.LG]Safe Learning of Uncertain Environments for Nonlinear Control-Affine Systems
    • [cs.LG]Sample Complexity and Overparameterization Bounds for Projection-Free Neural TD Learning
    • [cs.LG]Scalable federated machine learning with FEDn
    • [cs.LG]Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating
    • [cs.LG]Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning
    • [cs.LG]Self-supervised Symmetric Nonnegative Matrix Factorization
    • [cs.LG]Smoothness Analysis of Loss Functions of Adversarial Training
    • [cs.LG]Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing
    • [cs.LG]Statistically Significant Stopping of Neural Network Training
    • [cs.LG]Strategic Classification Made Practical
    • [cs.LG]Task-Adaptive Neural Network Retrieval with Meta-Contrastive Learning
    • [cs.LG]The Age of Correlated Features in Supervised Learning based Forecasting
    • [cs.LG]The KL-Divergence between a Graph Model and its Fair I-Projection as a Fairness Regularizer
    • [cs.LG]The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games
    • [cs.LG]Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search
    • [cs.LG]Topic Modelling Meets Deep Neural Networks: A Survey
    • [cs.LG]Towards Efficient Local Causal Structure Learning
    • [cs.LG]Towards Personalized Federated Learning
    • [cs.LG]Transformers with Competitive Ensembles of Independent Mechanisms
    • [cs.LG]Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly
    • [cs.LG]Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements
    • [cs.LG]Unsupervised Domain Adaptation for Cross-Subject Few-Shot Neurological Symptom Detection
    • [cs.LG]Wide Network Learning with Differential Privacy
    • [cs.LG]ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation
    • [cs.NE]Convergence Rate of the (1+1)-Evolution Strategy with Success-Based Step-Size Adaptation on Convex Quadratic Functions
    • [cs.NE]Deep Learning with a Classifier System: Initial Results
    • [cs.NE]Enhancing hierarchical surrogate-assisted evolutionary algorithm for high-dimensional expensive optimization via random projection
    • [cs.NE]Incorporating Domain Knowledge into Deep Neural Networks
    • [cs.NE]Individual risk profiling for portable devices using a neural network to process the recording of 30 successive pairs of cognitive reaction and emotional response to a multivariate situational risk assessment
    • [cs.NE]Multi-Objective Evolutionary Design of CompositeData-Driven Models
    • [cs.NE]Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
    • [cs.NE]Semantic Neighborhood Ordering in Multi-objective Genetic Programming based on Decomposition
    • [cs.NE]SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic Environments
    • [cs.PL]Roosterize: Suggesting Lemma Names for Coq Verification Projects Using Deep Learning
    • [cs.RO]A Bioinspired Approach-Sensitive Neural Network for Collision Detection in Cluttered and Dynamic Backgrounds
    • [cs.RO]A CPG-Based Agile and Versatile Locomotion Framework Using Proximal Symmetry Loss
    • [cs.RO]A Holistic Motion Planning and Control Solution to Challenge a Professional Racecar Driver
    • [cs.RO]A Kinematic Bottleneck Approach For Pose Regression of Flexible Surgical Instruments directly from Images
    • [cs.RO]A Safety-Aware Kinodynamic Architecture for Human-Robot Collaboration
    • [cs.RO]A Unified MPC Framework for Whole-Body Dynamic Locomotion and Manipulation
    • [cs.RO]Autonomous Navigation of an Ultrasound Probe Towards Standard Scan Planes with Deep Reinforcement Learning
    • [cs.RO]Avoiding Degeneracy for Monocular Visual SLAM with Point and Line Features
    • [cs.RO]Avoiding dynamic small obstacles with onboard sensing and computating on aerial robots
    • [cs.RO]BPActuators: Lightweight and Low-Cost Soft Actuators by Balloons and Plastics
    • [cs.RO]Careful with That! Observation of Human Movements to Estimate Objects Properties
    • [cs.RO]Collaborative Recognition of Feasible region with Aerial and Ground Robots through DPCN
    • [cs.RO]Contact-Implicit Trajectory Optimization for Dynamic Object Manipulation
    • [cs.RO]Continuous control of an underground loader using deep reinforcement learning
    • [cs.RO]CrossMap Transformer: A Crossmodal Masked Path Transformer Using Double Back-Translation for Vision-and-Language Navigation
    • [cs.RO]Diverse Critical Interaction Generation for Planning and Planner Evaluation
    • [cs.RO]Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game
    • [cs.RO]EKMP: Generalized Imitation Learning with Adaptation, Nonlinear Hard Constraints and Obstacle Avoidance
    • [cs.RO]Enhancement for Robustness of Koopman Operator-based Data-driven Mobile Robotic Systems
    • [cs.RO]Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization
    • [cs.RO]Generalization Through Hand-Eye Coordination: An Action Space for Learning Spatially-Invariant Visuomotor Control
    • [cs.RO]Geometry-Based Grasping of Vine Tomatoes
    • [cs.RO]Human-Centered Dynamic Scheduling Architecture for Collaborative Application
    • [cs.RO]LTO: Lazy Trajectory Optimization with Graph-Search Planning for High DOF Robots in Cluttered Environments
    • [cs.RO]Learning Human-like Hand Reaching for Human-Robot Handshaking
    • [cs.RO]Learning Multimodal Contact-Rich Skills from Demonstrations Without Reward Engineering
    • [cs.RO]Learning Robotic Manipulation Tasks through Visual Planning
    • [cs.RO]Learning Symbolic Operators for Task and Motion Planning
    • [cs.RO]Learning-based Bias Correction for Time Difference of Arrival Ultra-wideband Localization of Resource-constrained Mobile Robots
    • [cs.RO]LiTAMIN2: Ultra Light LiDAR-based SLAM using Geometric Approximation applied with KL-Divergence
    • [cs.RO]Meta-Learning-Based Robust Adaptive Flight Control Under Uncertain Wind Conditions
    • [cs.RO]Model-based Safe Reinforcement Learning using Generalized Control Barrier Function
    • [cs.RO]Multi-robot task allocation for safe planning under dynamic uncertainties
    • [cs.RO]NavTuner: Learning a Scene-Sensitive Family of Navigation Policies
    • [cs.RO]Path Planning for Manipulation using Experience-driven Random Trees
    • [cs.RO]Path continuity for multi-wheeled AGVs
    • [cs.RO]Pixel-level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments
    • [cs.RO]Prognostics-Informed Battery Reconfiguration in a Multi-Battery Small UAS Energy System
    • [cs.RO]Reachability-based Identification, Analysis, and Control Synthesis of Robot Systems
    • [cs.RO]Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle
    • [cs.RO]Sim-to-Real Transfer for Robotic Manipulation with Tactile Sensory
    • [cs.RO]Simultaneous Tactile Exploration and Grasp Refinement for Unknown Objects
    • [cs.RO]Spatial Attention Point Network for Deep-learning-based Robust Autonomous Robot Motion Generation
    • [cs.RO]TouchRoller: A Rolling Optical Tactile Sensor for Rapid Assessment of Large Surfaces
    • [cs.RO]Virtual Adversarial Humans finding Hazards in Robot Workplaces
    • [cs.SD]Audio scene monitoring using redundant un-localized microphone arrays
    • [cs.SD]Audio-Visual Speech Separation Using Cross-Modal Correspondence Loss
    • [cs.SD]Brain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition
    • [cs.SD]Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event Localization
    • [cs.SD]Investigations on Audiovisual Emotion Recognition in Noisy Conditions
    • [cs.SD]Listen, Read, and Identify: Multimodal Singing Language Identification
    • [cs.SD]SoundCLR: Contrastive Learning of Representations For Improved Environmental Sound Classification
    • [cs.SD]Unsupervised Classification of Voiced Speech and Pitch Tracking Using Forward-Backward Kalman Filtering
    • [cs.SD]Virufy: A Multi-Branch Deep Learning Network for Automated Detection of COVID-19
    • [cs.SE]A Brief Survey of Current Software Engineering Practices in Continuous Integration and Automated Accessibility Testing
    • [cs.SE]An Exploratory Study of Log Placement Recommendation in an Enterprise System
    • [cs.SE]Automatic Generation of Challenging Road Networks for ALKS Testing based on Bezier Curves and Search
    • [cs.SE]Follow Your Nose — Which Code Smells are Worth Chasing?
    • [cs.SE]Investigating the potential impact of values on requirements and software engineering
    • [cs.SE]Offshore Software Maintenance Outsourcing Predicting Clients Proposal using Supervised Learning
    • [cs.SE]On Introducing Automatic Test Case Generation in Practice: A Success Story and Lessons Learned
    • [cs.SE]Test Automation with Grad-CAM Heatmaps — A Future Pipe Segment in MLOps for Vision AI?
    • [cs.SE]The High-Assurance ROS Framework
    • [cs.SE]Underproduction: An Approach for Measuring Risk in Open Source Software
    • [cs.SI]A multi-objective time series analysis of community mobility reduction comparing first and second COVID-19 waves
    • [cs.SI]A simple method for improving the accuracy of Chung-Lu random graph generation
    • [cs.SI]Automated Generation of Interorganizational Disaster Response Networks through Information Extraction
    • [cs.SI]COVID-19: Detecting Depression Signals during Stay-At-Home Period
    • [cs.SI]CogDL: An Extensive Toolkit for Deep Learning on Graphs
    • [cs.SI]Condition Sensing for Electricity Infrastructure in Disasters by Mining Public Topics from Social Media
    • [cs.SI]Criminal Networks Analysis in Missing Data scenarios through Graph Distances
    • [cs.SI]Discovering Dense Correlated Subgraphs in Dynamic Networks
    • [cs.SI]Exploring the social influence of Kaggle virtual community on the M5 competition
    • [cs.SI]Gender Typicality of Behavior Predicts Success on Creative Platforms
    • [cs.SI]How Fair is Fairness-aware Representative Ranking and Methods for Fair Ranking
    • [cs.SI]ISHNE: Influence Self-attention for Heterogeneous Network Embedding
    • [cs.SI]Interplay Between Hierarchy and Centrality in Complex Networks
    • [cs.SI]Nonparametric estimation of the preferential attachment function from one network snapshot
    • [cs.SI]Preferential attachment hypergraph with high modularity
    • [cs.SI]TweetCOVID: A System for Analyzing Public Sentiments and Discussions about COVID-19 via Twitter Activities
    • [cs.SI]Understanding & Predicting User Lifetime with Machine Learning in an Anonymous Location-Based Social Network
    • [econ.EM]Can Machine Learning Catch the COVID-19 Recession?
    • [econ.EM]Dynamic covariate balancing: estimating treatment effects over time
    • [econ.EM]Network Cluster-Robust Inference
    • [econ.GN]Computing Prices for Target Profits in Contracts
    • [eess.AS]AdaSpeech: Adaptive Text to Speech for Custom Voice
    • [eess.AS]Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition
    • [eess.AS]Contrastive Separative Coding for Self-supervised Representation Learning
    • [eess.AS]Exploiting ultrasound tongue imaging for the automatic detection of speech articulation errors
    • [eess.AS]Long-Running Speech Recognizer:An End-to-End Multi-Task Learning Framework for Online ASR and VAD
    • [eess.AS]Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation
    • [eess.AS]Silent versus modal multi-speaker speech recognition from ultrasound and video
    • [eess.AS]Tune-In: Training Under Negative Environments with Interference for Attention Networks Simulating Cocktail Party Effect
    • [eess.IV]A Practical Framework for ROI Detection in Medical Images — a case study for hip detection in anteroposterior pelvic radiographs
    • [eess.IV]Assessing deep learning methods for the identification of kidney stones in endoscopic images
    • [eess.IV]Efficient Deep Image Denoising via Class Specific Convolution
    • [eess.IV]Feature-Align Network and Knowledge Distillation for Efficient Denoising
    • [eess.IV]LADMM-Net: An Unrolled Deep Network For Spectral Image Fusion From Compressive Data
    • [eess.IV]Medical Imaging and Machine Learning
    • [eess.IV]MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing
    • [eess.IV]Robust 3D U-Net Segmentation of Macular Holes
    • [eess.IV]Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution Enhancement
    • [eess.IV]Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning
    • [eess.SP]Deep Learning-based Compressive Beam Alignment in mmWave Vehicular Systems
    • [eess.SP]Deep Reinforcement Learning for URLLC data management on top of scheduled eMBB traffic
    • [eess.SP]Deep Unfolded Recovery of Sub-Nyquist Sampled Ultrasound Image
    • [eess.SP]ECGT2T: Electrocardiogram synthesis from Two asynchronous leads to Ten leads
    • [eess.SP]Path-specific Underwater Acoustic Channel Tracking and its Application in Passive Time Reversal Mirror
    • [eess.SP]SmartON: Just-in-Time Active Event Detection on Energy Harvesting Systems
    • [eess.SP]Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamforming
    • [eess.SY]Constructing Dampened LTI Systems Generating Polynomial Bases
    • [eess.SY]Set-Membership Estimation in Shared Situational Awareness for Automated Vehicles in Occluded Scenarios
    • [hep-ph]Deep Learning strategies for ProtoDUNE raw data denoising
    • [math-ph]Local Tail Statistics of Heavy-Tailed Random Matrix Ensembles with Unitary Invariance
    • [math.CO]Linear Recurrences over a Finite Field with Exactly Two Periods
    • [math.CT]Learners’ languages
    • [math.DS]Analysis, Prediction, and Control of Epidemics: A Survey from Scalar to Dynamic Network Models
    • [math.NA]Error Estimates for the Variational Training of Neural Networks with Boundary Penalty
    • [math.NA]Estimating and increasing the structural robustness of a network
    • [math.PR]Asymptotic Stochastic Comparison of Random Processes
    • [math.PR]Bernoulli sums and Rényi entropy inequalities
    • [math.PR]Departure-based Asymptotic Stochastic Order for Random Processes
    • [math.ST]Algorithmic Obstructions in the Random Number Partitioning Problem
    • [math.ST]Bayesian Point Estimation and Predictive Density Estimation for the Binomial Distribution with a Restricted Probability Parameter
    • [math.ST]Comparisons of Order Statistics from Some Heterogeneous Discrete Distributions
    • [math.ST]Finite Sample Smeariness on Spheres
    • [math.ST]General dependence structures for some models based on exponential families with quadratic variance functions
    • [math.ST]Information-geometry of physics-informed statistical manifolds and its use in data assimilation
    • [math.ST]Posterior consistency for the spectral density of non-Gaussian stationary time series
    • [math.ST]Random tree Besov priors — Towards fractal imaging
    • [math.ST]Smeariness Begets Finite Sample Smeariness
    • [math.ST]Splitting the Sample at the Largest Uncensored Observation
    • [nlin.SI]Neural Network Approach to Construction of Classical Integrable Systems
    • [physics.ao-ph]Statistical Post-processing for Gridded Temperature Forecasts Using Encoder-Decoder Based Deep Convolutional Neural Networks
    • [physics.med-ph]Latent linear dynamics in spatiotemporal medical data
    • [q-bio.MN]Noncoding RNAs and deep learning neural network discriminate multi-cancer types
    • [q-fin.RM]Explainable AI in Credit Risk Management
    • [q-fin.ST]Forecasting high-frequency financial time series: an adaptive learning approach with the order book data
    • [q-fin.ST]Scale matters: The daily, weekly and monthly volatility and predictability of Bitcoin, Gold, and the S&P 500
    • [q-fin.TR]The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network
    • [quant-ph]A Hybrid Quantum-Classical Hamiltonian Learning Algorithm
    • [quant-ph]Non-invertible Anonymous Communication for the Quantum Era
    • [stat.AP]A Hierarchical Spike-and-Slab Model for Pan-Cancer Survival Using Pan-Omic Data
    • [stat.AP]Dynamic Stochastic Blockmodel Regression for Network Data: Application to International Militarized Conflicts
    • [stat.AP]Empirical study to explore the influence of salesperson’s customer orientation on customer loyalty
    • [stat.AP]Examining socioeconomic factors to understand the hospital case-fatality rates of COVID-19 in the city of Sao Paulo, Brazil
    • [stat.AP]Model-based Personalized Synthetic MR Imaging
    • [stat.AP]Moderating effects of retail operations and hard-sell sales techniques on salesperson’s interpersonal skills and customer repurchase intention
    • [stat.AP]ROC Analyses Based on Measuring Evidence
    • [stat.AP]Statistical methods used to combine the effective reproduction number, R(t), and other related measures of COVID-19 in the UK
    • [stat.AP]Towards Understanding the COVID-19 Case Fatality Rate
    • [stat.CO]A practical tutorial on Variational Bayes
    • [stat.ME]A Stein Goodness of fit Test for Exponential Random Graph Models
    • [stat.ME]BEAUTY Powered BEAST
    • [stat.ME]Conditional Precedence Orders for Stochastic Comparison of Random Variables
    • [stat.ME]Covariate balancing for causal inference on categorical and continuous treatments
    • [stat.ME]Diffusion Means and Heat Kernel on Manifolds
    • [stat.ME]Dynamic estimation with random forests for discrete-time survival data
    • [stat.ME]Empirical Bayes Model Averaging with Influential Observations: Tuning Zellner’s g Prior for Predictive Robustness
    • [stat.ME]Exact Simulation of Max-Infinitely Divisible Processes
    • [stat.ME]Factor-augmented Bayesian treatment effects models for panel outcomes
    • [stat.ME]Fast selection of nonlinear mixed effect models using penalized likelihood
    • [stat.ME]General Bayesian 今日学术视野(2021.3.4) - 图5 calibration of mathematical models
    • [stat.ME]Gradient boosting for extreme quantile regression
    • [stat.ME]Improving the output quality of official statistics based on machine learning algorithms
    • [stat.ME]Instrumental variables, spatial confounding and interference
    • [stat.ME]Interpretable Stein Goodness-of-fit Tests on Riemannian Manifolds
    • [stat.ME]Jenss-Bayley Latent Change Score Model with Individual Ratio of Growth Acceleration in the Framework of Individual Measurement Occasions
    • [stat.ME]Laplacian P-splines for Bayesian inference in the mixture cure model
    • [stat.ME]Maximum Approximate Bernstein Likelihood Estimation of Densities in a Two-sample Semiparametric Model
    • [stat.ME]Median Optimal Treatment Regimes
    • [stat.ME]Multi Split Conformal Prediction
    • [stat.ME]Multiscale change point detection via gradual bandwidth adjustment in moving sum processes
    • [stat.ME]On the Subbagging Estimation for Massive Data
    • [stat.ME]Online High-Dimensional Change-Point Detection using Topological Data Analysis
    • [stat.ME]Optimal Imperfect Classification for Gaussian Functional Data
    • [stat.ME]Penalized Poisson model for network meta-analysis of individual patient time-to-event data
    • [stat.ME]Penalized Projected Kernel Calibration for Computer Models
    • [stat.ME]Population Interference in Panel Experiments
    • [stat.ME]Propensity Score Weighting Analysis of Survival Outcomes Using Pseudo-observations
    • [stat.ME]Randomization Inference for Composite Experiments with Spillovers and Peer Effects
    • [stat.ME]Spatial sampling design to improve the efficiency of the estimation of the critical parameters of the SARS-CoV-2 epidemic
    • [stat.ME]Statistical Inference for Local Granger Causality
    • [stat.ME]Statistical learning and cross-validation for point processes
    • [stat.ME]Tangent functional canonical correlation analysis for densities and shapes, with applications to multimodal imaging data
    • [stat.ME]Time-Varying Coefficient Model Estimation Through Radial Basis Functions
    • [stat.ME]Validation of cluster analysis results on validation data: A systematic framework
    • [stat.ML]A Theorem of the Alternative for Personalized Federated Learning
    • [stat.ML]Asymptotic Risk of Overparameterized Likelihood Models: Double Descent Theory for Deep Neural Networks
    • [stat.ML]BERT based patent novelty search by training claims to their own description
    • [stat.ML]Communication-efficient Byzantine-robust distributed learning with statistical guarantee
    • [stat.ML]Fairness in Credit Scoring: Assessment, Implementation and Profit Implications
    • [stat.ML]Fast Adaptation with Linearized Neural Networks
    • [stat.ML]Feedback Coding for Active Learning
    • [stat.ML]Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
    • [stat.ML]Hessian Eigenspectra of More Realistic Nonlinear Models
    • [stat.ML]Kernel Interpolation for Scalable Online Gaussian Processes
    • [stat.ML]Learning Proposals for Probabilistic Programs with Inference Combinators
    • [stat.ML]Meta-learning One-class Classifiers with Eigenvalue Solvers for Supervised Anomaly Detection
    • [stat.ML]Meta-learning representations for clustering with infinite Gaussian mixture models
    • [stat.ML]Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks
    • [stat.ML]Panel semiparametric quantile regression neural network for electricity consumption forecasting
    • [stat.ML]Practical Privacy Filters and Odometers with Rényi Differential Privacy and Applications to Differentially Private Deep Learning
    • [stat.ML]Privacy-Preserving Distributed SVD via Federated Power
    • [stat.ML]Probabilistic Inference for Structural Health Monitoring: New Modes of Learning from Data
    • [stat.ML]Self-Regularity of Non-Negative Output Weights for Overparameterized Two-Layer Neural Networks
    • [stat.ML]Slow-Growing Trees
    • [stat.ML]Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior
    • [stat.ML]The Mathematics Behind Spectral Clustering And The Equivalence To PCA
    • [stat.ML]UCB Momentum Q-learning: Correcting the bias without forgetting
    • [stat.ML]Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance)

    ·····································

    • [astro-ph.IM]DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains
    A. Ćiprijanović, D. Kafkes, K. Downey, S. Jenkins, G. N. Perdue, S. Madireddy, T. Johnston, G. F. Snyder, B. Nord
    http://arxiv.org/abs/2103.01373v1

    • [cond-mat.mtrl-sci]Active learning based generative design for the discovery of wide bandgap materials
    Rui Xin, Edirisuriya M. D. Siriwardane, Yuqi Song, Yong Zhao, Steph-Yves Louis, Alireza Nasiri, Jianjun Hu
    http://arxiv.org/abs/2103.00608v1

    • [cond-mat.stat-mech]Accelerated Jarzynski Estimator with Deterministic Virtual Trajectories
    Nobumasa Ishida, Yoshihiko Hasegawa
    http://arxiv.org/abs/2103.00529v1

    • [cs.AI]A Bioinspired Retinal Neural Network for Accurately Extracting Small-Target Motion Information in Cluttered Backgrounds
    Xiao Huang, Hong Qiao, Hui Li, Zhihong Jiang
    http://arxiv.org/abs/2103.00848v1

    • [cs.AI]Differentiable Inductive Logic Programming for Structured Examples
    Hikaru Shindo, Masaaki Nishino, Akihiro Yamamoto
    http://arxiv.org/abs/2103.01719v1

    • [cs.AI]Distilling Causal Effect of Data in Class-Incremental Learning
    Xinting Hu, Kaihua Tang, Chunyan Miao, Xian-Sheng Hua, Hanwang Zhang
    http://arxiv.org/abs/2103.01737v1

    • [cs.AI]Expected Value of Communication for Planning in Ad Hoc Teamwork
    William Macke, Reuth Mirsky, Peter Stone
    http://arxiv.org/abs/2103.01171v1

    • [cs.AI]Explaining Adversarial Vulnerability with a Data Sparsity Hypothesis
    Mahsa Paknezhad, Cuong Phuc Ngo, Amadeus Aristo Winarto, Alistair Cheong, Beh Chuen Yang, Wu Jiayang, Lee Hwee Kuan
    http://arxiv.org/abs/2103.00778v1

    • [cs.AI]Fast threshold optimization for multi-label audio tagging using Surrogate gradient learning
    Thomas Pellegrini, Timothée Masquelier
    http://arxiv.org/abs/2103.00833v1

    • [cs.AI]Generating Probabilistic Safety Guarantees for Neural Network Controllers
    Sydney M. Katz, Kyle D. Julian, Christopher A. Strong, Mykel J. Kochenderfer
    http://arxiv.org/abs/2103.01203v1

    • [cs.AI]KANDINSKYPatterns — An experimental exploration environment for Pattern Analysis and Machine Intelligence
    Andreas Holzinger, Anna Saranti, Heimo Mueller
    http://arxiv.org/abs/2103.00519v1

    • [cs.AI]Knowledge-Guided Dynamic Systems Modeling: A Case Study on Modeling River Water Quality
    Namyong Park, MinHyeok Kim, Nguyen Xuan Hoai, R. I., McKay, Dong-Kyun Kim
    http://arxiv.org/abs/2103.00792v1

    • [cs.AI]Learning Monopoly Gameplay: A Hybrid Model-Free Deep Reinforcement Learning and Imitation Learning Approach
    Marina Haliem, Trevor Bonjour, Aala Alsalem, Shilpa Thomas, Hongyu Li, Vaneet Aggarwal, Bharat Bhargava, Mayank Kejriwal
    http://arxiv.org/abs/2103.00683v1

    • [cs.AI]Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues
    Hung Le, Nancy F. Chen, Steven C. H. Hoi
    http://arxiv.org/abs/2103.00820v1

    • [cs.AI]Logic Embeddings for Complex Query Answering
    Francois Luus, Prithviraj Sen, Pavan Kapanipathi, Ryan Riegel, Ndivhuwo Makondo, Thabang Lebese, Alexander Gray
    http://arxiv.org/abs/2103.00418v1

    • [cs.AI]Measuring Inconsistency over Sequences of Business Rule Cases
    Carl Corea, Matthias Thimm, Patrick Delfmann
    http://arxiv.org/abs/2103.01108v1

    • [cs.AI]Neural Production Systems
    Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
    http://arxiv.org/abs/2103.01937v1

    • [cs.AI]PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception
    Aviv Netanyahu, Tianmin Shu, Boris Katz, Andrei Barbu, Joshua B. Tenenbaum
    http://arxiv.org/abs/2103.01933v1

    • [cs.AI]Scaling up Mean Field Games with Online Mirror Descent
    Julien Perolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
    http://arxiv.org/abs/2103.00623v1

    • [cs.AI]Single and Parallel Machine Scheduling with Variable Release Dates
    Felix Mohr, Gonzalo Mejía, Francisco Yuraszeck
    http://arxiv.org/abs/2103.01785v1

    • [cs.AI]Sparse Training Theory for Scalable and Efficient Agents
    Decebal Constantin Mocanu, Elena Mocanu, Tiago Pinto, Selima Curci, Phuong H. Nguyen, Madeleine Gibescu, Damien Ernst, Zita A. Vale
    http://arxiv.org/abs/2103.01636v1

    • [cs.AI]TopicTracker: A Platform for Topic Trajectory Identification and Visualisation
    Yong-Bin Kang, Timos Sellis
    http://arxiv.org/abs/2103.01432v1

    • [cs.AI]Using contrastive learning to improve the performance of steganalysis schemes
    Yanzhen Ren, Yiwen Liu, Lina Wang
    http://arxiv.org/abs/2103.00891v1

    • [cs.AI]Where the Action is: Let’s make Reinforcement Learning for Stochastic Dynamic Vehicle Routing Problems work!
    Florentin D Hildebrandt, Barrett Thomas, Marlin W Ulmer
    http://arxiv.org/abs/2103.00507v1

    • [cs.AR]Acceleration of probabilistic reasoning through custom processor architecture
    Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert, Marian Verhelst
    http://arxiv.org/abs/2103.00266v1

    • [cs.AR]Mitigating Edge Machine Learning Inference Bottlenecks: An Empirical Study on Accelerating Google Edge Models
    Amirali Boroumand, Saugata Ghose, Berkin Akin, Ravi Narayanaswami, Geraldo F. Oliveira, Xiaoyu Ma, Eric Shiu, Onur Mutlu
    http://arxiv.org/abs/2103.00768v1

    • [cs.AR]SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network
    Fangxin Liu, Wenbo Zhao, Yilong Zhao, Zongwu Wang, Tao Yang, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang
    http://arxiv.org/abs/2103.01705v1

    • [cs.AR]SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM
    Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
    http://arxiv.org/abs/2103.00421v1

    • [cs.CL]A Data-Centric Framework for Composable NLP Workflows
    Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu
    http://arxiv.org/abs/2103.01834v1

    • [cs.CL]A Data-driven Approach to Estimate User Satisfaction in Multi-turn Dialogues
    Ziming Li, Dookun Park, Julia Kiseleva, Young-Bum Kim, Sungjin Lee
    http://arxiv.org/abs/2103.01287v1

    • [cs.CL]A Simple But Effective Approach to n-shot Task-Oriented Dialogue Augmentation
    Taha Aksu, Nancy F. Chen, Min-Yen Kan, Zhengyuan Liu
    http://arxiv.org/abs/2103.00293v1

    • [cs.CL]A Survey on Stance Detection for Mis- and Disinformation Identification
    Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein
    http://arxiv.org/abs/2103.00242v1

    • [cs.CL]Adapting MARBERT for Improved Arabic Dialect Identification: Submission to the NADI 2021 Shared Task
    Badr AlKhamissi, Mohamed Gabr, Muhammad ElNokrashy, Khaled Essam
    http://arxiv.org/abs/2103.01065v1

    • [cs.CL]An End-to-End Network for Emotion-Cause Pair Extraction
    Aaditya Singh, Shreeshail Hingane, Saim Wani, Ashutosh Modi
    http://arxiv.org/abs/2103.01544v1

    • [cs.CL]AraBERT and Farasa Segmentation Based Approach For Sarcasm and Sentiment Detection in Arabic Tweets
    Anshul Wadhawan
    http://arxiv.org/abs/2103.01679v1

    • [cs.CL]BERT-based knowledge extraction method of unstructured domain text
    Wang Zijia, Li Ye, Zhu Zhongkai
    http://arxiv.org/abs/2103.00728v1

    • [cs.CL]COVID-19 Tweets Analysis through Transformer Language Models
    Abdul Hameed Azeemi, Adeel Waheed
    http://arxiv.org/abs/2103.00199v1

    • [cs.CL]CREATe: Clinical Report Extraction and Annotation Technology
    Yichao Zhou, Wei-Ting Chen, Bowen Zhang, David Lee, J. Harry Caufield, Kai-Wei Chang, Yizhou Sun, Peipei Ping, Wei Wang
    http://arxiv.org/abs/2103.00562v1

    • [cs.CL]Citizen Participation and Machine Learning for a Better Democracy
    M. Arana-Catania, F. A. Van Lier, Rob Procter, Nataliya Tkachenko, Yulan He, Arkaitz Zubiaga, Maria Liakata
    http://arxiv.org/abs/2103.00508v1

    • [cs.CL]Combat COVID-19 Infodemic Using Explainable Natural Language Processing Models
    Jackie Ayoub, X. Jessie Yang, Feng Zhou
    http://arxiv.org/abs/2103.00747v1

    • [cs.CL]Contrastive Explanations for Model Interpretability
    Alon Jacovi, Swabha Swayamdipta, Shauli Ravfogel, Yanai Elazar, Yejin Choi, Yoav Goldberg
    http://arxiv.org/abs/2103.01378v1

    • [cs.CL]Conversational Norms for Human-Robot Dialogues
    Maitreyee Tewari, Thomas Hellström, Suna Bensch
    http://arxiv.org/abs/2103.01706v1

    • [cs.CL]Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language
    Avia Efrat, Uri Shaham, Dan Kilman, Omer Levy
    http://arxiv.org/abs/2103.01242v1

    • [cs.CL]Data Augmentation for Abstractive Query-Focused Multi-Document Summarization
    Ramakanth Pasunuru, Asli Celikyilmaz, Michel Galley, Chenyan Xiong, Yizhe Zhang, Mohit Bansal, Jianfeng Gao
    http://arxiv.org/abs/2103.01863v1

    • [cs.CL]Decomposing lexical and compositional syntax and semantics with deep language models
    Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
    http://arxiv.org/abs/2103.01620v1

    • [cs.CL]Deep Bag-of-Sub-Emotions for Depression Detection in Social Media
    Juan S. Lara, Mario Ezra Aragon, Fabio A. Gonzalez, Manuel Montes-y-Gomez
    http://arxiv.org/abs/2103.01334v1

    • [cs.CL]Detecting Abusive Language on Online Platforms: A Critical Analysis
    Preslav Nakov, Vibha Nayak, Kyle Dent, Ameya Bhatawdekar, Sheikh Muhammad Sarwar, Momchil Hardalov, Yoan Dinkov, Dimitrina Zlatkova, Guillaume Bouchard, Isabelle Augenstein
    http://arxiv.org/abs/2103.00153v1

    • [cs.CL]Distributional Formal Semantics
    Noortje J. Venhuizen, Petra Hendriks, Matthew W. Crocker, Harm Brouwer
    http://arxiv.org/abs/2103.01713v1

    • [cs.CL]Dual Reinforcement-Based Specification Generation for Image De-Rendering
    Ramakanth Pasunuru, David Rosenberg, Gideon Mann, Mohit Bansal
    http://arxiv.org/abs/2103.01867v1

    • [cs.CL]Emotion Dynamics in Movie Dialogues
    Will E. Hipson, Saif M. Mohammad
    http://arxiv.org/abs/2103.01345v1

    • [cs.CL]Emotion Ratings: How Intensity, Annotation Confidence and Agreements are Entangled
    Enrica Troiano, Sebastian Padó, Roman Klinger
    http://arxiv.org/abs/2103.01667v1

    • [cs.CL]Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detection
    Lara Grimminger, Roman Klinger
    http://arxiv.org/abs/2103.01664v1

    • [cs.CL]Hindi-Urdu Adposition and Case Supersenses v1.0
    Aryaman Arora, Nitin Venkateswaran, Nathan Schneider
    http://arxiv.org/abs/2103.01399v1

    • [cs.CL]Interpretable Multi-Modal Hate Speech Detection
    Prashanth Vijayaraghavan, Hugo Larochelle, Deb Roy
    http://arxiv.org/abs/2103.01616v1

    • [cs.CL]Long Document Summarization in a Low Resource Setting using Pretrained Language Models
    Ahsaas Bajaj, Pavitra Dangati, Kalpesh Krishna, Pradhiksha Ashok Kumar, Rheeya Uppaal, Bradford Windsor, Eliot Brenner, Dominic Dotterrer, Rajarshi Das, Andrew McCallum
    http://arxiv.org/abs/2103.00751v1

    • [cs.CL]M6: A Chinese Multimodal Pretrainer
    Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang
    http://arxiv.org/abs/2103.00823v2

    • [cs.CL]MultiSubs: A Large-scale Multimodal and Multilingual Dataset
    Josiah Wang, Pranava Madhyastha, Josiel Figueiredo, Chiraag Lala, Lucia Specia
    http://arxiv.org/abs/2103.01910v1

    • [cs.CL]NLP-CUET@DravidianLangTech-EACL2021: Offensive Language Detection from Multilingual Code-Mixed Text using Transformers
    Omar Sharif, Eftekhar Hossain, Mohammed Moshiul Hoque
    http://arxiv.org/abs/2103.00455v1

    • [cs.CL]NLP-CUET@LT-EDI-EACL2021: Multilingual Code-Mixed Hope Speech Detection using Cross-lingual Representation Learner
    Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque
    http://arxiv.org/abs/2103.00464v1

    • [cs.CL]On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions
    Rob van der Goot, Ahmet Üstün, Barbara Plank
    http://arxiv.org/abs/2103.01273v1

    • [cs.CL]Probing Product Description Generation via Posterior Distillation
    Haolan Zhan, Hainan Zhang, Hongshen Chen, Lei Shen, Zhuoye Ding, Yongjun Bao, Weipeng Yan, Yanyan Lan
    http://arxiv.org/abs/2103.01594v1

    • [cs.CL]RAGA: Relation-aware Graph Attention Networks for Global Entity Alignment
    Renbo Zhu, Meng Ma, Ping Wang
    http://arxiv.org/abs/2103.00791v1

    • [cs.CL]RuSentEval: Linguistic Source, Encoder Force!
    Vladislav Mikhailov, Ekaterina Taktasheva, Elina Sigdel, Ekaterina Artemova
    http://arxiv.org/abs/2103.00573v2

    • [cs.CL]Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP
    Timo Schick, Sahana Udupa, Hinrich Schütze
    http://arxiv.org/abs/2103.00453v1

    • [cs.CL]Sentiment Analysis of Users’ Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset
    Kashif Ahmad, Firoj Alam, Junaid Qadir, Basheer Qolomany, Imran Khan, Talhat Khan, Muhammad Suleman, Naina Said, Syed Zohaib Hassan, Asma Gul, Ala Al-Fuqaha
    http://arxiv.org/abs/2103.01196v1

    • [cs.CL]The Rediscovery Hypothesis: Language Models Need to Meet Linguistics
    Vassilina Nikoulina, Maxat Tezekbayev, Nuradil Kozhakhmet, Madina Babazhanova, Matthias Gallé, Zhenisbek Assylbekov
    http://arxiv.org/abs/2103.01819v1

    • [cs.CL]Token-Modification Adversarial Attacks for Natural Language Processing: A Survey
    Tom Roth, Yansong Gao, Alsharif Abuadbba, Surya Nepal, Wei Liu
    http://arxiv.org/abs/2103.00676v1

    • [cs.CL]Towards Conversational Humor Analysis and Design
    Tanishq Chaudhary, Mayank Goel, Radhika Mamidi
    http://arxiv.org/abs/2103.00536v1

    • [cs.CL]Towards Efficiently Diversifying Dialogue Generation via Embedding Augmentation
    Yu Cao, Liang Ding, Zhiliang Tian, Meng Fang
    http://arxiv.org/abs/2103.01534v1

    • [cs.CL]ToxCCIn: Toxic Content Classification with Interpretability
    Tong Xiang, Sean MacAvaney, Eugene Yang, Nazli Goharian
    http://arxiv.org/abs/2103.01328v1

    • [cs.CL]Unsupervised Word Segmentation with Bi-directional Neural Language Model
    Lihao Wang, Zongyi Li, Xiaoqing Zheng
    http://arxiv.org/abs/2103.01421v1

    • [cs.CL]Vyākarana: A Colorless Green Benchmark for Syntactic Evaluation in Indic Languages
    Rajaswa Patil, Jasleen Dhillon, Siddhant Mahurkar, Saumitra Kulkarni, Manav Malhotra, Veeky Baths
    http://arxiv.org/abs/2103.00854v1

    • [cs.CR]A Brief Survey on Deep Learning Based Data Hiding, Steganography and Watermarking
    Chaoning Zhang, Chenguo Lin, Philipp Benz, Kejiang Chen, Weiming Zhang, In So Kweon
    http://arxiv.org/abs/2103.01607v1

    • [cs.CR]ActiveGuard: An Active DNN IP Protection Technique via Adversarial Examples
    Mingfu Xue, Shichang Sun, Can He, Yushu Zhang, Jian Wang, Weiqiang Liu
    http://arxiv.org/abs/2103.01527v1

    • [cs.CR]Blockchain-Based Federated Learning in Mobile Edge Networks with Application in Internet of Vehicles
    Rui Wang, Heju Li, Erwu Liu
    http://arxiv.org/abs/2103.01116v1

    • [cs.CR]Constrained Differentially Private Federated Learning for Low-bandwidth Devices
    Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
    http://arxiv.org/abs/2103.00342v1

    • [cs.CR]Cybersecurity Awareness
    Jason R. C. Nurse
    http://arxiv.org/abs/2103.00474v1

    • [cs.CR]Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering
    Hemant Rathore, Sanjay K. Sahay, Shivin Thukral, Mohit Sewak
    http://arxiv.org/abs/2103.00637v1

    • [cs.CR]Dissecting the Performance of Chained-BFT
    Fangyu Gai, Ali Farahbakhsh, Jianyu Niu, Chen Feng, Ivan Beschastnikh, Hao Duan
    http://arxiv.org/abs/2103.00777v1

    • [cs.CR]Identification of Significant Permissions for Efficient Android Malware Detection
    Hemant Rathore, Sanjay K. Sahay, Ritvik Rajvanshi, Mohit Sewak
    http://arxiv.org/abs/2103.00643v1

    • [cs.CR]Multi-Party Proof Generation in QAP-based zk-SNARKs
    Ali Rahimi, Mohammad Ali Maddah-Ali
    http://arxiv.org/abs/2103.01344v1

    • [cs.CR]Recovering or Testing Extended-Affine Equivalence
    Anne Canteaut, Alain Couvreur, Léo Perrin
    http://arxiv.org/abs/2103.00078v1

    • [cs.CR]Virus-MNIST: A Benchmark Malware Dataset
    David Noever, Samantha E. Miller Noever
    http://arxiv.org/abs/2103.00602v1

    • [cs.CV]A 3D model-based approach for fitting masks to faces in the wild
    Je Hyeong Hong, Hanjo Kim, Minsoo Kim, Gi Pyo Nam, Junghyun Cho, Hyeong-Seok Ko, Ig-Jae Kim
    http://arxiv.org/abs/2103.00803v1

    • [cs.CV]A Comprehensive Study on Face Recognition Biases Beyond Demographics
    Philipp Terhörst, Jan Niklas Kolf, Marco Huber, Florian Kirchbuchner, Naser Damer, Aythami Morales, Julian Fierrez, Arjan Kuijper
    http://arxiv.org/abs/2103.01592v1

    • [cs.CV]A Deep Emulator for Secondary Motion of 3D Characters
    Mianlun Zheng, Yi Zhou, Duygu Ceylan, Jernej Barbic
    http://arxiv.org/abs/2103.01261v1

    • [cs.CV]A Driving Behavior Recognition Model with Bi-LSTM and Multi-Scale CNN
    He Zhang, Zhixiong Nan, Tao Yang, Yifan Liu, Nanning Zheng
    http://arxiv.org/abs/2103.00801v1

    • [cs.CV]A Little Energy Goes a Long Way: Energy-Efficient, Accurate Conversion from Convolutional Neural Networks to Spiking Neural Networks
    Dengyu Wu, Xinping Yi, Xiaowei Huang
    http://arxiv.org/abs/2103.00944v1

    • [cs.CV]A Novel CNN-LSTM-based Approach to Predict Urban Expansion
    Wadii Boulila, Hamza Ghandorh, Mehshan Ahmed Khan, Fawad Ahmed, Jawad Ahmad
    http://arxiv.org/abs/2103.01695v1

    • [cs.CV]A Pose-only Solution to Visual Reconstruction and Navigation
    Qi Cai, Lilian Zhang, Yuanxin Wu, Wenxian Yu, Dewen Hu
    http://arxiv.org/abs/2103.01530v1

    • [cs.CV]A Structurally Regularized Convolutional Neural Network for Image Classification using Wavelet-based SubBand Decomposition
    Pavel Sinha, Ioannis Psaromiligkos, Zeljko Zilic
    http://arxiv.org/abs/2103.01823v1

    • [cs.CV]A Survey of Deep Learning Techniques for Weed Detection from Images
    A S M Mahmudul Hasan, Ferdous Sohel, Dean Diepeveen, Hamid Laga, Michael G. K. Jones
    http://arxiv.org/abs/2103.01415v1

    • [cs.CV]ADAADepth: Adapting Data Augmentation and Attention for Self-Supervised Monocular Depth Estimation
    Vinay Kaushik, Kartik Jindgar, Brejesh Lall
    http://arxiv.org/abs/2103.00853v1

    • [cs.CV]Achieving Competitive Play Through Bottom-Up Approach in Semantic Segmentation
    E. Pryzant, Q. Deng, B. Mei, E. Shresth
    1a8
    a
    http://arxiv.org/abs/2103.00657v1

    • [cs.CV]Adversarial Reciprocal Points Learning for Open Set Recognition
    Guangyao Chen, Peixi Peng, Xiangqian Wang, Yonghong Tian
    http://arxiv.org/abs/2103.00953v2

    • [cs.CV]All at Once Network Quantization via Collaborative Knowledge Transfer
    Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Naigang Wang, Bowen Pan Kailash Gopalakrishnan, Aude Oliva, Rogerio Feris, Kate Saenko
    http://arxiv.org/abs/2103.01435v1

    • [cs.CV]Am I a Real or Fake Celebrity? Measuring Commercial Face Recognition Web APIs under Deepfake Impersonation Attack
    Shahroz Tariq, Sowon Jeon, Simon S. Woo
    http://arxiv.org/abs/2103.00847v2

    • [cs.CV]An Interpretable Multiple-Instance Approach for the Detection of referable Diabetic Retinopathy from Fundus Images
    Alexandros Papadopoulos, Fotis Topouzis, Anastasios Delopoulos
    http://arxiv.org/abs/2103.01702v1

    • [cs.CV]AttriMeter: An Attribute-guided Metric Interpreter for Person Re-Identification
    Xiaodong Chen, Xinchen Liu, Wu Liu, Xiao-Ping Zhang, Yongdong Zhang, Tao Mei
    http://arxiv.org/abs/2103.01451v1

    • [cs.CV]Auto-Exposure Fusion for Single-Image Shadow Removal
    Lan Fu, Changqing Zhou, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Wei Feng, Yang Liu, Song Wang
    http://arxiv.org/abs/2103.01255v1

    • [cs.CV]Automatic Stockpile Volume Monitoring using Multi-view Stereo from SkySat Imagery
    Roger Marí, Carlo de Franchis, Enric Meinhardt-Llopis, Gabriele Facciolo
    http://arxiv.org/abs/2103.00945v1

    • [cs.CV]Brain Programming is Immune to Adversarial Attacks: Towards Accurate and Robust Image Classification using Symbolic Learning
    Gerardo Ibarra-Vazquez, Gustavo Olague, Mariana Chan-Ley, Cesar Puente, Carlos Soubervielle-Montalvo
    http://arxiv.org/abs/2103.01359v1

    • [cs.CV]Brain-inspired algorithms for processing of visual data
    Nicola Strisciuglio
    http://arxiv.org/abs/2103.01634v1

    • [cs.CV]Categorical Depth Distribution Network for Monocular 3D Object Detection
    Cody Reading, Ali Harakeh, Julia Chae, Steven L. Waslander
    http://arxiv.org/abs/2103.01100v1

    • [cs.CV]Coarse-Fine Networks for Temporal Activity Detection in Videos
    Kumara Kahatapitiya, Michael S. Ryoo
    http://arxiv.org/abs/2103.01302v1

    • [cs.CV]Comparison of Methods Generalizing Max- and Average-Pooling
    Florentin Bieder, Robin Sandkühler, Philippe C. Cattin
    http://arxiv.org/abs/2103.01746v1

    • [cs.CV]Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation
    Yukun Su, Ruizhou Sun, Guosheng Lin, Qingyao Wu
    http://arxiv.org/abs/2103.01795v1

    • [cs.CV]Contextually Guided Convolutional Neural Networks for Learning Most Transferable Representations
    Olcay Kursun, Semih Dinc, Oleg V. Favorov
    http://arxiv.org/abs/2103.01566v1

    • [cs.CV]Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training
    Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
    http://arxiv.org/abs/2103.00673v1

    • [cs.CV]Counterfactual Zero-Shot and Open-Set Visual Recognition
    Zhongqi Yue, Tan Wang, Hanwang Zhang, Qianru Sun, Xian-Sheng Hua
    http://arxiv.org/abs/2103.00887v1

    • [cs.CV]Cross Modal Focal Loss for RGBD Face Anti-Spoofing
    Anjith George, Sebastien Marcel
    http://arxiv.org/abs/2103.00948v1

    • [cs.CV]DF-VO: What Should Be Learnt for Visual Odometry?
    Huangying Zhan, Chamara Saroj Weerasekera, Jia-Wang Bian, Ravi Garg, Ian Reid
    http://arxiv.org/abs/2103.00933v1

    • [cs.CV]DR-TANet: Dynamic Receptive Temporal Attention Network for Street Scene Change Detection
    Shuo Chen, Kailun Yang, Rainer Stiefelhagen
    http://arxiv.org/abs/2103.00879v1

    • [cs.CV]DST: Data Selection and joint Training for Learning with Noisy Labels
    Yi Wei, Xue Mei, Xin Liu, Pengxiang Xu
    http://arxiv.org/abs/2103.00813v1

    • [cs.CV]Deep Perceptual Image Quality Assessment for Compression
    Juan Carlos Mier, Eddie Huang, Hossein Talebi, Feng Yang, Peyman Milanfar
    http://arxiv.org/abs/2103.01114v1

    • [cs.CV]Deep learning based geometric registration for medical images: How accurate can we get without visual features?
    Lasse Hansen, Mattias P. Heinrich
    http://arxiv.org/abs/2103.00885v1

    • [cs.CV]Depth from Camera Motion and Object Detection
    Brent A. Griffin, Jason J. Corso
    http://arxiv.org/abs/2103.01468v1

    • [cs.CV]Detection and Rectification of Arbitrary Shaped Scene Texts by using Text Keypoints and Links
    Chuhui Xue, Shijian Lu, Steven Hoi
    http://arxiv.org/abs/2103.00785v1

    • [cs.CV]Diffusion Probabilistic Models for 3D Point Cloud Generation
    Shitong Luo, Wei Hu
    http://arxiv.org/abs/2103.01458v1

    • [cs.CV]Diversifying Sample Generation for Accurate Data-Free Quantization
    Xiangguo Zhang, Haotong Qin, Yifu Ding, Ruihao Gong, Qinghua Yan, Renshuai Tao, Yuhang Li, Fengwei Yu, Xianglong Liu
    http://arxiv.org/abs/2103.01049v1

    • [cs.CV]Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
    Jiakai Wang, Aishan Liu, Zixin Yin, Shunchang Liu, Shiyu Tang, Xianglong Liu
    http://arxiv.org/abs/2103.01050v1

    • [cs.CV]Embedded Knowledge Distillation in Depth-level Dynamic Neural Network
    Shuchang Lyu, Ting-Bing Xu, Guangliang Cheng
    http://arxiv.org/abs/2103.00793v1

    • [cs.CV]Emotion pattern detection on facial videos using functional statistics
    Rongjiao Ji, Alessandra Micheletti, Natasa Krklec Jerinkic, Zoranka Desnica
    http://arxiv.org/abs/2103.00844v1

    • [cs.CV]Emotion recognition techniques with rule based and machine learning approaches
    Aasma Aslam, Babar Hussian
    http://arxiv.org/abs/2103.00658v1

    • [cs.CV]Exploiting latent representation of sparse semantic layers for improved short-term motion prediction with Capsule Networks
    Albert Dulian, John C. Murray
    http://arxiv.org/abs/2103.01644v1

    • [cs.CV]Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
    Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah
    http://arxiv.org/abs/2103.01315v1

    • [cs.CV]Exploring the high dimensional geometry of HSI features
    Wojciech Czaja, Ilya Kavalerov, Weilin Li
    http://arxiv.org/abs/2103.01303v1

    • [cs.CV]FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation
    Aoran Xiao, Xiaofei Yang, Shijian Lu, Dayan Guan, Jiaxing Huang
    http://arxiv.org/abs/2103.00738v1

    • [cs.CV]Few-Shot Lifelong Learning
    Pratik Mazumder, Pravendra Singh, Piyush Rai
    http://arxiv.org/abs/2103.00991v1

    • [cs.CV]Few-shot Open-set Recognition by Transformation Consistency
    Minki Jeong, Seokeon Choi, Changick Kim
    http://arxiv.org/abs/2103.01537v1

    • [cs.CV]FineNet: Frame Interpolation and Enhancement for Face Video Deblurring
    Phong Tran, Anh Tran, Thao Nguyen, Minh Hoai
    http://arxiv.org/abs/2103.00871v1

    • [cs.CV]Fixing Data Augmentation to Improve Adversarial Robustness
    Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian, Florian Stimberg, Olivia Wiles, Timothy Mann
    http://arxiv.org/abs/2103.01946v1

    • [cs.CV]Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning
    David Williams, Matthew Gadd, Daniele De Martini, Paul Newman
    http://arxiv.org/abs/2103.00869v1

    • [cs.CV]Generative Adversarial Transformers
    Drew A. Hudson, C. Lawrence Zitnick
    http://arxiv.org/abs/2103.01209v2

    • [cs.CV]Geometry-Guided Street-View Panorama Synthesis from Satellite Imagery
    Yujiao Shi, Dylan Campbell, Xin Yu, Hongdong Li
    http://arxiv.org/abs/2103.01623v1

    • [cs.CV]HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline
    Konrad Heidler, Lichao Mou, Celia Baumhoer, Andreas Dietz, Xiao Xiang Zhu
    http://arxiv.org/abs/2103.01849v1

    • [cs.CV]Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph
    Xin Ye, Yezhou Yang
    http://arxiv.org/abs/2103.01350v1

    • [cs.CV]IdentityDP: Differential Private Identification Protection for Face Images
    Yunqian Wen, Li Song, Bo Liu, Ming Ding, Rong Xie
    http://arxiv.org/abs/2103.01745v1

    • [cs.CV]Image-to-image Translation via Hierarchical Style Disentanglement
    Xinyang Li, Shengchuan Zhang, Jie Hu, Liujuan Cao, Xiaopeng Hong, Xudong Mao, Feiyue Huang, Yongjian Wu, Rongrong Ji
    http://arxiv.org/abs/2103.01456v1

    • [cs.CV]Image/Video Deep Anomaly Detection: A Survey
    Bahram Mohammadi, Mahmood Fathy, Mohammad Sabokrou
    http://arxiv.org/abs/2103.01739v1

    • [cs.CV]Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation
    Lie Ju, Xin Wang, Lin Wang, Dwarikanath Mahapatra, Xin Zhao, Mehrtash Harandi, Tom Drummond, Tongliang Liu, Zongyuan Ge
    http://arxiv.org/abs/2103.00528v1

    • [cs.CV]InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring
    Zhihao Yuan, Xu Yan, Yinghong Liao, Ruimao Zhang, Zhen Li, Shuguang Cui
    http://arxiv.org/abs/2103.01128v1

    • [cs.CV]Inter-class Discrepancy Alignment for Face Recognition
    Jiaheng Liu, Yudong Wu, Yichao Wu, Zhenmao Li, Chen Ken, Ding Liang, Junjie Yan
    http://arxiv.org/abs/2103.01559v1

    • [cs.CV]Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing
    Danfeng Hong, Wei He, Naoto Yokoya, Jing Yao, Lianru Gao, Liangpei Zhang, Jocelyn Chanussot, Xiao Xiang Zhu
    http://arxiv.org/abs/2103.01449v1

    • [cs.CV]Learning Frequency Domain Approximation for Binary Neural Networks
    Yixing Xu, Kai Han, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang
    http://arxiv.org/abs/2103.00841v1

    • [cs.CV]Learning for Visual Navigation by Imagining the Success
    Mahdi Kazemi Moghaddam, Ehsan Abbasnejad, Qi Wu, Javen Shi, Anton Van Den Hengel
    http://arxiv.org/abs/2103.00446v1

    • [cs.CV]Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
    Chongyi Li, Chunle Guo, Chen Change Loy
    http://arxiv.org/abs/2103.00860v1

    • [cs.CV]MFST: Multi-Features Siamese Tracker
    Zhenxi Li, Guillaume-Alexandre Bilodeau, Wassim Bouachir
    http://arxiv.org/abs/2103.00810v1

    • [cs.CV]Masked Face Recognition: Human vs. Machine
    Naser Damer, Fadi Boutros, Marius Süßmilch, Meiling Fang, Florian Kirchbuchner, Arjan Kuijper
    http://arxiv.org/abs/2103.01924v1

    • [cs.CV]Maximal function pooling with applications
    Wojciech Czaja, Weilin Li, Yiran Li, Mike Pekala
    http://arxiv.org/abs/2103.01292v1

    • [cs.CV]Medical Image Segmentation with Limited Supervision: A Review of Deep Network Models
    Jialin Peng, Ye Wang
    http://arxiv.org/abs/2103.00429v1

    • [cs.CV]Model-Agnostic Defense for Lane Detection against Adversarial Attack
    Henry Xu, An Ju, David Wagner
    http://arxiv.org/abs/2103.00663v1

    • [cs.CV]Multiclass Burn Wound Image Classification Using Deep Convolutional Neural Networks
    Behrouz Rostami, Jeffrey Niezgoda, Sandeep Gopalakrishnan, Zeyun Yu
    http://arxiv.org/abs/2103.01361v1

    • [cs.CV]Multiple Convolutional Features in Siamese Networks for Object Tracking
    Zhenxi Li, Guillaume-Alexandre Bilodeau, Wassim Bouachir
    http://arxiv.org/abs/2103.01222v1

    • [cs.CV]NLP-CUET@DravidianLangTech-EACL2021: Investigating Visual and Textual Features to Identify Trolls from Multimodal Social Media Memes
    Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque
    http://arxiv.org/abs/2103.00466v1

    • [cs.CV]Network Pruning via Resource Reallocation
    Yuenan Hou, Zheng Ma, Chunxiao Liu, Zhe Wang, Chen Change Loy
    http://arxiv.org/abs/2103.01847v1

    • [cs.CV]NeuTex: Neural Texture Mapping for Volumetric Neural Rendering
    Fanbo Xiang, Zexiang Xu, Miloš Hašan, Yannick Hold-Geoffroy, Kalyan Sunkavalli, Hao Su
    http://arxiv.org/abs/2103.00762v1

    • [cs.CV]OMNet: Learning Overlapping Mask for Partial-to-Partial Point Cloud Registration
    Hao Xu, Shuaicheng Liu, Guangfu Wang, Guanghui Liu, Bing Zeng
    http://arxiv.org/abs/2103.00937v2

    • [cs.CV]OmniNet: Omnidirectional Representations from Transformers
    Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Donald Metzler
    http://arxiv.org/abs/2103.01075v1

    • [cs.CV]On the Generalisation Capabilities of Fisher Vector based Face Presentation Attack Detection
    Lázaro J. González-Soler, Marta Gomez-Barrero, Christoph Busch
    http://arxiv.org/abs/2103.01721v1

    • [cs.CV]OpenICS: Open Image Compressive Sensing Toolbox and Benchmark
    Jonathan Zhao, Matthew Westerham, Mark Lakatos-Toth, Zhikang Zhang, Avi Moskoff, Fengbo Ren
    http://arxiv.org/abs/2103.00652v1

    • [cs.CV]Over-sampling De-occlusion Attention Network for Prohibited Items Detection in Noisy X-ray Images
    Renshuai Tao, Yanlu Wei, Hainan Li, Aishan Liu, Yifu Ding, Haotong Qin, Xianglong Liu
    http://arxiv.org/abs/2103.00809v1

    • [cs.CV]P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching
    Bing Wang, Changhao Chen, Zhaopeng Cui, Jie Qin, Chris Xiaoxuan Lu, Zhengdi Yu, Peijun Zhao, Zhen Dong, Fan Zhu, Niki Trigoni, Andrew Markham
    http://arxiv.org/abs/2103.01055v1

    • [cs.CV]Panoramic Panoptic Segmentation: Towards Complete Surrounding Understanding via Unsupervised Contrastive Learning
    Alexander Jaus, Kailun Yang, Rainer Stiefelhagen
    http://arxiv.org/abs/2103.00868v1

    • [cs.CV]Part2Whole: Iteratively Enrich Detail for Cross-Modal Retrieval with Partial Query
    Guanyu Cai, Xinyang Jiang, Jun Zhang, Yifei Gong, Lianghua He, Pai Peng, Xiaowei Guo, Xing Sun
    http://arxiv.org/abs/2103.01654v1

    • [cs.CV]Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
    Stephen Hausler, Sourav Garg, Ming Xu, Michael Milford, Tobias Fischer
    http://arxiv.org/abs/2103.01486v1

    • [cs.CV]Perspectives on individual animal identification from biology and computer vision
    Maxime Vidal, Nathan Wolf, Beth Rosenberg, Bradley P. Harris, Alexander Mathis
    http://arxiv.org/abs/2103.00560v1

    • [cs.CV]Predicting Video with VQVAE
    Jacob Walker, Ali Razavi, Aäron van den Oord
    http://arxiv.org/abs/2103.01950v1

    • [cs.CV]Predicting post-operative right ventricular failure using video-based deep learning
    Rohan Shad, Nicolas Quach, Robyn Fong, Patpilai Kasinpila, Cayley Bowles, Miguel Castro, Ashrith Guha, Eddie Suarez, Stefan Jovinge, Sangjin Lee, Theodore Boeve, Myriam Amsallem, Xiu Tang, Francois Haddad, Yasuhiro Shudo, Y. Joseph Woo, Jeffrey Teuteberg, John P. Cunningham, Curt P. Langlotz, William Hiesinger
    http://arxiv.org/abs/2103.00364v1

    • [cs.CV]Real Masks and Fake Faces: On the Masked Face Presentation Attack Detection
    Meiling Fang, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
    http://arxiv.org/abs/2103.01546v1

    • [cs.CV]Representation Learning for Event-based Visuomotor Policies
    Sai Vemprala, Sami Mian, Ashish Kapoor
    http://arxiv.org/abs/2103.00806v1

    • [cs.CV]SUM: A Benchmark Dataset of Semantic Urban Meshes
    Weixiao Gao, Liangliang Nan, Bas Boom, Hugo Ledoux
    http://arxiv.org/abs/2103.00355v1

    • [cs.CV]Scalable Scene Flow from Point Clouds in the Real World
    Philipp Jund, Chris Sweeney, Nichola Abdo, Zhifeng Chen, Jonathon Shlens
    http://arxiv.org/abs/2103.01306v1

    • [cs.CV]Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations
    Xiang Gao, Wei Hu, Guo-Jun Qi
    http://arxiv.org/abs/2103.00787v1

    • [cs.CV]Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map
    Elmira Amirloo, Mohsen Rohani, Ershad Banijamali, Jun Luo, Pascal Poupart
    http://arxiv.org/abs/2103.01039v1

    • [cs.CV]Self-supervised Low Light Image Enhancement and Denoising
    Yu Zhang, Xiaoguang Di, Bin Zhang, Qingyan Li, Shiyu Yan, Chunhui Wang
    http://arxiv.org/abs/2103.00832v1

    • [cs.CV]Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection
    Chenchen Zhu, Fangyi Chen, Uzair Ahmed, Marios Savvides
    http://arxiv.org/abs/2103.01903v1

    • [cs.CV]Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation
    Manish Sahu, Anirban Mukhopadhyay, Stefan Zachow
    http://arxiv.org/abs/2103.01593v1

    • [cs.CV]Single-Shot Motion Completion with Transformer
    Yinglin Duan, Tianyang Shi, Zhengxia Zou, Yenan Lin, Zhehui Qian, Bohan Zhang, Yi Yuan
    http://arxiv.org/abs/2103.00776v1

    • [cs.CV]Snowy Night-to-Day Translator and Semantic Segmentation Label Similarity for Snow Hazard Indicator
    Takato Yasuno, Hiroaki Sugawara, Junichiro Fujii, Ryuto Yoshida
    http://arxiv.org/abs/2103.00545v1

    • [cs.CV]Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain
    Honggu Liu, Xiaodan Li, Wenbo Zhou, Yuefeng Chen, Yuan He, Hui Xue, Weiming Zhang, Nenghai Yu
    http://arxiv.org/abs/2103.01856v1

    • [cs.CV]Square Root Bundle Adjustment for Large-Scale Reconstruction
    Nikolaus Demmel, Christiane Sommer, Daniel Cremers, Vladyslav Usenko
    http://arxiv.org/abs/2103.01843v1

    • [cs.CV]Systematic Analysis and Removal of Circular Artifacts for StyleGAN
    Way Tan, Bihan Wen, Xulei Yang
    http://arxiv.org/abs/2103.01090v1

    • [cs.CV]There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
    Francisco Rivera Valverde, Juana Valeria Hurtado, Abhinav Valada
    http://arxiv.org/abs/2103.01353v1

    • [cs.CV]Towards Continual, Online, Unsupervised Depth
    Muhammad Umar Karim Khan
    http://arxiv.org/abs/2103.00369v2

    • [cs.CV]Towards Precise and Efficient Image Guided Depth Completion
    Mu Hu, Shuling Wang, Bin Li, Shiyu Ning, Li Fan, Xiaojin Gong
    http://arxiv.org/abs/2103.00783v1

    • [cs.CV]Training Generative Adversarial Networks in One Stage
    Chengchao Shen, Youtan Yin, Xinchao Wang, Xubin LI, Jie Song, Mingli Song
    http://arxiv.org/abs/2103.00430v1

    • [cs.CV]TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning
    Bingyan Liu, Yifeng Cai, Yao Guo, Xiangqun Chen
    http://arxiv.org/abs/2103.01542v1

    • [cs.CV]Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery
    Chen Wu, Sihan Zhu, Jiaqi Yang, Meiqi Hu, Bo Du, Liangpei Zhang, Lefei Zhang, Chengxi Han, Meng Lan
    http://arxiv.org/abs/2103.01717v1

    • [cs.CV]Universal-Prototype Augmentation for Few-Shot Object Detection
    Aming Wu, Yahong Han, Linchao Zhu, Yi Yang, Cheng Deng
    http://arxiv.org/abs/2103.01077v1

    • [cs.CV]Unmasking Face Embeddings by Self-restrained Triplet Loss for Accurate Masked Face Recognition
    Fadi Boutros, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
    http://arxiv.org/abs/2103.01716v1

    • [cs.CV]Unsupervised Depth and Ego-motion Estimation for Monocular Thermal Video using Multi-spectral Consistency Loss
    Ukcheol Shin, Kyunghyun Lee, SeokJu Lee, In So Kweon
    http://arxiv.org/abs/2103.00760v1

    • [cs.CV]Using CNNs to Identify the Origin of Finger Vein Image
    Babak Maser, Andreas Uhl
    http://arxiv.org/abs/2103.01632v1

    • [cs.CV]WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
    Krishna Srinivasan, Karthik Raman, Jiecao Chen, Michael Bendersky, Marc Najork
    http://arxiv.org/abs/2103.01913v1

    • [cs.CV]When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework
    Zhizhong Huang, Junping Zhang, Hongming Shan
    http://arxiv.org/abs/2103.01520v1

    • [cs.CY]An Analysis of Distributed Systems Syllabi With a Focus on Performance-Related Topics
    Cristina L. Abad, Alexandru Iosup, Edwin F. Boza, Eduardo Ortiz-Holguin
    http://arxiv.org/abs/2103.01858v1

    • [cs.CY]COVID-19 vs Social Media Apps: Does Privacy Really Matter?
    Omar Haggag, Sherif Haggag, John Grundy, Mohamed Abdelrazek
    http://arxiv.org/abs/2103.01779v1

    • [cs.CY]Current eHealth Challenges and recent trends in eHealth applications
    Muhammad Mudassar Qureshi, Amjad Farooq, Muhammad Mazhar Qureshi
    http://arxiv.org/abs/2103.01756v1

    • [cs.CY]Dados Abertos Governamentais no contexto de Políticas Públicas de Saúde e Sistemas Prisionais: Realidade ou Utopia?
    Rafael Antônio Lima Cardoso, Glauco de Figueiredo Carneiro, José Euclimar Xavier de Menezes
    http://arxiv.org/abs/2103.00541v1

    • [cs.CY]Digital History and History Teaching in the Digital Age
    Maria Papadopoulou, Zacharoula Smyrnaiou
    http://arxiv.org/abs/2103.00473v1

    • [cs.CY]Language-agnostic Topic Classification for Wikipedia
    Isaac Johnson, Martin Gerlach, Diego Sáez-Trumper
    http://arxiv.org/abs/2103.00068v1

    • [cs.CY]Morning or Evening? An Examination of Circadian Rhythms of CS1 Students
    Albina Zavgorodniaia, Raj Shrestha, Juho Leinonen, Arto Hellas, John Edwards
    http://arxiv.org/abs/2103.01752v1

    • [cs.CY]Narratives and Counternarratives on Data Sharing in Africa
    Rediet Abebe, Kehinde Aruleba, Abeba Birhane, Sara Kingsley, George Obaido, Sekou L. Remy, Swathi Sadagopan
    http://arxiv.org/abs/2103.01168v1

    • [cs.CY]Reasons, Values, Stakeholders: A Philosophical Framework for Explainable Artificial Intelligence
    Atoosa Kasirzadeh
    http://arxiv.org/abs/2103.00752v1

    • [cs.CY]Reflections on the Clinical Acceptance of Artificial Intelligence
    Jens Schneider, Marco Agus
    http://arxiv.org/abs/2103.01149v1

    • [cs.CY]The Healthy States of America: Creating a Health Taxonomy with Social Media
    Sanja Scepanovic, Luca Maria Aiello, Ke Zhou, Sagar Joglekar, Daniele Quercia
    http://arxiv.org/abs/2103.01169v1

    • [cs.CY]The Rise of a New Digital Third Space Professional in Higher Education: Recognising Research Software Engineering
    Shoaib Sufi
    http://arxiv.org/abs/2103.01041v1

    • [cs.CY]Understanding the Complexity of Detecting Political Ads
    Vera Sosnovik, Oana Goga
    http://arxiv.org/abs/2103.00822v1

    • [cs.CY]Unsupervised Representations Predict Popularity of Peer-Shared Artifacts in an Online Learning Environment
    Renzhe Yu, John Scott, Zachary A. Pardos
    http://arxiv.org/abs/2103.00163v1

    • [cs.DB]CARMI: A Cache-Aware Learned Index with a Cost-based Construction Algorithm
    Jiaoyi Zhang, Yihan Gao
    http://arxiv.org/abs/2103.00858v1

    • [cs.DC]A Soft Method for Outliers Detection at the Edge of the Network
    Kostas Kolomvatsos, Christos Anagnostopoulos
    http://arxiv.org/abs/2103.00179v1

    • [cs.DC]Accelerating Distributed-Memory Autotuning via Statistical Analysis of Execution Paths
    Edward Hutter, Edgar Solomonik
    http://arxiv.org/abs/2103.01304v1

    • [cs.DC]An HPC-Based Hydrothermal Finite Element Simulator for Modeling Underground Response to Community-Scale Geothermal Energy Production
    Xiang Sun, Kenichi Soga, Alp Cinar, Zhenxiang Su, Kecheng Chen, Krishna Kumar, Patrick F. Dobson, Peter S. Nico
    http://arxiv.org/abs/2103.00081v1

    • [cs.DC]An intelligent Data Delivery Service for and beyond the ATLAS experiment
    Wen Guan, Tadashi Maeno, Brian Paul Bockelman, Torre Wenaus, Fahui Lin, Siarhei Padolski, Rui Zhang, Aleksandr Alekseev
    http://arxiv.org/abs/2103.00523v1

    • [cs.DC]Coffea-casa: an analysis facility prototype
    Matous Adamec, Garhan Attebury, Kenneth Bloom, Brian Bockelman, Carl Lundstedt, Oksana Shadura, John Thiltges
    http://arxiv.org/abs/2103.01871v1

    • [cs.DC]Design and Performance Characterization of RADICAL-Pilot on Leadership-class Platforms
    Andre Merzky, Matteo Turilli, Mikhail Titov, Aymen Al-Saadi, Shantenu Jha
    http://arxiv.org/abs/2103.00091v1

    • [cs.DC]Efficient Soft-Error Detection for Low-precision Deep Learning Recommendation Models
    Sihuan Li, Jianyu Huang, Ping Tak Peter Tang, Daya Khudia, Jongsoo Park, Harish Dattatraya Dixit, Zizhong Chen
    http://arxiv.org/abs/2103.00130v1

    • [cs.DC]Inferring Unobserved Events in Systems With Shared Resources and Queues
    Dirk Fahland, Vadim Denisov, Wil. M. P. van der Aalst
    http://arxiv.org/abs/2103.00167v1

    • [cs.DC]LEAF: Simulating Large Energy-Aware Fog Computing Environments
    Philipp Wiesner, Lauritz Thamsen
    http://arxiv.org/abs/2103.01170v1

    • [cs.DC]Memory Reclamation for Recoverable Mutual Exclusion
    Sahil Dhoked, Neeraj Mittal
    http://arxiv.org/abs/2103.01538v1

    • [cs.DC]On the Utility of Gradient Compression in Distributed Training Systems
    Saurabh Agarwal, Hongyi Wang, Shivaram Venkataraman, Dimitris Papailiopoulos
    http://arxiv.org/abs/2103.00543v1

    • [cs.DC]Parallel In-Place Algorithms: Theory and Practice
    Yan Gu, Omar Obeya, Julian Shun
    http://arxiv.org/abs/2103.01216v1

    • [cs.DC]Parallel Machine Learning of Partial Differential Equations
    Amin Totounferoush, Neda Ebrahimi Pour, Sabine Roller, Miriam Mehl
    http://arxiv.org/abs/2103.01869v1

    • [cs.DC]Performance Optimization of SU3_Bench on Xeon and Programmable Integrated Unified Memory Architecture
    Jesmin Jahan Tithi, Fabio Checconi, Douglas Doerfler, Fabrizio Petrini
    http://arxiv.org/abs/2103.00571v1

    • [cs.DC]Reasons behind growing adoption of Cloud after Covid-19 Pandemic and Challenges ahead
    Mayank Gokarna
    http://arxiv.org/abs/2103.00176v1

    • [cs.DC]Scalable communication for high-order stencil computations using CUDA-aware MPI
    Johannes Pekkilä, Miikka S. Väisälä, Maarit J. Käpylä, Matthias Rheinhardt, Oskar Lappi
    http://arxiv.org/abs/2103.01597v1

    • [cs.DC]Serverless Workflows with Durable Functions and Netherite
    Sebastian Burckhardt, Chris Gillum, David Justo, Konstantinos Kallas, Connor McMahon, Christopher S. Meiklejohn
    http://arxiv.org/abs/2103.00033v1

    • [cs.DC]The Difficulty in Scaling Blockchains: A Simple Explanation
    Maarten van Steen, Andrew Chien, Patrick Eugster
    http://arxiv.org/abs/2103.01487v1

    • [cs.DM]Nested Vehicle Routing Problem: Optimizing Drone-Truck Surveillance Operations
    Fanruiqi Zeng, Zaiwei Chen, John-Paul Clarke, David Goldsman
    http://arxiv.org/abs/2103.01528v1

    • [cs.DS]An Introduction to Johnson-Lindenstrauss Transforms
    Casper Benjamin Freksen
    http://arxiv.org/abs/2103.00564v1

    • [cs.GR]Mixture of Volumetric Primitives for Efficient Neural Rendering
    Stephen Lombardi, Tomas Simon, Gabriel Schwartz, Michael Zollhoefer, Yaser Sheikh, Jason Saragih
    http://arxiv.org/abs/2103.01954v1

    • [cs.GT]Better Together? How Externalities of Size Complicate Notions of Solidarity and Actuarial Fairness
    Kate Donahue, Solon Barocas
    http://arxiv.org/abs/2103.00347v1

    • [cs.GT]Information Discrepancy in Strategic Learning
    Yahav Bechavod, Chara Podimata, Zhiwei Steven Wu, Juba Ziani
    http://arxiv.org/abs/2103.01028v1

    • [cs.HC]Anticipation Next — System-sensitive technology development and integration in work contexts
    Sarah Janboecke, Susanne Zajitschek
    http://arxiv.org/abs/2103.00923v1

    • [cs.HC]Between Post-Flaneur and Smartphone Zombie Smartphone Users Altering Visual Attention and Walking Behavior in Public Space
    Gorsev Argin, Burak Pak, Handan Turkoglu
    http://arxiv.org/abs/2103.01217v1

    • [cs.HC]Towards a Better Understanding of Social Acceptability
    Alarith Uhde, Marc Hassenzahl
    http://arxiv.org/abs/2103.01637v1

    • [cs.HC]Visualizing Rule Sets: Exploration and Validation of a Design Space
    Jun Yuan, Oded Nov, Enrico Bertini
    http://arxiv.org/abs/2103.01022v1

    • [cs.IR]A Linguistic Study on Relevance Modeling in Information Retrieval
    Yixing Fan, Jiafeng Guo, Xinyu Ma, Ruqing Zhang, Yanyan Lan, Xueqi Cheng
    http://arxiv.org/abs/2103.00956v1

    • [cs.IR]An Efficient Indexing and Searching Technique for Information Retrieval for Urdu Language
    Muhammad Mudassar Qureshi, Muhammad Shoaib, Kalsoom
    http://arxiv.org/abs/2103.00532v1

    • [cs.IR]An open-source framework for ExpFinder integrating 今日学术视野(2021.3.4) - 图6-gram Vector Space Model and 今日学术视野(2021.3.4) - 图7CO-HITS
    Hung Du, Yong-Bin Kang
    http://arxiv.org/abs/2103.00917v1

    • [cs.IR]Automated Creative Optimization for E-Commerce Advertising
    Jin Chen, Ju Xu, Gangwei Jiang, Tiezheng Ge, Zhiqiang Zhang, Defu Lian, Kai Zheng
    http://arxiv.org/abs/2103.00436v1

    • [cs.IR]Cross-Domain Recommendation: Challenges, Progress, and Prospects
    Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, Guanfeng Liu
    http://arxiv.org/abs/2103.01696v1

    • [cs.IR]Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure
    Jin Chen, Tiezheng Ge, Gangwei Jiang, Zhiqiang Zhang, Defu Lian, Kai Zheng
    http://arxiv.org/abs/2103.01453v1

    • [cs.IR]Explore User Neighborhood for Real-time E-commerce Recommendation
    Xu Xie, Fei Sun, Xiaoyong Yang, Zhao Yang, Jinyang Gao, Wenwu Ou, Bin Cui
    http://arxiv.org/abs/2103.00442v1

    • [cs.IR]High-Performance Training by Exploiting Hot-Embeddings in Recommendation Systems
    Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, Prashant J. Nair
    http://arxiv.org/abs/2103.00686v1

    • [cs.IR]LRG at TREC 2020: Document Ranking with XLNet-Based Models
    Abheesht Sharma, Harshit Pandey
    http://arxiv.org/abs/2103.00380v1

    • [cs.IR]On Estimating Recommendation Evaluation Metrics under Sampling
    Ruoming Jin, Dong Li, Benjamin Mudrak, Jing Gao Zhi Liu
    http://arxiv.org/abs/2103.01474v1

    • [cs.IR]Parallel Algorithms for Densest Subgraph Discovery Using Shared Memory Model
    B. D. M. De Zoysa, Y. A. M. M. A. Ali, M. D. I. Maduranga, Indika Perera, Saliya Ekanayake, Anil Vullikanti
    http://arxiv.org/abs/2103.00154v1

    • [cs.IR]Query Rewriting via Cycle-Consistent Translation for E-Commerce Search
    Yiming Qiu, Kang Zhang, Han Zhang, Songlin Wang, Sulong Xu, Yun Xiao, Bo Long, Wen-Yun Yang
    http://arxiv.org/abs/2103.00800v1

    • [cs.IT]6G Downlink Transmission via Rate Splitting Space Division Multiple Access Based on Grouped Code Index Modulation
    Wenchao Zhai, Yishan Wu, Jun Zhao, Huimei Han
    http://arxiv.org/abs/2103.00829v1

    • [cs.IT]Active Reconfigurable Intelligent Surface Aided Wireless Communications
    Ruizhe Long, Ying-Chang Liang, Yiyang Pei, Erik G. Larsson
    http://arxiv.org/abs/2103.00709v1

    • [cs.IT]Adaptive Transmission Scheduling in Wireless Networks for Asynchronous Federated Learning
    Hyun-Suk Lee, Jang-Won Lee
    http://arxiv.org/abs/2103.01422v1

    • [cs.IT]Angle-Domain Intelligent Reflecting Surface Systems: Design and Analysis
    Xiaoling Hu, Caijun Zhong, Zhaoyang Zhang
    http://arxiv.org/abs/2103.00934v1

    • [cs.IT]Burst-Error Propagation Suppression for Decision-Feedback Equalizer in Field-Trial Submarine Fiber-Optic Communications
    Ji Zhou, Chengkun Yang, Dawei Wang, Qi Sui, Haide Wang, Shecheng Gao, Yuanhua Feng, Weiping Liu, Yuelin Yan, Jianping Li, Changyuan Yu, Zhaohui Li
    http://arxiv.org/abs/2103.00186v1

    • [cs.IT]Channel-Driven Monte Carlo Sampling for Bayesian Distributed Learning in Wireless Data Centers
    Dongzhu Liu, Osvaldo Simeone
    http://arxiv.org/abs/2103.01351v1

    • [cs.IT]Coded Computing via Binary Linear Codes: Designs and Performance Limits
    Mahdi Soleymani, Mohammad Vahid Jamali, Hessam Mahdavifar
    http://arxiv.org/abs/2103.01503v1

    • [cs.IT]Dynamic Oversampling Tecniques for 1-Bit ADCs in Large-Scale MIMO Systems
    Z. Shao, L. Landau, R. de Lamare
    http://arxiv.org/abs/2103.00103v1

    • [cs.IT]Dynamic Sample Complexity for Exact Sparse Recovery using Sequential Iterative Hard Thresholding
    Samrat Mukhopadhyay
    http://arxiv.org/abs/2103.00449v1

    • [cs.IT]Efficient Encoding Algorithm of Binary and Non-Binary LDPC Codes Using Block Triangulation
    Yuta Iketo, Takayuki Nozaki
    http://arxiv.org/abs/2103.01560v1

    • [cs.IT]Expectation-Maximization-Aided Hybrid Generalized Expectation Consistent for Sparse Signal Reconstruction
    Qiuyun Zou, Haochuan Zhang, Hongwen Yang
    http://arxiv.org/abs/2103.01833v1

    • [cs.IT]Explicit Construction of Minimum Bandwidth Rack-Aware Regenerating Codes
    Liyang Zhou, Zhifang Zhang
    http://arxiv.org/abs/2103.01533v1

    • [cs.IT]Gradient Coding with Dynamic Clustering for Straggler-Tolerant Distributed Learning
    Baturalp Buyukates, Emre Ozfatura, Sennur Ulukus, Deniz Gunduz
    http://arxiv.org/abs/2103.01206v1

    • [cs.IT]Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role can RIS Play?
    Wanli Ni, Yuanwei Liu, Zhaohui Yang, Hui Tian, Xuemin Shen
    http://arxiv.org/abs/2103.00435v1

    • [cs.IT]Jamming Aided Covert Communication with Multiple Receivers
    Ke-Wen Huang, Hao Deng, Hui-Ming Wang
    http://arxiv.org/abs/2103.01433v1

    • [cs.IT]Joint Location and Communication Study for Intelligent Reflecting Surface Aided Wireless Communication System
    Rui Wang, Zhe Xing, Erwu Liu
    http://arxiv.org/abs/2103.01063v1

    • [cs.IT]Joint Radar and Communication: A Survey
    Zhiyong Feng, Zixi Fang, Zhiqing Wei, Xu Chen, Zhi Quan, Danna Ji
    http://arxiv.org/abs/2103.00496v1

    • [cs.IT]Learning Robust Beamforming for MISO Downlink Systems
    Junbeom Kim, Hoon Lee, Seok-Hwan Park
    http://arxiv.org/abs/2103.01602v1

    • [cs.IT]Learning-Based Phase Compression and Quantization for Massive MIMO CSI Feedback with Magnitude-Aided Information
    Yu-Chien Lin, Zhi Ding, Zhenyu Liu, Ta-Sung Lee
    http://arxiv.org/abs/2103.00432v1

    • [cs.IT]Low-Complexity Zero-Forcing Precoding for XL-MIMO Transmissions
    Lucas N. Ribeiro, Stefan Schwarz, Martin Haardt
    http://arxiv.org/abs/2103.00971v1

    • [cs.IT]Millimeter Wave and sub-THz Indoor Radio Propagation Channel Measurements, Models, and Comparisons in an Office Environment
    Yunchou Xing, Theodore S. Rappaport, Amitava Ghosh
    http://arxiv.org/abs/2103.00385v1

    • [cs.IT]On Energy Allocation and Data Scheduling in Backscatter Networks with Multi-antenna Readers
    Mohammad Movahednasab, Mohammad Reza Pakravan, Behrooz Makki, Tommy Svensson
    http://arxiv.org/abs/2103.01502v1

    • [cs.IT]On the Connectivity and Giant Component Size of Random K-out Graphs Under Randomly Deleted Nodes
    Eray Can Elumar, Mansi Sood, Osman Yagan
    http://arxiv.org/abs/2103.01471v1

    • [cs.IT]On the Size of Levenshtein Balls
    Daniella Bar-Lev, Tuvi Etzion, Eitan Yaakobi
    http://arxiv.org/abs/2103.01681v1

    • [cs.IT]Optimal Communication-Computation Trade-Off in Heterogeneous Gradient Coding
    Tayyebeh Jahani-Nezhad, Mohammad Ali Maddah-Ali
    http://arxiv.org/abs/2103.01589v1

    • [cs.IT]Passive Beamforming Design and Channel Estimation for IRS Communication System with Few-Bit ADCs
    Jingnan Li, Rui Wang, Erwu Liu
    http://arxiv.org/abs/2103.00463v1

    • [cs.IT]Performance Analysis of OTFS Modulation with Receive Antenna Selection
    Vighnesh S Bhat, G. D. Surabhi, A. Chockalingam
    http://arxiv.org/abs/2103.01563v1

    • [cs.IT]Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation
    Mohamed Seif, Wei-Ting Chang, Ravi Tandon
    http://arxiv.org/abs/2103.01953v1

    • [cs.IT]Propagation Measurements and Path Loss Models for sub-THz in Urban Microcells
    Yunchou Xing, Theodore S. Rappaport
    http://arxiv.org/abs/2103.01151v1

    • [cs.IT]Quantization for spectral super-resolution
    C. Sinan Gunturk, Weilin Li
    http://arxiv.org/abs/2103.00079v1

    • [cs.IT]RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials
    Xilong Pei, Haifan Yin, Li Tan, Lin Cao, Zhanpeng Li, Kai Wang, Kun Zhang, Emil Björnson
    http://arxiv.org/abs/2103.00534v1

    • [cs.IT]Real-time error correction codes for deletable errors
    Ghurumuruhan Ganesan
    http://arxiv.org/abs/2103.00758v1

    • [cs.IT]Secure UAV Random Networks With Minimum Safety Distance
    Jiawei Lyu, Hui-Ming Wang
    http://arxiv.org/abs/2103.01018v1

    • [cs.IT]Signal recovery from a few linear measurements of its high-order spectra
    Tamir Bendory, Dan Edidin, Shay Kreymer
    http://arxiv.org/abs/2103.01551v1

    • [cs.IT]Sparse Activity Detection in Multi-Cell Massive MIMO Exploiting Channel Large-Scale Fading
    Zhilin Chen, Foad Sohrabi, Wei Yu
    http://arxiv.org/abs/2103.00782v1

    • [cs.IT]Stream Distributed Coded Computing
    Alejandro Cohen, Guillaume Thiran, Homa Esfahanizadeh, Muriel Médard
    http://arxiv.org/abs/2103.01921v1

    • [cs.IT]Terahertz Ultra-Massive MIMO-Based Aeronautical Communications in Space-Air-Ground Integrated Networks
    Anwen Liao, Zhen Gao, Dongming Wang, Hua Wang, Hao Yin, Derrick Wing Kwan Ng, Mohamed-Slim Alouini
    http://arxiv.org/abs/2103.01829v1

    • [cs.IT]Terahertz Wireless Communications: Research Issues and Challenges for Active and Passive Systems in Space and on the Ground above 100 GHz
    Yunchou Xing, Theodore S. Rappaport
    http://arxiv.org/abs/2103.00604v1

    • [cs.IT]The Capacity Region of Distributed Multi-User Secret Sharing
    Ali Khalesi, Mahtab Mirmohseni, Mohammad Ali Maddah-Ali
    http://arxiv.org/abs/2103.01568v1

    • [cs.IT]Towards 6G with Connected Sky: UAVs and Beyond
    Mohammad Mozaffari, Xingqin Lin, Stephen Hayes
    http://arxiv.org/abs/2103.01143v1

    • [cs.IT]UAV-Enabled Wireless Power Transfer: A Tutorial Overview
    Lifeng Xie, Xiaowen Cao, Jie Xu, Rui Zhang
    http://arxiv.org/abs/2103.00207v1

    • [cs.LG]A Biased Graph Neural Network Sampler with Near-Optimal Regret
    Qingru Zhang, David Wipf, Quan Gan, Le Song
    http://arxiv.org/abs/2103.01089v1

    • [cs.LG]A Brief Summary of Interactions Between Meta-Learning and Self-Supervised Learning
    Huimin Peng
    http://arxiv.org/abs/2103.00845v1

    • [cs.LG]A HINT from Arithmetic: On Systematic Generalization of Perception, Syntax, and Semantics
    Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
    http://arxiv.org/abs/2103.01403v1

    • [cs.LG]A Kernel Framework to Quantify a Model’s Local Predictive Uncertainty under Data Distributional Shifts
    Rishabh Singh, Jose C. Principe
    http://arxiv.org/abs/2103.01374v1

    • [cs.LG]A Minimax Probability Machine for Non-Decomposable Performance Measures
    Junru Luo, Hong Qiao, Bo Zhang
    http://arxiv.org/abs/2103.00396v1

    • [cs.LG]A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness
    Jacob Abernathy, Pranjal Awasthi, Satyen Kale
    http://arxiv.org/abs/2103.01276v1

    • [cs.LG]A Proof of Concept Neural Network Watchdog using a Hybrid Generative Classifier For Optimized Outlier Detection
    Justin Bui, Robert J. Marks II
    http://arxiv.org/abs/2103.00582v1

    • [cs.LG]A Spectral Enabled GAN for Time Series Data Generation
    Kaleb E. Smith, Anthony O. Smith
    http://arxiv.org/abs/2103.01904v1

    • [cs.LG]A Survey On Universal Adversarial Attack
    Chaoning Zhang, Philipp Benz, Chenguo Lin, Adil Karjauv, Jing Wu, In So Kweon
    http://arxiv.org/abs/2103.01498v1

    • [cs.LG]A Survey on Deep Semi-supervised Learning
    Xiangli Yang, Zixing Song, Irwin King, Zenglin Xu
    http://arxiv.org/abs/2103.00550v1

    • [cs.LG]A survey on Variational Autoencoders from a GreenAI perspective
    A. Asperti, D. Evangelista, E. Loli Piccolomini
    http://arxiv.org/abs/2103.01071v1

    • [cs.LG]Acceleration via Fractal Learning Rate Schedules
    Naman Agarwal, Surbhi Goel, Cyril Zhang
    http://arxiv.org/abs/2103.01338v1

    • [cs.LG]Adaptive Regularized Submodular Maximization
    Shaojie Tang, Jing Yuan
    http://arxiv.org/abs/2103.00384v1

    • [cs.LG]Adaptive Sampling for Minimax Fair Classification
    Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
    http://arxiv.org/abs/2103.00755v1

    • [cs.LG]AdeNet: Deep learning architecture that identifies damaged electrical insulators in power lines
    Ademola Okerinde, Lior Shamir, William Hsu, Tom Theis
    http://arxiv.org/abs/2103.01426v1

    • [cs.LG]Adversarial Examples for Unsupervised Machine Learning Models
    Chia-Yi Hsu, Pin-Yu Chen, Songtao Lu, Sijia Lu, Chia-Mu Yu
    http://arxiv.org/abs/2103.01895v1

    • [cs.LG]Adversarial Information Bottleneck
    Pemhlong Zhai, Shihua Zhang
    http://arxiv.org/abs/2103.00381v1

    • [cs.LG]Adversarial training in communication constrained federated learning
    Devansh Shah, Parijat Dube, Supriyo Chakraborty, Ashish Verma
    http://arxiv.org/abs/2103.01319v1

    • [cs.LG]Autobahn: Automorphism-based Graph Neural Nets
    Erik Henning Thiede, Wenda Zhou, Risi Kondor
    http://arxiv.org/abs/2103.01710v1

    • [cs.LG]Automated Machine Learning on Graphs: A Survey
    Ziwei Zhang, Xin Wang, Wenwu Zhu
    http://arxiv.org/abs/2103.00742v1

    • [cs.LG]Automated data-driven approach for gap filling in the time series using evolutionary learning
    Mikhail Sarafanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya
    http://arxiv.org/abs/2103.01124v1

    • [cs.LG]Botcha: Detecting Malicious Non-Human Traffic in the Wild
    Sunny Dhamnani, Ritwik Sinha, Vishwa Vinay, Lilly Kumari, Margarita Savova
    http://arxiv.org/abs/2103.01428v1

    • [cs.LG]Categorical Foundations of Gradient-Based Learning
    G. S. H. Cruttwell, Bruno Gavranović, Neil Ghani, Paul Wilson, Fabio Zanasi
    http://arxiv.org/abs/2103.01931v1

    • [cs.LG]Challenges and Opportunities in High-dimensional Variational Inference
    Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe, Michael Riis Andersen, Jonathan Huggins, Aki Vehtari
    http://arxiv.org/abs/2103.01085v1

    • [cs.LG]Characterization of Neural Networks Automatically Mapped on Automotive-grade Microcontrollers
    Giulia Crocioni, Giambattista Gruosso, Danilo Pau, Davide Denaro, Luigi Zambrano, Giuseppe di Giore
    http://arxiv.org/abs/2103.00201v1

    • [cs.LG]Class Means as an Early Exit Decision Mechanism
    Alperen Gormez, Erdem Koyuncu
    http://arxiv.org/abs/2103.01148v1

    • [cs.LG]Computationally Efficient Wasserstein Loss for Structured Labels
    Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada
    http://arxiv.org/abs/2103.00899v1

    • [cs.LG]Computing the Information Content of Trained Neural Networks
    Jeremy Bernstein, Yisong Yue
    http://arxiv.org/abs/2103.01045v1

    • [cs.LG]Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
    Yixing Zhang, Xiuyuan Cheng, Galen Reeves
    http://arxiv.org/abs/2103.00394v1

    • [cs.LG]Coordination Among Neural Modules Through a Shared Global Workspace
    Anirudh Goyal, Aniket Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Mozer, Yoshua Bengio
    http://arxiv.org/abs/2103.01197v1

    • [cs.LG]Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms
    Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
    http://arxiv.org/abs/2103.01096v1

    • [cs.LG]DM algorithms in healthindustry
    Li Wang
    http://arxiv.org/abs/2103.01888v1

    • [cs.LG]DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing
    Wenxiao Wang, Tianhao Wang, Lun Wang, Nanqing Luo, Pan Zhou, Dawn Song, Ruoxi Jia
    http://arxiv.org/abs/2103.01496v1

    • [cs.LG]DTW-Merge: A Novel Data Augmentation Technique for Time Series Classification
    Mohammad Akyash, Hoda Mohammadzade, Hamid Behroozi
    http://arxiv.org/abs/2103.01119v1

    • [cs.LG]Data-driven MIMO control of room temperature and bidirectional EV charging using deep reinforcement learning: simulation and experiments
    B. Svetozarevic, C. Baumann, S. Muntwiler, L. Di Natale, P. Heer, M. Zeilinger
    http://arxiv.org/abs/2103.01886v1

    • [cs.LG]Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality on Hölder Class
    Yuling Jiao, Yanming Lai, Xiliang Lu, Zhijian Yang
    http://arxiv.org/abs/2103.00542v1

    • [cs.LG]DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers
    Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark Barrett
    http://arxiv.org/abs/2103.01629v1

    • [cs.LG]DeepReDuce: ReLU Reduction for Fast Private Inference
    Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
    http://arxiv.org/abs/2103.01396v1

    • [cs.LG]Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization
    Tolga Ergen, Arda Sahiner, Batu Ozturkler, John Pauly, Morteza Mardani, Mert Pilanci
    http://arxiv.org/abs/2103.01499v1

    • [cs.LG]Distilling Knowledge via Intermediate Classifier Heads
    Aryan Asadian, Amirali Salehi-Abari
    http://arxiv.org/abs/2103.00497v1

    • [cs.LG]Domain Generalization via Inference-time Label-Preserving Target Projections
    Prashant Pandey, Mrigank Raman, Sumanth Varambally, Prathosh AP
    http://arxiv.org/abs/2103.01134v1

    • [cs.LG]Double Coverage with Machine-Learned Advice
    Alexander Lindermayr, Nicole Megow, Bertrand Simon
    http://arxiv.org/abs/2103.01640v1

    • [cs.LG]Ensemble Bootstrapping for Q-Learning
    Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir
    http://arxiv.org/abs/2103.00445v1

    • [cs.LG]Evaluating the Robustness of Geometry-Aware Instance-Reweighted Adversarial Training
    Dorjan Hitaj, Giulio Pagnotta, Iacopo Masi, Luigi V. Mancini
    http://arxiv.org/abs/2103.01914v1

    • [cs.LG]Extreme Volatility Prediction in Stock Market: When GameStop meets Long Short-Term Memory Networks
    Yigit Alparslan, Edward Kim
    http://arxiv.org/abs/2103.01121v1

    • [cs.LG]Factoring out prior knowledge from low-dimensional embeddings
    Edith Heiter, Jonas Fischer, Jilles Vreeken
    http://arxiv.org/abs/2103.01828v1

    • [cs.LG]Federated Learning without Revealing the Decision Boundaries
    Roozbeh Yousefzadeh
    http://arxiv.org/abs/2103.00695v1

    • [cs.LG]FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs
    Jan Portisch, Michael Hladik, Heiko Paulheim
    http://arxiv.org/abs/2103.01576v1

    • [cs.LG]Financial Crime & Fraud Detection Using Graph Computing: Application Considerations & Outlook
    E. Kurshan, H. Shen, H. Yu
    http://arxiv.org/abs/2103.01854v1

    • [cs.LG]ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations
    Weihua Hu, Muhammed Shuaibi, Abhishek Das, Siddharth Goyal, Anuroop Sriram, Jure Leskovec, Devi Parikh, C. Lawrence Zitnick
    http://arxiv.org/abs/2103.01436v1

    • [cs.LG]GEBT: Drawing Early-Bird Tickets in Graph Convolutional Network Training
    Haoran You, Zhihan Lu, Zijian Zhou, Yingyan Lin
    http://arxiv.org/abs/2103.00794v1

    • [cs.LG]Generative Particle Variational Inference via Estimation of Functional Gradients
    Neale Ratzlaff, Qinxun Bai, Li Fuxin, Wei Xu
    http://arxiv.org/abs/2103.01291v1

    • [cs.LG]Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks
    Haifeng Li, Jun Cao, Jiawei Zhu, Qing Zhu, Guohua Wu
    http://arxiv.org/abs/2103.01770v1

    • [cs.LG]Graph-Time Convolutional Neural Networks
    Elvin Isufi, Gabriele Mazzola
    http://arxiv.org/abs/2103.01730v1

    • [cs.LG]Heterogeneity for the Win: One-Shot Federated Clustering
    Don Kurian Dennis, Tian Li, Virginia Smith
    http://arxiv.org/abs/2103.00697v1

    • [cs.LG]Hierarchical Inducing Point Gaussian Process for Inter-domain Observations
    Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David Blei, John Cunningham
    http://arxiv.org/abs/2103.00393v1

    • [cs.LG]Is Simple Uniform Sampling Efficient for Center-Based Clustering With Outliers: When and Why?
    Hu Ding, Jiawei Huang
    http://arxiv.org/abs/2103.00558v1

    • [cs.LG]Kernel-Based Models for Influence Maximization on Graphs based on Gaussian Process Variance Minimization
    Salvatore Cuomo, Wolfgang Erb, Gabriele Santin
    http://arxiv.org/abs/2103.01575v1

    • [cs.LG]Label-Imbalanced and Group-Sensitive Classification under Overparameterization
    Ganesh Ramachandra Kini, Orestis Paraskevas, Samet Oymak, Christos Thrampoulidis
    http://arxiv.org/abs/2103.01550v1

    • [cs.LG]Learning disentangled representations via product manifold projection
    Marco Fumero, Luca Cosmo, Simone Melzi, Emanuele Rodolà
    http://arxiv.org/abs/2103.01638v1

    • [cs.LG]Learning with Hyperspherical Uniformity
    Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller
    http://arxiv.org/abs/2103.01649v1

    • [cs.LG]Listening to the city, attentively: A Spatio-Temporal Attention Boosted Autoencoder for the Short-Term Flow Prediction Problem
    Stefano Fiorini, Michele Ciavotta, Andrea Maurino
    http://arxiv.org/abs/2103.00983v1

    • [cs.LG]LocalDrop: A Hybrid Regularization for Deep Neural Networks
    Ziqing Lu, Chang Xu, Bo Du, Takashi Ishida, Lefei Zhang, Masashi Sugiyama
    http://arxiv.org/abs/2103.00719v1

    • [cs.LG]Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database
    Gareth Jones, Jim Parr, Perumal Nithiarasu, Sanjay Pant
    http://arxiv.org/abs/2103.00599v1

    • [cs.LG]Machine learning on small size samples: A synthetic knowledge synthesis
    Peter Kokol, Marko Kokol, Sašo Zagoranski
    http://arxiv.org/abs/2103.01002v1

    • [cs.LG]Manifold optimization for optimal transport
    Bamdev Mishra, N T V Satya Dev, Hiroyuki Kasai, Pratik Jawanpuria
    http://arxiv.org/abs/2103.00902v1

    • [cs.LG]Meta-Learning an Inference Algorithm for Probabilistic Programs
    Gwonsoo Che, Hongseok Yang
    http://arxiv.org/abs/2103.00737v1

    • [cs.LG]Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search
    Kartik Hegde, Po-An Tsai, Sitao Huang, Vikas Chandra, Angshuman Parashar, Christopher W. Fletcher
    http://arxiv.org/abs/2103.01489v1

    • [cs.LG]Mind the box: 今日学术视野(2021.3.4) - 图8-APGD for sparse adversarial attacks on image classifiers
    Francesco Croce, Matthias Hein
    http://arxiv.org/abs/2103.01208v1

    • [cs.LG]Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding
    Bruno Andreis, Jeffrey Willette, Juho Lee, Sung Ju Hwang
    http://arxiv.org/abs/2103.01615v1

    • [cs.LG]Missing Value Imputation on Multidimensional Time Series
    Parikshit Bansal, Prathamesh Deshpande, Sunita Sarawagi
    http://arxiv.org/abs/2103.01600v1

    • [cs.LG]Model-Agnostic Explainability for Visual Search
    Mark Hamilton, Scott Lundberg, Lei Zhang, Stephanie Fu, William T. Freeman
    http://arxiv.org/abs/2103.00370v1

    • [cs.LG]Moment-Based Variational Inference for Stochastic Differential Equations
    Christian Wildner, Heinz Koeppl
    http://arxiv.org/abs/2103.00988v1

    • [cs.LG]Multi-Level Attention Pooling for Graph Neural Networks: Unifying Graph Representations with Multiple Localities
    Takeshi D. Itoh, Takatomi Kubo, Kazushi Ikeda
    http://arxiv.org/abs/2103.01488v1

    • [cs.LG]Multi-label Classification via Adaptive Resonance Theory-based Clustering
    Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi
    http://arxiv.org/abs/2103.01511v1

    • [cs.LG]Non-Euclidean Differentially Private Stochastic Convex Optimization
    Raef Bassily, Cristóbal Guzmán, Anupama Nandi
    http://arxiv.org/abs/2103.01278v1

    • [cs.LG]Offline Reinforcement Learning with Pseudometric Learning
    Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist
    http://arxiv.org/abs/2103.01948v1

    • [cs.LG]On the Fairness of Generative Adversarial Networks (GANs)
    Patrik Joslin Kenfack, Daniil Dmitrievich Arapovy, Rasheed Hussain, S. M. Ahsan Kazmi, Adil Mehmood Khan
    http://arxiv.org/abs/2103.00950v1

    • [cs.LG]On the Memory Mechanism of Tensor-Power Recurrent Models
    Hejia Qiu, Chao Li, Ying Weng, Zhun Sun, Xingyu He, Qibin Zhao
    http://arxiv.org/abs/2103.01521v1

    • [cs.LG]Online Orthogonal Dictionary Learning Based on Frank-Wolfe Method
    Ye Xue, Vincent Lau
    http://arxiv.org/abs/2103.01484v1

    • [cs.LG]Online anomaly detection using statistical leverage for streaming business process events
    Jonghyeon Ko, Marco Comuzzi
    http://arxiv.org/abs/2103.00831v1

    • [cs.LG]Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories
    Wayne Isaac Tan Uy, Benjamin Peherstorfer
    http://arxiv.org/abs/2103.01362v1

    • [cs.LG]Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
    Zuowei Shen, Haizhao Yang, Shijun Zhang
    http://arxiv.org/abs/2103.00502v1

    • [cs.LG]Optimal Linear Combination of Classifiers
    Georgi Nalbantov, Svetoslav Ivanov
    http://arxiv.org/abs/2103.01109v1

    • [cs.LG]PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization
    Bingyan Liu, Yao Guo, Xiangqun Chen
    http://arxiv.org/abs/2103.01548v1

    • [cs.LG]PairRank: Online Pairwise Learning to Rank by Divide-and-Conquer
    Yiling Jia, Huazheng Wang, Stephen Guo, Hongning Wang
    http://arxiv.org/abs/2103.00368v1

    • [cs.LG]Performance Variability in Zero-Shot Classification
    Matías Molina, Jorge Sánchez
    http://arxiv.org/abs/2103.01284v1

    • [cs.LG]Persistent Message Passing
    Heiko Strathmann, Mohammadamin Barekatain, Charles Blundell, Petar Veličković
    http://arxiv.org/abs/2103.01043v1

    • [cs.LG]Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers
    M. Abid, A. Khabou, Y. Ouakrim, H. Watel, S. Chemkhi, A. Mitiche, A. Benazza-Benyahia, N. Mezghani
    http://arxiv.org/abs/2103.01859v1

    • [cs.LG]Posterior Meta-Replay for Continual Learning
    Christian Henning, Maria R. Cervera, Francesco D’Angelo, Johannes von Oswald, Regina Traber, Benjamin Ehret, Seijin Kobayashi, João Sacramento, Benjamin F. Grewe
    http://arxiv.org/abs/2103.01133v1

    • [cs.LG]Predictive Maintenance Tool for Non-Intrusive Inspection Systems
    Georgi Nalbantov, Dimitar Todorov, Nikolay Zografov, Stefan Georgiev, Nadia Bojilova
    http://arxiv.org/abs/2103.01044v1

    • [cs.LG]Private Stochastic Convex Optimization: Optimal Rates in 今日学术视野(2021.3.4) - 图9 Geometry
    Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
    http://arxiv.org/abs/2103.01516v1

    • [cs.LG]Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
    Eran Malach, Pritish Kamath, Emmanuel Abbe, Nathan Srebro
    http://arxiv.org/abs/2103.01210v1

    • [cs.LG]Reinforcement Learning for Adaptive Mesh Refinement
    Jiachen Yang, Tarik Dzanic, Brenden Petersen, Jun Kudo, Ketan Mittal, Vladimir Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio Kolev, Robert Anderson, Daniel Faissol
    http://arxiv.org/abs/2103.01342v1

    • [cs.LG]Robust learning under clean-label attack
    Avrim Blum, Steve Hanneke, Jian Qian, Han Shao
    http://arxiv.org/abs/2103.00671v1

    • [cs.LG]STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection
    Vitor Cerqueira, Heitor Murilo Gomes, Albert Bifet, Luis Torgo
    http://arxiv.org/abs/2103.00903v1

    • [cs.LG]SWIS — Shared Weight bIt Sparsity for Efficient Neural Network Acceleration
    Shurui Li, Wojciech Romaszkan, Alexander Graening, Puneet Gupta
    http://arxiv.org/abs/2103.01308v1

    • [cs.LG]Safe Learning of Uncertain Environments for Nonlinear Control-Affine Systems
    Farhad Farokhi, Alex Leong, Iman Shames, Mohammad Zamani
    http://arxiv.org/abs/2103.01413v1

    • [cs.LG]Sample Complexity and Overparameterization Bounds for Projection-Free Neural TD Learning
    Semih Cayci, Siddhartha Satpathi, Niao He, R. Srikant
    http://arxiv.org/abs/2103.01391v1

    • [cs.LG]Scalable federated machine learning with FEDn
    Morgan Ekmefjord, Addi Ait-Mlouk, Sadi Alawadi, Mattias Åkesson, Desislava Stoyanova, Ola Spjuth, Salman Toor, Andreas Hellander
    http://arxiv.org/abs/2103.00148v1

    • [cs.LG]Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating
    Qingsong Zhang, Bin Gu, Cheng Deng, Heng Huang
    http://arxiv.org/abs/2103.00958v1

    • [cs.LG]Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning
    Dasol Hwang, Jinyoung Park, Sunyoung Kwon, Kyung-Min Kim, Jung-Woo Ha, Hyunwoo j. Kim
    http://arxiv.org/abs/2103.00771v1

    • [cs.LG]Self-supervised Symmetric Nonnegative Matrix Factorization
    Yuheng Jia, Hui Liu, Junhui Hou, Sam Kwong, Qingfu Zhang
    http://arxiv.org/abs/2103.01689v1

    • [cs.LG]Smoothness Analysis of Loss Functions of Adversarial Training
    Sekitoshi Kanai, Masanori Yamada, Hiroshi Takahashi, Yuki Yamanaka, Yasutoshi Ida
    http://arxiv.org/abs/2103.01400v1

    • [cs.LG]Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing
    Charlie Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson
    http://arxiv.org/abs/2103.01009v1

    • [cs.LG]Statistically Significant Stopping of Neural Network Training
    Justin K. Terry, Mario Jayakumar, Kusal De Alwis
    http://arxiv.org/abs/2103.01205v1

    • [cs.LG]Strategic Classification Made Practical
    Sagi Levanon, Nir Rosenfeld
    http://arxiv.org/abs/2103.01826v1

    • [cs.LG]Task-Adaptive Neural Network Retrieval with Meta-Contrastive Learning
    Wonyong Jeong, Hayeon Lee, Gun Park, Eunyoung Hyung, Jinheon Baek, Sung Ju Hwang
    http://arxiv.org/abs/2103.01495v1

    • [cs.LG]The Age of Correlated Features in Supervised Learning based Forecasting
    MD Kamran Chowdhury Shisher, Heyang Qin, Lei Yang, Feng Yan, Yin Sun
    http://arxiv.org/abs/2103.00092v1

    • [cs.LG]The KL-Divergence between a Graph Model and its Fair I-Projection as a Fairness Regularizer
    Maarten Buyl, Tijl De Bie
    http://arxiv.org/abs/2103.01846v1

    • [cs.LG]The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games
    Chao Yu, Akash Velu, Eugene Vinitsky, Yu Wang, Alexandre Bayen, Yi Wu
    http://arxiv.org/abs/2103.01955v1

    • [cs.LG]Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search
    Guoyang Xie, Jinbao Wang, Guo Yu, Feng Zheng, Yaochu Jin
    http://arxiv.org/abs/2103.00363v1

    • [cs.LG]Topic Modelling Meets Deep Neural Networks: A Survey
    He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray Buntine
    http://arxiv.org/abs/2103.00498v1

    • [cs.LG]Towards Efficient Local Causal Structure Learning
    Shuai Yang, Hao Wang, Kui Yu, Fuyuan Cao, Xindong Wu
    http://arxiv.org/abs/2103.00378v1

    • [cs.LG]Towards Personalized Federated Learning
    Alysa Ziying Tan, Han Yu, Lizhen Cui, Qiang Yang
    http://arxiv.org/abs/2103.00710v1

    • [cs.LG]Transformers with Competitive Ensembles of Independent Mechanisms
    Alex Lamb, Di He, Anirudh Goyal, Guolin Ke, Chien-Feng Liao, Mirco Ravanelli, Yoshua Bengio
    http://arxiv.org/abs/2103.00336v1

    • [cs.LG]Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly
    Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang
    http://arxiv.org/abs/2103.00397v1

    • [cs.LG]Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements
    Lara Hoffmann, Ines Fortmeier, Clemens Elster
    http://arxiv.org/abs/2103.01259v1

    • [cs.LG]Unsupervised Domain Adaptation for Cross-Subject Few-Shot Neurological Symptom Detection
    Bingzhao Zhu, Mahsa Shoaran
    http://arxiv.org/abs/2103.00606v1

    • [cs.LG]Wide Network Learning with Differential Privacy
    Huanyu Zhang, Ilya Mironov, Meisam Hejazinia
    http://arxiv.org/abs/2103.01294v1

    • [cs.LG]ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation
    Zhize Li, Peter Richtárik
    http://arxiv.org/abs/2103.01447v1

    • [cs.NE]Convergence Rate of the (1+1)-Evolution Strategy with Success-Based Step-Size Adaptation on Convex Quadratic Functions
    Daiki Morinaga, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto
    http://arxiv.org/abs/2103.01578v1

    • [cs.NE]Deep Learning with a Classifier System: Initial Results
    Richard J. Preen, Larry Bull
    http://arxiv.org/abs/2103.01118v1

    • [cs.NE]Enhancing hierarchical surrogate-assisted evolutionary algorithm for high-dimensional expensive optimization via random projection
    Xiaodong Ren, Daofu Guo, Zhigang Ren, Yongsheng Liang, An Chen
    http://arxiv.org/abs/2103.00682v1

    • [cs.NE]Incorporating Domain Knowledge into Deep Neural Networks
    Tirtharaj Dash, Sharad Chitlangia, Aditya Ahuja, Ashwin Srinivasan
    http://arxiv.org/abs/2103.00180v1

    • [cs.NE]Individual risk profiling for portable devices using a neural network to process the recording of 30 successive pairs of cognitive reaction and emotional response to a multivariate situational risk assessment
    Frederic Jumelle, Kelvin So, Didan Deng
    http://arxiv.org/abs/2103.00441v1

    • [cs.NE]Multi-Objective Evolutionary Design of CompositeData-Driven Models
    Iana S. Polonskaia, Nikolay O. Nikitin, Ilia Revin, Pavel Vychuzhanin, Anna V. Kalyuzhnaya
    http://arxiv.org/abs/2103.01301v1

    • [cs.NE]Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
    Shikuang Deng, Shi Gu
    http://arxiv.org/abs/2103.00476v1

    • [cs.NE]Semantic Neighborhood Ordering in Multi-objective Genetic Programming based on Decomposition
    Fergal Stapleton, Edgar Galván
    http://arxiv.org/abs/2103.00480v1

    • [cs.NE]SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic Environments
    Rachmad Vidya Wicaksana Putra, Muhammad Shafique
    http://arxiv.org/abs/2103.00424v1

    • [cs.PL]Roosterize: Suggesting Lemma Names for Coq Verification Projects Using Deep Learning
    Pengyu Nie, Karl Palmskog, Junyi Jessy Li, Milos Gligoric
    http://arxiv.org/abs/2103.01346v1

    • [cs.RO]A Bioinspired Approach-Sensitive Neural Network for Collision Detection in Cluttered and Dynamic Backgrounds
    Xiao Huang, Hong Qiao, Hui Li, Zhihong Jiang
    http://arxiv.org/abs/2103.00857v1

    • [cs.RO]A CPG-Based Agile and Versatile Locomotion Framework Using Proximal Symmetry Loss
    Mohammadreza Kasaei, Miguel Abreu, Nuno Lau, Artur Pereira, Luis Paulo Reis
    http://arxiv.org/abs/2103.00928v1

    • [cs.RO]A Holistic Motion Planning and Control Solution to Challenge a Professional Racecar Driver
    Sirish Srinivasan, Sebastian Nicolas Giles, Alexander Liniger
    http://arxiv.org/abs/2103.00358v1

    • [cs.RO]A Kinematic Bottleneck Approach For Pose Regression of Flexible Surgical Instruments directly from Images
    Luca Sestini, Benoit Rosa, Elena De Momi, Giancarlo Ferrigno, Nicolas Padoy
    http://arxiv.org/abs/2103.00586v1

    • [cs.RO]A Safety-Aware Kinodynamic Architecture for Human-Robot Collaboration
    Andrea Pupa, Mohammad Arrfou, Gildo Andreoni, Cristian Secchi
    http://arxiv.org/abs/2103.01818v1

    • [cs.RO]A Unified MPC Framework for Whole-Body Dynamic Locomotion and Manipulation
    Jean-Pierre Sleiman, Farbod Farshidian, Maria Vittoria Minniti, Marco Hutter
    http://arxiv.org/abs/2103.00946v1

    • [cs.RO]Autonomous Navigation of an Ultrasound Probe Towards Standard Scan Planes with Deep Reinforcement Learning
    Keyu Li, Jian Wang, Yangxin Xu, Hao Qin, Dongsheng Liu, Li Liu, Max Q. -H. Meng
    http://arxiv.org/abs/2103.00718v1

    • [cs.RO]Avoiding Degeneracy for Monocular Visual SLAM with Point and Line Features
    Hyunjun Lim, Yeeun Kim, Kwangik Jung, Sumin Hu, Hyun Myung
    http://arxiv.org/abs/2103.01501v1

    • [cs.RO]Avoiding dynamic small obstacles with onboard sensing and computating on aerial robots
    Fanze Kong, Wei Xu, Fu Zhang
    http://arxiv.org/abs/2103.00406v1

    • [cs.RO]BPActuators: Lightweight and Low-Cost Soft Actuators by Balloons and Plastics
    Qiukai Qi, Shogo Yoshida, Genki Kakihana, Takuma Torii, Van Anh Ho, Haoran Xie
    http://arxiv.org/abs/2103.01409v1

    • [cs.RO]Careful with That! Observation of Human Movements to Estimate Objects Properties
    Linda Lastrico, Alessandro Carfì, Alessia Vignolo, Alessandra Sciutti, Fulvio Mastrogiovanni, Francesco Rea
    http://arxiv.org/abs/2103.01555v1

    • [cs.RO]Collaborative Recognition of Feasible region with Aerial and Ground Robots through DPCN
    Yunshuang Li, Zheyuan Huang, Zexi chen, Yue Wang, Rong Xiong
    http://arxiv.org/abs/2103.00947v1

    • [cs.RO]Contact-Implicit Trajectory Optimization for Dynamic Object Manipulation
    Jean-Pierre Sleiman, Jan Carius, Ruben Grandia, Martin Wermelinger, Marco Hutter
    http://arxiv.org/abs/2103.01104v1

    • [cs.RO]Continuous control of an underground loader using deep reinforcement learning
    Sofi Backman, Daniel Lindmark, Kenneth Bodin, Martin Servin, Joakim Mörk, Håkan Löfgren
    http://arxiv.org/abs/2103.01283v1

    • [cs.RO]CrossMap Transformer: A Crossmodal Masked Path Transformer Using Double Back-Translation for Vision-and-Language Navigation
    Aly Magassouba, Komei Sugiura, Hisashi Kawai
    http://arxiv.org/abs/2103.00852v1

    • [cs.RO]Diverse Critical Interaction Generation for Planning and Planner Evaluation
    Zhao-Heng Yin, Lingfeng Sun, Liting Sun, Masayoshi Tomizuka, Wei Zhan
    http://arxiv.org/abs/2103.00906v1

    • [cs.RO]Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game
    Nigora Gafur, Gajanan Kanagalingam, Martin Ruskowski
    http://arxiv.org/abs/2103.00583v1

    • [cs.RO]EKMP: Generalized Imitation Learning with Adaptation, Nonlinear Hard Constraints and Obstacle Avoidance
    Yanlong Huang
    http://arxiv.org/abs/2103.00452v1

    • [cs.RO]Enhancement for Robustness of Koopman Operator-based Data-driven Mobile Robotic Systems
    Lu Shi, Konstantinos Karydis
    http://arxiv.org/abs/2103.00812v1

    • [cs.RO]Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization
    Jinyun Zhou, Rui Wang, Xu Liu, Yifei Jiang, Shu Jiang, Jiaming Tao, Jinghao Miao, Shiyu Song
    http://arxiv.org/abs/2103.01882v1

    • [cs.RO]Generalization Through Hand-Eye Coordination: An Action Space for Learning Spatially-Invariant Visuomotor Control
    Chen Wang, Rui Wang, Danfei Xu, Ajay Mandlekar, Li Fei-Fei, Silvio Savarese
    http://arxiv.org/abs/2103.00375v1

    • [cs.RO]Geometry-Based Grasping of Vine Tomatoes
    Taeke de Haan, Padmaja Kulkarni, Robert Babuska
    http://arxiv.org/abs/2103.01272v1

    • [cs.RO]Human-Centered Dynamic Scheduling Architecture for Collaborative Application
    Andrea Pupa, Wietse Van Dijk, Cristian Secchi
    http://arxiv.org/abs/2103.01831v1

    • [cs.RO]LTO: Lazy Trajectory Optimization with Graph-Search Planning for High DOF Robots in Cluttered Environments
    Yuki Shirai, Xuan Lin, Ankur Mehta, Dennis Hong
    http://arxiv.org/abs/2103.01333v1

    • [cs.RO]Learning Human-like Hand Reaching for Human-Robot Handshaking
    Vignesh Prasad, Ruth Stock-Homburg, Jan Peters
    http://arxiv.org/abs/2103.00616v1

    • [cs.RO]Learning Multimodal Contact-Rich Skills from Demonstrations Without Reward Engineering
    Mythra V. Balakuntala, Upinder Kaur, Xin Ma, Juan Wachs, Richard M. Voyles
    http://arxiv.org/abs/2103.01296v1

    • [cs.RO]Learning Robotic Manipulation Tasks through Visual Planning
    Sulabh Kumra, Shirin Josh, Ferat Sahin
    http://arxiv.org/abs/2103.01434v1

    • [cs.RO]Learning Symbolic Operators for Task and Motion Planning
    Tom Silver, Rohan Chitnis, Joshua Tenenbaum, Leslie Pack Kaelbling, Tomas Lozano-Perez
    http://arxiv.org/abs/2103.00589v1

    • [cs.RO]Learning-based Bias Correction for Time Difference of Arrival Ultra-wideband Localization of Resource-constrained Mobile Robots
    Wenda Zhao, Jacopo Panerati, Angela P. Schoellig
    http://arxiv.org/abs/2103.01885v1

    • [cs.RO]LiTAMIN2: Ultra Light LiDAR-based SLAM using Geometric Approximation applied with KL-Divergence
    Masashi Yokozuka, Kenji Koide, Shuji Oishi, Atsuhiko Banno
    http://arxiv.org/abs/2103.00784v1

    • [cs.RO]Meta-Learning-Based Robust Adaptive Flight Control Under Uncertain Wind Conditions
    Michael O’Connell, Guanya Shi, Xichen Shi, Soon-Jo Chung
    http://arxiv.org/abs/2103.01932v1

    • [cs.RO]Model-based Safe Reinforcement Learning using Generalized Control Barrier Function
    Haitong Ma, Jianyu Chen, Shengbo Eben Li, Ziyu Lin, Sifa Zheng
    http://arxiv.org/abs/2103.01556v1

    • [cs.RO]Multi-robot task allocation for safe planning under dynamic uncertainties
    Daniel Tihanyi, Yimeng Lu, Orcun Karaca, Maryam Kamgarpour
    http://arxiv.org/abs/2103.01840v1

    • [cs.RO]NavTuner: Learning a Scene-Sensitive Family of Navigation Policies
    Haoxin Ma, Justin S. Smith, Patricio A. Vela
    http://arxiv.org/abs/2103.01464v1

    • [cs.RO]Path Planning for Manipulation using Experience-driven Random Trees
    Èric Pairet, Constantinos Chamzas, Yvan Petillot, Lydia E. Kavraki
    http://arxiv.org/abs/2103.00448v1

    • [cs.RO]Path continuity for multi-wheeled AGVs
    Mirko Kokot, Damjan Miklić, Tamara Petrović
    http://arxiv.org/abs/2103.01619v1

    • [cs.RO]Pixel-level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments
    Chongjian Yuan, Xiyuan Liu, Xiaoping Hong, Fu Zhang
    http://arxiv.org/abs/2103.01627v1

    • [cs.RO]Prognostics-Informed Battery Reconfiguration in a Multi-Battery Small UAS Energy System
    Prashin Sharma, Ella Atkins
    http://arxiv.org/abs/2103.01883v1

    • [cs.RO]Reachability-based Identification, Analysis, and Control Synthesis of Robot Systems
    Stefan B. Liu, Bastian Schürmann, Matthias Althoff
    http://arxiv.org/abs/2103.01626v1

    • [cs.RO]Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle
    Jinwoo Jeon, Sungwook Jung, Eungchang Lee, Duckyu Choi, Hyun Myung
    http://arxiv.org/abs/2103.01655v1

    • [cs.RO]Sim-to-Real Transfer for Robotic Manipulation with Tactile Sensory
    Zihan Ding, Ya-Yen Tsai, Wang Wei Lee, Bidan Huang
    http://arxiv.org/abs/2103.00410v1

    • [cs.RO]Simultaneous Tactile Exploration and Grasp Refinement for Unknown Objects
    Cristiana de Farias, Naresh Marturi, Rustam Stolkin, Yasemin Bekiroglu
    http://arxiv.org/abs/2103.00655v1

    • [cs.RO]Spatial Attention Point Network for Deep-learning-based Robust Autonomous Robot Motion Generation
    Hideyuki Ichiwara, Hiroshi Ito, Kenjiro Yamamoto, Hiroki Mori, Tetsuya Ogata
    http://arxiv.org/abs/2103.01598v1

    • [cs.RO]TouchRoller: A Rolling Optical Tactile Sensor for Rapid Assessment of Large Surfaces
    Guanqun Cao, Jiaqi Jiang, Chen Lu, Daniel Fernandes Gomes, Shan Luo
    http://arxiv.org/abs/2103.00595v1

    • [cs.RO]Virtual Adversarial Humans finding Hazards in Robot Workplaces
    Tom P. Huck, Christoph Ledermann, Torsten Kröger
    http://arxiv.org/abs/2103.00973v1

    • [cs.SD]Audio scene monitoring using redundant un-localized microphone arrays
    Peter Gerstoft, Yihan Hu, Chaitanya Patil, Ardel Alegre, Michael J. Bianco, Yoav Freund, Francois Grondin
    http://arxiv.org/abs/2103.01830v1

    • [cs.SD]Audio-Visual Speech Separation Using Cross-Modal Correspondence Loss
    Naoki Makishima, Mana Ihori, Akihiko Takashima, Tomohiro Tanaka, Shota Orihashi, Ryo Masumura
    http://arxiv.org/abs/2103.01463v1

    • [cs.SD]Brain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition
    Gautam Krishna, Mason Carnahan, Shilpa Shamapant, Yashitha Surendranath, Saumya Jain, Arundhati Ghosh, Co Tran, Jose del R Millan, Ahmed H Tewfik
    http://arxiv.org/abs/2103.00383v1

    • [cs.SD]Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event Localization
    Christopher Schymura, Tsubasa Ochiai, Marc Delcroix, Keisuke Kinoshita, Tomohiro Nakatani, Shoko Araki, Dorothea Kolossa
    http://arxiv.org/abs/2103.00417v1

    • [cs.SD]Investigations on Audiovisual Emotion Recognition in Noisy Conditions
    Michael Neumann, Ngoc Thang Vu
    http://arxiv.org/abs/2103.01894v1

    • [cs.SD]Listen, Read, and Identify: Multimodal Singing Language Identification
    Keunwoo Choi, Yuxuan Wang
    http://arxiv.org/abs/2103.01893v1

    • [cs.SD]SoundCLR: Contrastive Learning of Representations For Improved Environmental Sound Classification
    Alireza Nasiri, Jianjun Hu
    http://arxiv.org/abs/2103.01929v1

    • [cs.SD]Unsupervised Classification of Voiced Speech and Pitch Tracking Using Forward-Backward Kalman Filtering
    Benedikt Boenninghoff, Robert M. Nickel, Steffen Zeiler, Dorothea Kolossa
    http://arxiv.org/abs/2103.01173v1

    • [cs.SD]Virufy: A Multi-Branch Deep Learning Network for Automated Detection of COVID-19
    Ahmed Fakhry, Xinyi Jiang, Jaclyn Xiao, Gunvant Chaudhari, Asriel Han, Amil Khanzada
    http://arxiv.org/abs/2103.01806v1

    • [cs.SE]A Brief Survey of Current Software Engineering Practices in Continuous Integration and Automated Accessibility Testing
    Parth Sane
    http://arxiv.org/abs/2103.00097v1

    • [cs.SE]An Exploratory Study of Log Placement Recommendation in an Enterprise System
    Jeanderson Cândido, Jan Haesen, Maurício Aniche, Arie van Deursen
    http://arxiv.org/abs/2103.01755v1

    • [cs.SE]Automatic Generation of Challenging Road Networks for ALKS Testing based on Bezier Curves and Search
    Florian Klück, Lorenz Klampfl, Franz Wotawa
    http://arxiv.org/abs/2103.01288v1

    • [cs.SE]Follow Your Nose — Which Code Smells are Worth Chasing?
    Idan Amit, Nili Ben Ezra, Dror G. Feitelson
    http://arxiv.org/abs/2103.01861v1

    • [cs.SE]Investigating the potential impact of values on requirements and software engineering
    Alistair Sutcliffe, Pete Sawyer, Wei Liu, Nelly Bencomo
    http://arxiv.org/abs/2103.01309v1

    • [cs.SE]Offshore Software Maintenance Outsourcing Predicting Clients Proposal using Supervised Learning
    Atif Ikram, Masita Abdul Jalil, Amir Bin Ngah, Ahmad Salman Khan, Tahir Iqbal
    http://arxiv.org/abs/2103.01223v1

    • [cs.SE]On Introducing Automatic Test Case Generation in Practice: A Success Story and Lessons Learned
    Matteo Brunetto, Giovanni Denaro, Leonardo Mariani, Mauro Pezzè
    http://arxiv.org/abs/2103.00465v1

    • [cs.SE]Test Automation with Grad-CAM Heatmaps — A Future Pipe Segment in MLOps for Vision AI?
    Markus Borg, Ronald Jabangwe, Simon Åberg, Arvid Ekblom, Ludwig Hedlund, August Lidfeldt
    http://arxiv.org/abs/2103.01837v1

    • [cs.SE]The High-Assurance ROS Framework
    André Santos, Alcino Cunha, Nuno Macedo
    http://arxiv.org/abs/2103.01603v1

    • [cs.SE]Underproduction: An Approach for Measuring Risk in Open Source Software
    Kaylea Champion, Benjamin Mako Hill
    http://arxiv.org/abs/2103.00352v1

    • [cs.SI]A multi-objective time series analysis of community mobility reduction comparing first and second COVID-19 waves
    Gabriela Cavalcante da Silva, Fernanda Monteiro de Almeida, Sabrina Oliveira, Leonardo C. T. Bezerra, Elizabeth F. Wanner, Ricardo H. C. Takahashi
    http://arxiv.org/abs/2103.00535v1

    • [cs.SI]A simple method for improving the accuracy of Chung-Lu random graph generation
    Christopher Brissette, George Slota
    http://arxiv.org/abs/2103.00662v1

    • [cs.SI]Automated Generation of Interorganizational Disaster Response Networks through Information Extraction
    Yitong Li, Duoduo Liao, Jundong Li, Wenying Ji
    http://arxiv.org/abs/2103.00287v1

    • [cs.SI]COVID-19: Detecting Depression Signals during Stay-At-Home Period
    Jean Marie Tshimula, Belkacem Chikhaoui, Shengrui Wang
    http://arxiv.org/abs/2103.00597v1

    • [cs.SI]CogDL: An Extensive Toolkit for Deep Learning on Graphs
    Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang
    http://arxiv.org/abs/2103.00959v1

    • [cs.SI]Condition Sensing for Electricity Infrastructure in Disasters by Mining Public Topics from Social Media
    Yudi Chen, Angel Umana, Chaowei Yang, Wenying JI
    http://arxiv.org/abs/2103.00708v1

    • [cs.SI]Criminal Networks Analysis in Missing Data scenarios through Graph Distances
    Annamaria Ficara, Lucia Cavallaro, Francesco Curreri, Giacomo Fiumara, Pasquale De Meo, Ovidiu Bagdasar, Wei Song, Antonio Liotta
    http://arxiv.org/abs/2103.00457v1

    • [cs.SI]Discovering Dense Correlated Subgraphs in Dynamic Networks
    Giulia Preti, Polina Rozenshtein, Aristides Gionis, Yannis Velegrakis
    http://arxiv.org/abs/2103.00451v1

    • [cs.SI]Exploring the social influence of Kaggle virtual community on the M5 competition
    Xixi Li, Yun Bai, Yanfei Kang
    http://arxiv.org/abs/2103.00501v1

    • [cs.SI]Gender Typicality of Behavior Predicts Success on Creative Platforms
    Orsolya Vasarhelyi, Balazs Vedres
    http://arxiv.org/abs/2103.01093v2

    • [cs.SI]How Fair is Fairness-aware Representative Ranking and Methods for Fair Ranking
    Akrati Saxena, George Fletcher, Mykola Pechenizkiy
    http://arxiv.org/abs/2103.01335v1

    • [cs.SI]ISHNE: Influence Self-attention for Heterogeneous Network Embedding
    Yang Yan, Qiuyan Wang
    http://arxiv.org/abs/2103.00118v1

    • [cs.SI]Interplay Between Hierarchy and Centrality in Complex Networks
    Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi
    http://arxiv.org/abs/2103.01376v1

    • [cs.SI]Nonparametric estimation of the preferential attachment function from one network snapshot
    Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
    http://arxiv.org/abs/2103.01750v1

    • [cs.SI]Preferential attachment hypergraph with high modularity
    Frédéric Giroire, Nicolas Nisse, Thibaud Trolliet, Małgorzata Sulkowska
    http://arxiv.org/abs/2103.01751v1

    • [cs.SI]TweetCOVID: A System for Analyzing Public Sentiments and Discussions about COVID-19 via Twitter Activities
    Jolin Shaynn-Ly Kwan, Kwan Hui Lim
    http://arxiv.org/abs/2103.01472v1

    • [cs.SI]Understanding & Predicting User Lifetime with Machine Learning in an Anonymous Location-Based Social Network
    Jens Helge Reelfs, Max Bergmann, Oliver Hohlfeld, Niklas Henckell
    http://arxiv.org/abs/2103.01300v1

    • [econ.EM]Can Machine Learning Catch the COVID-19 Recession?
    Philippe Goulet Coulombe, Massimiliano Marcellino, Dalibor Stevanovic
    http://arxiv.org/abs/2103.01201v1

    • [econ.EM]Dynamic covariate balancing: estimating treatment effects over time
    Davide Viviano, Jelena Bradic
    http://arxiv.org/abs/2103.01280v1

    • [econ.EM]Network Cluster-Robust Inference
    Michael P. Leung
    http://arxiv.org/abs/2103.01470v1

    • [econ.GN]Computing Prices for Target Profits in Contracts
    Ghurumuruhan Ganesan
    http://arxiv.org/abs/2103.00766v1

    • [eess.AS]AdaSpeech: Adaptive Text to Speech for Custom Voice
    Mingjian Chen, Xu Tan, Bohan Li, Yanqing Liu, Tao Qin, Sheng Zhao, Tie-Yan Liu
    http://arxiv.org/abs/2103.00993v1

    • [eess.AS]Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition
    Hirofumi Inaguma, Tatsuya Kawahara
    http://arxiv.org/abs/2103.00422v1

    • [eess.AS]Contrastive Separative Coding for Self-supervised Representation Learning
    Jun Wang, Max W. Y. Lam, Dan Su, Dong Yu
    http://arxiv.org/abs/2103.00816v1

    • [eess.AS]Exploiting ultrasound tongue imaging for the automatic detection of speech articulation errors
    Manuel Sam Ribeiro, Joanne Cleland, Aciel Eshky, Korin Richmond, Steve Renals
    http://arxiv.org/abs/2103.00324v1

    • [eess.AS]Long-Running Speech Recognizer:An End-to-End Multi-Task Learning Framework for Online ASR and VAD
    Meng Li, Shiyu Zhou, Bo Xu
    http://arxiv.org/abs/2103.01661v1

    • [eess.AS]Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation
    Max W. Y. Lam, Jun Wang, Dan Su, Dong Yu
    http://arxiv.org/abs/2103.00819v1

    • [eess.AS]Silent versus modal multi-speaker speech recognition from ultrasound and video
    Manuel Sam Ribeiro, Aciel Eshky, Korin Richmond, Steve Renals
    http://arxiv.org/abs/2103.00333v1

    • [eess.AS]Tune-In: Training Under Negative Environments with Interference for Attention Networks Simulating Cocktail Party Effect
    Jun Wang, Max W. Y. Lam, Dan Su, Dong Yu
    http://arxiv.org/abs/2103.01461v1

    • [eess.IV]A Practical Framework for ROI Detection in Medical Images — a case study for hip detection in anteroposterior pelvic radiographs
    Feng-Yu Liu, Chih-Chi Chen, Shann-Ching Chen, Chien-Hung Liao
    http://arxiv.org/abs/2103.01584v1

    • [eess.IV]Assessing deep learning methods for the identification of kidney stones in endoscopic images
    Francisco Lopez, Andres Varela, Oscar Hinojosa, Mauricio Mendez, Dinh-Hoan Trinh, Jonathan ElBeze, Jacques Hubert, Vincent Estrade, Miguel Gonzalez, Gilberto Ochoa, Christian Daul
    http://arxiv.org/abs/2103.01146v1

    • [eess.IV]Efficient Deep Image Denoising via Class Specific Convolution
    Lu Xu, Jiawei Zhang, Xuanye Cheng, Feng Zhang, Xing Wei, Jimmy Ren
    http://arxiv.org/abs/2103.01624v1

    • [eess.IV]Feature-Align Network and Knowledge Distillation for Efficient Denoising
    Lucas D. Young, Fitsum A. Reda, Rakesh Ranjan, Jon Morton, Jun Hu, Yazhu Ling, Xiaoyu Xiang, David Liu, Vikas Chandra
    http://arxiv.org/abs/2103.01524v1

    • [eess.IV]LADMM-Net: An Unrolled Deep Network For Spectral Image Fusion From Compressive Data
    Juan Marcos Ramírez, José Ignacio Martínez Torre, Henry Arguello Fuentes
    http://arxiv.org/abs/2103.00940v1

    • [eess.IV]Medical Imaging and Machine Learning
    Rohan Shad, John P. Cunningham, Euan A. Ashley, Curtis P. Langlotz, William Hiesinger
    http://arxiv.org/abs/2103.01938v1

    • [eess.IV]MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing
    Zhengjue Wang, Hao Zhang, Ziheng Cheng, Bo Chen, Xin Yuan
    http://arxiv.org/abs/2103.01786v1

    • [eess.IV]Robust 3D U-Net Segmentation of Macular Holes
    Jonathan Frawley, Chris G. Willcocks, Maged Habib, Caspar Geenen, David H. Steel, Boguslaw Obara
    http://arxiv.org/abs/2103.01299v1

    • [eess.IV]Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution Enhancement
    Hongming Luo, Fei Zhou, Guangsen Liao, Guoping Qiu
    http://arxiv.org/abs/2103.01698v1

    • [eess.IV]Towards Unbiased COVID-19 Lesion Localisation and Segmentation via Weakly Supervised Learning
    Yang Yang, Jiancong Chen, Ruixuan Wang, Ting Ma, Lingwei Wang, Jie Chen, Wei-Shi Zheng, Tong Zhang
    http://arxiv.org/abs/2103.00780v1

    • [eess.SP]Deep Learning-based Compressive Beam Alignment in mmWave Vehicular Systems
    Yuyang Wang, Nitin Jonathan Myers, Nuria González-Prelcic, Robert W. Heath Jr
    http://arxiv.org/abs/2103.00125v1

    • [eess.SP]Deep Reinforcement Learning for URLLC data management on top of scheduled eMBB traffic
    Fabio Saggese, Luca Pasqualini, Marco Moretti, Andrea Abrardo
    http://arxiv.org/abs/2103.01801v1

    • [eess.SP]Deep Unfolded Recovery of Sub-Nyquist Sampled Ultrasound Image
    Alon Mamistvalov, Yonina C. Eldar
    http://arxiv.org/abs/2103.01263v1

    • [eess.SP]ECGT2T: Electrocardiogram synthesis from Two asynchronous leads to Ten leads
    Yong-Yeon Jo, Joon-Myoung Kwon
    http://arxiv.org/abs/2103.00006v1

    • [eess.SP]Path-specific Underwater Acoustic Channel Tracking and its Application in Passive Time Reversal Mirror
    Xiuqing Li, Wei Li, Xinlin Yi, Qihang Huang, Yuhang Wang, Chenzhe Ye
    http://arxiv.org/abs/2103.00874v1

    • [eess.SP]SmartON: Just-in-Time Active Event Detection on Energy Harvesting Systems
    Yubo Luo, Shahriar Nirjon
    http://arxiv.org/abs/2103.00749v1

    • [eess.SP]Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamforming
    Ahmet M. Elbir, Kumar Vijay Mishra, Symeon Chatzinotas
    http://arxiv.org/abs/2103.00328v1

    • [eess.SY]Constructing Dampened LTI Systems Generating Polynomial Bases
    Andreas Stöckel
    http://arxiv.org/abs/2103.00051v1

    • [eess.SY]Set-Membership Estimation in Shared Situational Awareness for Automated Vehicles in Occluded Scenarios
    Vandana Narri, Amr Alanwar, Jonas Mårtensson, Christoffer Norén, Laura Dal Col, Karl Henrik Johansson
    http://arxiv.org/abs/2103.01791v1

    • [hep-ph]Deep Learning strategies for ProtoDUNE raw data denoising
    Marco Rossi, Sofia Vallecorsa
    http://arxiv.org/abs/2103.01596v1

    • [math-ph]Local Tail Statistics of Heavy-Tailed Random Matrix Ensembles with Unitary Invariance
    Mario Kieburg, Adam Monteleone
    http://arxiv.org/abs/2103.00817v1

    • [math.CO]Linear Recurrences over a Finite Field with Exactly Two Periods
    Ghurumuruhan Ganesan
    http://arxiv.org/abs/2103.00827v1

    • [math.CT]Learners’ languages
    David I. Spivak
    http://arxiv.org/abs/2103.01189v1

    • [math.DS]Analysis, Prediction, and Control of Epidemics: A Survey from Scalar to Dynamic Network Models
    Lorenzo Zino, Ming Cao
    http://arxiv.org/abs/2103.00181v1

    • [math.NA]Error Estimates for the Variational Training of Neural Networks with Boundary Penalty
    Johannes Müller, Marius Zeinhofer
    http://arxiv.org/abs/2103.01007v1

    • [math.NA]Estimating and increasing the structural robustness of a network
    Silvia Noschese, Lothar Reichel
    http://arxiv.org/abs/2103.00247v1

    • [math.PR]Asymptotic Stochastic Comparison of Random Processes
    Sugata Ghosh, Asok K. Nanda
    http://arxiv.org/abs/2103.01720v1

    • [math.PR]Bernoulli sums and Rényi entropy inequalities
    Mokshay Madiman, James Melbourne, Cyril Roberto
    http://arxiv.org/abs/2103.00896v1

    • [math.PR]Departure-based Asymptotic Stochastic Order for Random Processes
    Sugata Ghosh, Asok K. Nanda
    http://arxiv.org/abs/2103.01727v1

    • [math.ST]Algorithmic Obstructions in the Random Number Partitioning Problem
    David Gamarnik, Eren C. Kızıldağ
    http://arxiv.org/abs/2103.01369v1

    • [math.ST]Bayesian Point Estimation and Predictive Density Estimation for the Binomial Distribution with a Restricted Probability Parameter
    Yasuyuki Hamura
    http://arxiv.org/abs/2103.00518v1

    • [math.ST]Comparisons of Order Statistics from Some Heterogeneous Discrete Distributions
    Shovan Chowdhury, Amarjit Kundu, Surja Kanta Mishra
    http://arxiv.org/abs/2103.00763v1

    • [math.ST]Finite Sample Smeariness on Spheres
    Benjamin Eltzner, Shayan Hundrieser, Stephan F. Huckemann
    http://arxiv.org/abs/2103.00512v1

    • [math.ST]General dependence structures for some models based on exponential families with quadratic variance functions
    Luis Nieto-Barajas, Eduardo Gutiérrez-Peña
    http://arxiv.org/abs/2103.01218v1

    • [math.ST]Information-geometry of physics-informed statistical manifolds and its use in data assimilation
    Francesca Boso, Daniel M. Tartakovsky
    http://arxiv.org/abs/2103.01160v1

    • [math.ST]Posterior consistency for the spectral density of non-Gaussian stationary time series
    Yifu Tang, Claudia Kirch, Jeong Eun Lee, Renate Meyer
    http://arxiv.org/abs/2103.01357v1

    • [math.ST]Random tree Besov priors — Towards fractal imaging
    Hanne Kekkonen, Matti Lassas, Eero Saksman, Samuli Siltanen
    http://arxiv.org/abs/2103.00574v1

    • [math.ST]Smeariness Begets Finite Sample Smeariness
    Do Tran, Benjamin Eltzner, Stephan Huckemann
    http://arxiv.org/abs/2103.00469v1

    • [math.ST]Splitting the Sample at the Largest Uncensored Observation
    Ross Maller, Sidney Resnick, Soudabeh Shemehsavar
    http://arxiv.org/abs/2103.01337v1

    • [nlin.SI]Neural Network Approach to Construction of Classical Integrable Systems
    Fumihiro Ishikawa, Hidemaro Suwa, Synge Todo
    http://arxiv.org/abs/2103.00372v1

    • [physics.ao-ph]Statistical Post-processing for Gridded Temperature Forecasts Using Encoder-Decoder Based Deep Convolutional Neural Networks
    Atsushi Kudo
    http://arxiv.org/abs/2103.01479v1

    • [physics.med-ph]Latent linear dynamics in spatiotemporal medical data
    Niklas Gunnarsson, Jens Sjölund, Thomas B. Schön
    http://arxiv.org/abs/2103.00930v1

    • [q-bio.MN]Noncoding RNAs and deep learning neural network discriminate multi-cancer types
    Anyou Wang, Rong Hai, Paul J Rider, Harrison Dulin
    http://arxiv.org/abs/2103.01179v1

    • [q-fin.RM]Explainable AI in Credit Risk Management
    Branka Hadji Misheva, Joerg Osterrieder, Ali Hirsa, Onkar Kulkarni, Stephen Fung Lin
    http://arxiv.org/abs/2103.00949v1

    • [q-fin.ST]Forecasting high-frequency financial time series: an adaptive learning approach with the order book data
    Parley Ruogu Yang
    http://arxiv.org/abs/2103.00264v1

    • [q-fin.ST]Scale matters: The daily, weekly and monthly volatility and predictability of Bitcoin, Gold, and the S&P 500
    Nassim Dehouche
    http://arxiv.org/abs/2103.00395v1

    • [q-fin.TR]The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network
    Zijian Shi, Yu Chen, John Cartlidge
    http://arxiv.org/abs/2103.01670v1

    • [quant-ph]A Hybrid Quantum-Classical Hamiltonian Learning Algorithm
    Youle Wang, Guangxi Li, Xin Wang
    http://arxiv.org/abs/2103.01061v1

    • [quant-ph]Non-invertible Anonymous Communication for the Quantum Era
    Luis Adrián Lizama-Pérez
    http://arxiv.org/abs/2103.00598v1

    • [stat.AP]A Hierarchical Spike-and-Slab Model for Pan-Cancer Survival Using Pan-Omic Data
    Sarah Samorodnitsky, Katherine A. Hoadley, Eric F. Lock
    http://arxiv.org/abs/2103.00629v1

    • [stat.AP]Dynamic Stochastic Blockmodel Regression for Network Data: Application to International Militarized Conflicts
    Santiago Olivella, Tyler Pratt, Kosuke Imai
    http://arxiv.org/abs/2103.00702v1

    • [stat.AP]Empirical study to explore the influence of salesperson’s customer orientation on customer loyalty
    Prathamesh Muzumdar, George Kurian
    http://arxiv.org/abs/2103.01220v1

    • [stat.AP]Examining socioeconomic factors to understand the hospital case-fatality rates of COVID-19 in the city of Sao Paulo, Brazil
    Camila Lorenz, Patricia Marques Moralejo Bermudi, Marcelo Antunes Failla, Breno Souza de Aguiar, Tatiana Natasha Toporcov, Francisco Chiaravalloti Neto, Ligia Vizeu Barrozo
    http://arxiv.org/abs/2103.00594v1

    • [stat.AP]Model-based Personalized Synthetic MR Imaging
    Subrata Pal, Somak Dutta, Ranjan Maitra
    http://arxiv.org/abs/2103.01532v1

    • [stat.AP]Moderating effects of retail operations and hard-sell sales techniques on salesperson’s interpersonal skills and customer repurchase intention
    Prathamesh Muzumdar, Ganga Prasad Basyal, Piyush Vyas
    http://arxiv.org/abs/2103.00054v1

    • [stat.AP]ROC Analyses Based on Measuring Evidence
    Luai Al Labadi, Michael Evans, Qiaoyu Liang
    http://arxiv.org/abs/2103.00772v1

    • [stat.AP]Statistical methods used to combine the effective reproduction number, R(t), and other related measures of COVID-19 in the UK
    T. Maishman, S. Schaap, D. S. Silk, S. J. Nevitt, D. C. Woods, V. E. Bowman
    http://arxiv.org/abs/2103.01742v1

    • [stat.AP]Towards Understanding the COVID-19 Case Fatality Rate
    Donghui Yan, Aiyou Chen, Buqing Yang
    http://arxiv.org/abs/2103.01313v1

    • [stat.CO]A practical tutorial on Variational Bayes
    Minh-Ngoc Tran, Trong-Nghia Nguyen, Viet-Hung Dao
    http://arxiv.org/abs/2103.01327v1

    • [stat.ME]A Stein Goodness of fit Test for Exponential Random Graph Models
    Wenkai Xu, Gesine Reinert
    http://arxiv.org/abs/2103.00580v1

    • [stat.ME]BEAUTY Powered BEAST
    Kai Zhang, Zhigen Zhao, Wen Zhou
    http://arxiv.org/abs/2103.00674v1

    • [stat.ME]Conditional Precedence Orders for Stochastic Comparison of Random Variables
    Sugata Ghosh, Asok K. Nanda
    http://arxiv.org/abs/2103.01650v1

    • [stat.ME]Covariate balancing for causal inference on categorical and continuous treatments
    Seong-ho Lee, Yanyuan Ma, Xavier de Luna
    http://arxiv.org/abs/2103.00527v1

    • [stat.ME]Diffusion Means and Heat Kernel on Manifolds
    Pernille Hansen, Benjamin Eltzner, Stefan Sommer
    http://arxiv.org/abs/2103.00588v1

    • [stat.ME]Dynamic estimation with random forests for discrete-time survival data
    Hoora Moradian, Weichi Yao, Denis Larocque, Jeffrey S. Simonoff, Halina Frydman
    http://arxiv.org/abs/2103.01355v1

    • [stat.ME]Empirical Bayes Model Averaging with Influential Observations: Tuning Zellner’s g Prior for Predictive Robustness
    Christopher M. Hans, Mario Peruggia, Junyan Wang
    http://arxiv.org/abs/2103.01252v1

    • [stat.ME]Exact Simulation of Max-Infinitely Divisible Processes
    Peng Zhong, Raphaël Huser, Thomas Opitz
    http://arxiv.org/abs/2103.00533v1

    • [stat.ME]Factor-augmented Bayesian treatment effects models for panel outcomes
    Helga Wagner, Sylvia Frühwirth-Schnatter, Liana Jacobi
    http://arxiv.org/abs/2103.00977v1

    • [stat.ME]Fast selection of nonlinear mixed effect models using penalized likelihood
    Edouard Ollier
    http://arxiv.org/abs/2103.01621v1

    • [stat.ME]General Bayesian 今日学术视野(2021.3.4) - 图10 calibration of mathematical models
    Antony M. Overstall, James M. McGree
    http://arxiv.org/abs/2103.01132v1

    • [stat.ME]Gradient boosting for extreme quantile regression
    Jasper Velthoen, Clément Dombry, Juan-Juan Cai, Sebastian Engelke
    http://arxiv.org/abs/2103.00808v1

    • [stat.ME]Improving the output quality of official statistics based on machine learning algorithms
    Quinten Meertens, Cees Diks, Jaap van den Herik, Frank Takes
    http://arxiv.org/abs/2103.00834v1

    • [stat.ME]Instrumental variables, spatial confounding and interference
    Andrew Giffin, Brian J. Reich, Shu Yang, Ana G. Rappold
    http://arxiv.org/abs/2103.00304v1

    • [stat.ME]Interpretable Stein Goodness-of-fit Tests on Riemannian Manifolds
    Wenkai Xu, Takeru Matsuda
    http://arxiv.org/abs/2103.00895v1

    • [stat.ME]Jenss-Bayley Latent Change Score Model with Individual Ratio of Growth Acceleration in the Framework of Individual Measurement Occasions
    Jin Liu
    http://arxiv.org/abs/2103.00290v1

    • [stat.ME]Laplacian P-splines for Bayesian inference in the mixture cure model
    Oswaldo Gressani, Christel Faes, Niel Hens
    http://arxiv.org/abs/2103.01526v1

    • [stat.ME]Maximum Approximate Bernstein Likelihood Estimation of Densities in a Two-sample Semiparametric Model
    Zhong Guan
    http://arxiv.org/abs/2103.00648v1

    • [stat.ME]Median Optimal Treatment Regimes
    Liu Leqi, Edward H. Kennedy
    http://arxiv.org/abs/2103.01802v1

    • [stat.ME]Multi Split Conformal Prediction
    Aldo Solari, Vera Djordjilović
    http://arxiv.org/abs/2103.00627v1

    • [stat.ME]Multiscale change point detection via gradual bandwidth adjustment in moving sum processes
    Tijana Levajkovic, Michael Messer
    http://arxiv.org/abs/2103.01060v1

    • [stat.ME]On the Subbagging Estimation for Massive Data
    Tao Zou, Xian Li, Xuan Liang, Hansheng Wang
    http://arxiv.org/abs/2103.00631v1

    • [stat.ME]Online High-Dimensional Change-Point Detection using Topological Data Analysis
    Xiaojun Zheng, Simon Mak, Yao Xie
    http://arxiv.org/abs/2103.00117v1

    • [stat.ME]Optimal Imperfect Classification for Gaussian Functional Data
    Shuoyang Wang, Zuofeng Shang, Guanqun Cao
    http://arxiv.org/abs/2103.00569v1

    • [stat.ME]Penalized Poisson model for network meta-analysis of individual patient time-to-event data
    Edouard Ollier, Pierre Blanchard, Gwénaël Le Teuff, Stefan Michiels
    http://arxiv.org/abs/2103.00069v1

    • [stat.ME]Penalized Projected Kernel Calibration for Computer Models
    Yan Wang
    http://arxiv.org/abs/2103.00807v1

    • [stat.ME]Population Interference in Panel Experiments
    Kevin Wu Han, Iavor Bojinov, Guillaume Basse
    http://arxiv.org/abs/2103.00553v1

    • [stat.ME]Propensity Score Weighting Analysis of Survival Outcomes Using Pseudo-observations
    Shuxi Zeng, Fan Li, Liangyuan Hu, Fan Li
    http://arxiv.org/abs/2103.00605v1

    • [stat.ME]Randomization Inference for Composite Experiments with Spillovers and Peer Effects
    Hui Xu, Guillaume Basse
    http://arxiv.org/abs/2103.00567v1

    • [stat.ME]Spatial sampling design to improve the efficiency of the estimation of the critical parameters of the SARS-CoV-2 epidemic
    Giorgio Alleva, Giuseppe Arbia, Piero Demetrio Falorsi, Vincenzo Nardelli, Alberto Zuliani
    http://arxiv.org/abs/2103.01254v1

    • [stat.ME]Statistical Inference for Local Granger Causality
    Yan Liu, Masanobu Taniguchi, Hernando Ombao
    http://arxiv.org/abs/2103.00209v1

    • [stat.ME]Statistical learning and cross-validation for point processes
    Ottmar Cronie, Mehdi Moradi, Christophe A. N. Biscio
    http://arxiv.org/abs/2103.01356v1

    • [stat.ME]Tangent functional canonical correlation analysis for densities and shapes, with applications to multimodal imaging data
    Min Ho Cho, Sebastian Kurtek, Karthik Bharath
    http://arxiv.org/abs/2103.01097v1

    • [stat.ME]Time-Varying Coefficient Model Estimation Through Radial Basis Functions
    Juan Sosa, Lina Buitrago
    http://arxiv.org/abs/2103.00315v1

    • [stat.ME]Validation of cluster analysis results on validation data: A systematic framework
    Theresa Ullmann, Christian Hennig, Anne-Laure Boulesteix
    http://arxiv.org/abs/2103.01281v1

    • [stat.ML]A Theorem of the Alternative for Personalized Federated Learning
    Shuxiao Chen, Qinqing Zheng, Qi Long, Weijie J. Su
    http://arxiv.org/abs/2103.01901v1

    • [stat.ML]Asymptotic Risk of Overparameterized Likelihood Models: Double Descent Theory for Deep Neural Networks
    Ryumei Nakada, Masaaki Imaizumi
    http://arxiv.org/abs/2103.00500v1

    • [stat.ML]BERT based patent novelty search by training claims to their own description
    Michael Freunek, André Bodmer
    http://arxiv.org/abs/2103.01126v2

    • [stat.ML]Communication-efficient Byzantine-robust distributed learning with statistical guarantee
    Xingcai Zhou, Le Chang, Pengfei Xu, Shaogao Lv
    http://arxiv.org/abs/2103.00373v1

    • [stat.ML]Fairness in Credit Scoring: Assessment, Implementation and Profit Implications
    Nikita Kozodoi, Johannes Jacob, Stefan Lessmann
    http://arxiv.org/abs/2103.01907v1

    • [stat.ML]Fast Adaptation with Linearized Neural Networks
    Wesley J. Maddox, Shuai Tang, Pablo Garcia Moreno, Andrew Gordon Wilson, Andreas Damianou
    http://arxiv.org/abs/2103.01439v1

    • [stat.ML]Feedback Coding for Active Learning
    Gregory Canal, Matthieu Bloch, Christopher Rozell
    http://arxiv.org/abs/2103.00654v1

    • [stat.ML]Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
    Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath
    http://arxiv.org/abs/2103.01890v1

    • [stat.ML]Hessian Eigenspectra of More Realistic Nonlinear Models
    Zhenyu Liao, Michael W. Mahoney
    http://arxiv.org/abs/2103.01519v1

    • [stat.ML]Kernel Interpolation for Scalable Online Gaussian Processes
    Samuel Stanton, Wesley J. Maddox, Ian Delbridge, Andrew Gordon Wilson
    http://arxiv.org/abs/2103.01454v1

    • [stat.ML]Learning Proposals for Probabilistic Programs with Inference Combinators
    Sam Stites, Heiko Zimmermann, Hao Wu, Eli Sennesh, Jan-Willem can de Meent
    http://arxiv.org/abs/2103.00668v1

    • [stat.ML]Meta-learning One-class Classifiers with Eigenvalue Solvers for Supervised Anomaly Detection
    Tomoharu Iwata, Atsutoshi Kumagai
    http://arxiv.org/abs/2103.00684v1

    • [stat.ML]Meta-learning representations for clustering with infinite Gaussian mixture models
    Tomoharu Iwata
    http://arxiv.org/abs/2103.00694v1

    • [stat.ML]Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks
    Irina Deeva, Anna Bubnova, Petr Andriushchenko, Anton Voskresenskiy, Nikita Bukhanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya
    http://arxiv.org/abs/2103.01804v1

    • [stat.ML]Panel semiparametric quantile regression neural network for electricity consumption forecasting
    Xingcai Zhou, Jiangyan Wang
    http://arxiv.org/abs/2103.00711v1

    • [stat.ML]Practical Privacy Filters and Odometers with Rényi Differential Privacy and Applications to Differentially Private Deep Learning
    Mathias Lécuyer
    http://arxiv.org/abs/2103.01379v1

    • [stat.ML]Privacy-Preserving Distributed SVD via Federated Power
    Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang
    http://arxiv.org/abs/2103.00704v1

    • [stat.ML]Probabilistic Inference for Structural Health Monitoring: New Modes of Learning from Data
    Lawrence A. Bull, Paul Gardner, Timothy J. Rogers, Elizabeth J. Cross, Nikolaos Dervilis, Keith Worden
    http://arxiv.org/abs/2103.01676v1

    • [stat.ML]Self-Regularity of Non-Negative Output Weights for Overparameterized Two-Layer Neural Networks
    David Gamarnik, Eren C. Kızıldağ, Ilias Zadik
    http://arxiv.org/abs/2103.01887v1

    • [stat.ML]Slow-Growing Trees
    Philippe Goulet Coulombe
    http://arxiv.org/abs/2103.01926v1

    • [stat.ML]Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior
    Mario González, Andrés Almansa, Pauline Tan
    http://arxiv.org/abs/2103.01648v1

    • [stat.ML]The Mathematics Behind Spectral Clustering And The Equivalence To PCA
    T Shen
    http://arxiv.org/abs/2103.00733v1

    • [stat.ML]UCB Momentum Q-learning: Correcting the bias without forgetting
    Pierre Menard, Omar Darwiche Domingues, Xuedong Shang, Michal Valko
    http://arxiv.org/abs/2103.01312v1

    • [stat.ML]Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance)
    Jan Stanczuk, Christian Etmann, Lisa Maria Kreusser, Carola-Bibiane Schonlieb
    http://arxiv.org/abs/2103.01678v1