cs.AI - 人工智能
    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.DL - 数字图书馆
    cs.DM - 离散数学
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    cs.MA - 多代理系统
    cs.MM - 多媒体
    cs.NE - 神经与进化计算
    cs.PF - 计算性能
    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
    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
    math.NT - 数论
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.chem-ph -化学物理
    physics.flu-dyn - 流体动力学
    physics.optics - 光学
    physics.soc-ph - 物理学与社会
    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
    • [cs.AI]Attribute Selection using Contranominal Scales
    • [cs.AI]Discrepancies in Epidemiological Modeling of Aggregated Heterogeneous Data
    • [cs.AI]Improving Label Quality by Jointly Modeling Items and Annotators
    • [cs.AI]Learning Space Partitions for Path Planning
    • [cs.AI]MILP, pseudo-boolean, and OMT solvers for optimal fault-tolerant placements of relay nodes in mission critical wireless networks
    • [cs.AI]Multi-Task Learning for User Engagement and Adoption in Live Video Streaming Events
    • [cs.AI]On Limited-Memory Subsampling Strategies for Bandits
    • [cs.AI]Optimal personalised treatment computation through in silico clinical trials on patient digital twins
    • [cs.AI]Proper Value Equivalence
    • [cs.AI]Score-Based Explanations in Data Management and Machine Learning: An Answer-Set Programming Approach to Counterfactual Analysis
    • [cs.CL]A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss
    • [cs.CL]A Condense-then-Select Strategy for Text Summarization
    • [cs.CL]A Discriminative Entity-Aware Language Model for Virtual Assistants
    • [cs.CL]Ad Text Classification with Transformer-Based Natural Language Processing Methods
    • [cs.CL]ArgFuse: A Weakly-Supervised Framework for Document-Level Event Argument Aggregation
    • [cs.CL]CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction
    • [cs.CL]CPM-2: Large-scale Cost-effective Pre-trained Language Models
    • [cs.CL]Calliar: An Online Handwritten Dataset for Arabic Calligraphy
    • [cs.CL]Challenges in Translation of Emotions in Multilingual User-Generated Content: Twitter as a Case Study
    • [cs.CL]Conversational Agents in Software Engineering: Survey, Taxonomy and Challenges
    • [cs.CL]Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ?
    • [cs.CL]Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification
    • [cs.CL]Empower Distantly Supervised Relation Extraction with Collaborative Adversarial Training
    • [cs.CL]Enhancing Question Generation with Commonsense Knowledge
    • [cs.CL]Explicit Interaction Network for Aspect Sentiment Triplet Extraction
    • [cs.CL]Extractive approach for text summarisation using graphs
    • [cs.CL]Hybrid approach to detecting symptoms of depression in social media entries
    • [cs.CL]Iterative Network Pruning with Uncertainty Regularization for Lifelong Sentiment Classification
    • [cs.CL]JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
    • [cs.CL]Learning to Rank Question Answer Pairs with Bilateral Contrastive Data Augmentation
    • [cs.CL]Multi-Pair Text Style Transfer on Unbalanced Data
    • [cs.CL]Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis
    • [cs.CL]Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence Modeling
    • [cs.CL]Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets
    • [cs.CL]ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction
    • [cs.CL]STEP-EZ: Syntax Tree guided semantic ExPlanation for Explainable Zero-shot modeling of clinical depression symptoms from text
    • [cs.CL]Self-Calibrating Neural-Probabilistic Model for Authorship Verification Under Covariate Shift
    • [cs.CL]Transformers for Headline Selection for Russian News Clusters
    • [cs.CL]TweeNLP: A Twitter Exploration Portal for Natural Language Processing
    • [cs.CR]Non-parametric Differentially Private Confidence Intervals for the Median
    • [cs.CR]Privacy-preserving Publication and Sharing of COVID-19 Pandemic Data
    • [cs.CV]3D Object Detection for Autonomous Driving: A Survey
    • [cs.CV]3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching
    • [cs.CV]A system of vision sensor based deep neural networks for complex driving scene analysis in support of crash risk assessment and prevention
    • [cs.CV]AdaZoom: Adaptive Zoom Network for Multi-Scale Object Detection in Large Scenes
    • [cs.CV]Adversarial Manifold Matching via Deep Metric Learning for Generative Modeling
    • [cs.CV]Affect-driven Engagement Measurement from Videos
    • [cs.CV]An End-to-End Khmer Optical Character Recognition using Sequence-to-Sequence with Attention
    • [cs.CV]Attack to Fool and Explain Deep Networks
    • [cs.CV]Attend What You Need: Motion-Appearance Synergistic Networks for Video Question Answering
    • [cs.CV]Augmented 2D-TAN: A Two-stage Approach for Human-centric Spatio-Temporal Video Grounding
    • [cs.CV]Automated Deepfake Detection
    • [cs.CV]Automatic Plant Cover Estimation with CNNs Automatic Plant Cover Estimation with Convolutional Neural Networks
    • [cs.CV]CAMERAS: Enhanced Resolution And Sanity preserving Class Activation Mapping for image saliency
    • [cs.CV]CLIP2Video: Mastering Video-Text Retrieval via Image CLIP
    • [cs.CV]CUDA-GR: Controllable Unsupervised Domain Adaptation for Gaze Redirection
    • [cs.CV]Can poachers find animals from public camera trap images?
    • [cs.CV]CenterAtt: Fast 2-stage Center Attention Network
    • [cs.CV]CompConv: A Compact Convolution Module for Efficient Feature Learning
    • [cs.CV]Confidence-Guided Radiology Report Generation
    • [cs.CV]Crop-Transform-Paste: Self-Supervised Learning for Visual Tracking
    • [cs.CV]Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification
    • [cs.CV]Delving into the pixels of adversarial samples
    • [cs.CV]DiGS : Divergence guided shape implicit neural representation for unoriented point clouds
    • [cs.CV]Distilling effective supervision for robust medical image segmentation with noisy labels
    • [cs.CV]Dynamical Deep Generative Latent Modeling of 3D Skeletal Motion
    • [cs.CV]Exploring Semantic Relationships for Unpaired Image Captioning
    • [cs.CV]Exploring Vision Transformers for Fine-grained Classification
    • [cs.CV]Exploring Visual Context for Weakly Supervised Person Search
    • [cs.CV]FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild
    • [cs.CV]Fast Simultaneous Gravitational Alignment of Multiple Point Sets
    • [cs.CV]FloorPP-Net: Reconstructing Floor Plans using Point Pillars for Scan-to-BIM
    • [cs.CV]Hard hat wearing detection based on head keypoint localization
    • [cs.CV]Humble Teachers Teach Better Students for Semi-Supervised Object Detection
    • [cs.CV]Informative Class Activation Maps
    • [cs.CV]Interactive Object Segmentation with Dynamic Click Transform
    • [cs.CV]Interpretable Face Manipulation Detection via Feature Whitening
    • [cs.CV]Interventional Video Grounding with Dual Contrastive Learning
    • [cs.CV]Knowledge Distillation via Instance-level Sequence Learning
    • [cs.CV]Large-scale image segmentation based on distributed clustering algorithms
    • [cs.CV]Learning to Track Object Position through Occlusion
    • [cs.CV]Low-Power Multi-Camera Object Re-Identification using Hierarchical Neural Networks
    • [cs.CV]MSN: Efficient Online Mask Selection Network for Video Instance Segmentation
    • [cs.CV]Mobile Sensing for Multipurpose Applications in Transportation
    • [cs.CV]More than Encoder: Introducing Transformer Decoder to Upsample
    • [cs.CV]Moving in a 360 World: Synthesizing Panoramic Parallaxes from a Single Panorama
    • [cs.CV]Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering
    • [cs.CV]Multiple Object Tracking with Mixture Density Networks for Trajectory Estimation
    • [cs.CV]Neighborhood Contrastive Learning for Novel Class Discovery
    • [cs.CV]NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction
    • [cs.CV]Neural Marching Cubes
    • [cs.CV]Neural Network Facial Authentication for Public Electric Vehicle Charging Station
    • [cs.CV]OadTR: Online Action Detection with Transformers
    • [cs.CV]Obstacle Detection for BVLOS Drones
    • [cs.CV]One Million Scenes for Autonomous Driving: ONCE Dataset
    • [cs.CV]PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging
    • [cs.CV]Place recognition survey: An update on deep learning approaches
    • [cs.CV]Plant Disease Detection Using Image Processing and Machine Learning
    • [cs.CV]Practical Transferability Estimation for Image Classification Tasks
    • [cs.CV]Pre-training also Transfers Non-Robustness
    • [cs.CV]Quality-Aware Memory Network for Interactive Volumetric Image Segmentation
    • [cs.CV]ReGO: Reference-Guided Outpainting for Scenery Image
    • [cs.CV]Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model via a Self-Supervised Contrastive Learning Method
    • [cs.CV]Robust Pooling through the Data Mode
    • [cs.CV]SHREC 2021: Track on Skeleton-based Hand Gesture Recognition in the Wild
    • [cs.CV]SODA10M: Towards Large-Scale Object Detection Benchmark for Autonomous Driving
    • [cs.CV]Segmentation of cell-level anomalies in electroluminescence images of photovoltaic modules
    • [cs.CV]Simple Distillation Baselines for Improving Small Self-supervised Models
    • [cs.CV]Single View Physical Distance Estimation using Human Pose
    • [cs.CV]Solution for Large-scale Long-tailed Recognition with Noisy Labels
    • [cs.CV]Structured Sparse R-CNN for Direct Scene Graph Generation
    • [cs.CV]Supervised learning for crop/weed classification based on color and texture features
    • [cs.CV]Surgical data science for safe cholecystectomy: a protocol for segmentation of hepatocystic anatomy and assessment of the critical view of safety
    • [cs.CV]TCIC: Theme Concepts Learning Cross Language and Vision for Image Captioning
    • [cs.CV]TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition
    • [cs.CV]TNT: Text-Conditioned Network with Transductive Inference for Few-Shot Video Classification
    • [cs.CV]Tag, Copy or Predict: A Unified Weakly-Supervised Learning Framework for Visual Information Extraction using Sequences
    • [cs.CV]Temporal Early Exits for Efficient Video Object Detection
    • [cs.CV]The Animal ID Problem: Continual Curation
    • [cs.CV]The Arm-Swing Is Discriminative in Video Gait Recognition for Athlete Re-Identification
    • [cs.CV]ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation
    • [cs.CV]TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?
    • [cs.CV]Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes
    • [cs.CV]Towards Long-Form Video Understanding
    • [cs.CV]Towards Single Stage Weakly Supervised Semantic Segmentation
    • [cs.CV]Trainable Class Prototypes for Few-Shot Learning
    • [cs.CV]Two-Stream Consensus Network: Submission to HACS Challenge 2021 Weakly-Supervised Learning Track
    • [cs.CV]Unbalanced Feature Transport for Exemplar-based Image Translation
    • [cs.CV]Understanding Object Dynamics for Interactive Image-to-Video Synthesis
    • [cs.CV]Unsupervised Deep Learning by Injecting Low-Rank and Sparse Priors
    • [cs.CV]VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning
    • [cs.CV]VQA-Aid: Visual Question Answering for Post-Disaster Damage Assessment and Analysis
    • [cs.CV]Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net
    • [cs.CV]Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations
    • [cs.CY]A Comparative Study of Online Disinformation and Offline Protests
    • [cs.CY]Fostering Student Engagement in a Mobile Formative Assessment System for High-School Economics
    • [cs.CY]Reassessing Measures for Press Freedom
    • [cs.DB]A Generic Distributed Clustering Framework for Massive Data
    • [cs.DB]Demonstration of Panda: A Weakly Supervised Entity Matching System
    • [cs.DC]Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication
    • [cs.DC]Jolteon and Ditto: Network-Adaptive Efficient Consensus with Asynchronous Fallback
    • [cs.DL]On predicting research grants productivity
    • [cs.DM]Abstract Geometrical Computation 11: Slanted Firing Squad Synchronisation on Signal Machines
    • [cs.G 32ee T]Proceedings Eighteenth Conference on Theoretical Aspects of Rationality and Knowledge
    • [cs.HC]Anticipatory Detection of Compulsive Body-focused Repetitive Behaviors with Wearables
    • [cs.IR]A Comprehensive Review on Non-Neural Networks Collaborative Filtering Recommendation Systems
    • [cs.IR]BanditMF: Multi-Armed Bandit Based Matrix Factorization Recommender System
    • [cs.IR]Computational Pronunciation Analysis in Sung Utterances
    • [cs.IR]Context-Aware Legal Citation Recommendation using Deep Learning
    • [cs.IR]Data Optimisation for a Deep Learning Recommender System
    • [cs.IR]DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation
    • [cs.IR]Leveraging Multiple Online Sources for Accurate Income Verification
    • [cs.IR]On Sampling Top-K Recommendation Evaluation
    • [cs.IR]Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
    • [cs.IT]Algorithm Unrolling for Massive Access via Deep Neural Network with Theoretical Guarantee
    • [cs.IT]Coded Faster-than-Nyquist Signaling for Short Packet Communications
    • [cs.IT]Competitive MA-DRL for Transmit Power Pool Design in Semi-Grant-Free NOMA Systems
    • [cs.IT]Deep Learning for Intelligent Wireless MAC: Exploiting Real Data Sampled on 2.4GHz Frequency Band
    • [cs.IT]Deep Learning-Based Active User Detection for Grant-free SCMA Systems
    • [cs.IT]Deep Neural Network-Based Blind Multiple User Detection for Grant-free Multi-User Shared Access
    • [cs.IT]Improved Private and Secure Distributed (Batch) Matrix Multiplication
    • [cs.IT]Infinite families of linear codes supporting more $t$-designs
    • [cs.IT]Linear Codes Associated to Symmetric Determinantal Varieties: Even Rank Case
    • [cs.IT]ML and MAP Device Activity Detections for Grant-Free Massive Access in Multi-Cell Networks
    • [cs.IT]Near-Optimal Pool Testing under Urgency Constraints
    • [cs.IT]On decoding of a specific type of self-dual codes
    • [cs.IT]On the Capacity-Achieving Input of Channels with Phase Quantization
    • [cs.IT]On the Ergodic Capacity of Reconfigurable Intelligent Surface (RIS)-Aided MIMO Channels
    • [cs.IT]Performance Evaluation of Cooperative NOMA-based Improved Hybrid SWIPT Protocol
    • [cs.IT]Realizing Neural Decoder at the Edge with Ensembled BNN
    • [cs.IT]Spatial Covariance Matrix Reconstruction for DOA Estimation in Hybrid Massive MIMO Systems with Multiple Radio Frequency Chains
    • [cs.IT]Strong Singleton type upper bounds for linear insertion-deletion codes
    • [cs.IT]Universal Rate-Distortion-Perception Representations for Lossy Compression
    • [cs.IT]Wireless Communication Aided by Intelligent Reflecting Surface: Active or Passive?
    • [cs.LG]A Game-Theoretic Taxonomy of Visual Concepts in DNNs
    • [cs.LG]A Max-Min Entropy Framework for Reinforcement Learning
    • [cs.LG]A Unified View of Algorithms for Path Planning Using Probabilistic Inference on Factor Graphs
    • [cs.LG]A causal view on compositional data
    • [cs.LG]A compressive multi-kernel method for privacy-preserving machine learning
    • [cs.LG]AOMD: An Analogy-aware Approach to Offensive Meme Detection on Social Media
    • [cs.LG]Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling
    • [cs.LG]Active Learning for Deep Neural Networks on Edge Devices
    • [cs.LG]Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem
    • [cs.LG]Adversarial Examples Make Strong Poisons
    • [cs.LG]Analytically Tractable Bayesian Deep Q-Learning
    • [cs.LG]Approximation capabilities of measure-preserving neural networks
    • [cs.LG]Attention-based Neural Network for Driving Environment Complexity Perception
    • [cs.LG]Bayesian inference of ODEs with Gaussian processes
    • [cs.LG]BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation
    • [cs.LG]Better Training using Weight-Constrained Stochastic Dynamics
    • [cs.LG]Boosting Offline Reinforcement Learning with Residual Generative Modeling
    • [cs.LG]Boundary Graph Neural Networks for 3D Simulations
    • [cs.LG]CD-SGD: Distributed Stochastic Gradient Descent with Compression and Delay Compensation
    • [cs.LG]Can contrastive learning avoid shortcut solutions?
    • [cs.LG]Cogradient Descent for Dependable Learning
    • [cs.LG]Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning
    • [cs.LG]Compressing Deep ODE-Nets using Basis Function Expansions
    • [cs.LG]Conditional Neural Relational Inference for Interacting Systems
    • [cs.LG]Contrastive Multi-Modal Clustering
    • [cs.LG]Corruption Robust Active Learning
    • [cs.LG]Decadal Forecasts with ResDMD: a Residual DMD Neural Network
    • [cs.LG]Deep Generative Learning via Schrödinger Bridge
    • [cs.LG]Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand
    • [cs.LG]Dependency Structure Misspecification in Multi-Source Weak Supervision Models
    • [cs.LG]Does Optimal Source Task Performance Imply Optimal Pre-training for a Target Task?
    • [cs.LG]Effects of boundary conditions in fully convolutional networks for learning spatio-temporal dynamics
    • [cs.LG]EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization
    • [cs.LG]Fast PDN Impedance Prediction Using Deep Learning
    • [cs.LG]FedCM: Federated Learning with Client-level Momentum
    • [cs.LG]FedXGBoost: Privacy-Preserving XGBoost for Federated Learning
    • [cs.LG]Federated Learning with Positive and Unlabeled Data
    • [cs.LG]Friendly Training: Neural Networks Can Adapt Data To Make Learning Easier
    • [cs.LG]GRAND: Graph Neural Diffusion
    • [cs.LG]Generalization in the Face of Adaptivity: A Bayesian Perspective
    • [cs.LG]Graceful Degradation and Related Fields
    • [cs.LG]Graph Attention Networks with LSTM-based Path Reweighting
    • [cs.LG]Graph Neural Networks for Learning Real-Time Prices in Electricity Market
    • [cs.LG]GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction
    • [cs.LG]Group-Structured Adversarial Training
    • [cs.LG]Heterogeneous Multi-task Learning with Expert Diversity
    • [cs.LG]How Do Adam and Training Strategies Help BNNs Optimization?
    • [cs.LG]Improving Compositional Generalization in Classification Tasks via Structure Annotations
    • [cs.LG]Improving Multi-Modal Learning with Uni-Modal Teachers
    • [cs.LG]Is Shapley Value fair? Improving Client Selection for Mavericks in Federated Learning
    • [cs.LG]Learning Timestamp-Level Representations for Time Series with Hierarchical Contrastive Loss
    • [cs.LG]Learning and Generalization in Overparameterized Normalizing Flows
    • [cs.LG]Leveraging Conditional Generative Models in a General Explanation Framework of Classifier Decisions
    • [cs.LG]Leveraging Language to Learn Program Abstractions and Search Heuristics
    • [cs.LG]Lossy Compression for Lossless Prediction
    • [cs.LG]Low-rank Dictionary Learning for Unsupervised Feature Selection
    • [cs.LG]Machine learning in the social and health sciences
    • [cs.LG]Matrix Encoding Networks for Neural Combinatorial Optimization
    • [cs.LG]Memory Augmented Optimizers for Deep Learning
    • [cs.LG]Multiplying Matrices Without Multiplying
    • [cs.LG]Multirate Training of Neural Networks
    • [cs.LG]Multivariate Data Explanation by Jumping Emerging Patterns Visualization
    • [cs.LG]Nearly Minimax Optimal Adversarial Imitation Learning with Known and Unknown Transitions
    • [cs.LG]Neural Controlled Differential Equations for Online Prediction Tasks
    • [cs.LG]Neural Network Classifier as Mutual Information Evaluator
    • [cs.LG]Neural Spectral Marked Point Processes
    • [cs.LG]Neural network interpretability for forecasting of aggregated renewable generation
    • [cs.LG]On Stein Variational Neural Network Ensembles
    • [cs.LG]On fine-tuning of Autoencoders for Fuzzy rule classifiers
    • [cs.LG]On the Cryptographic Hardness of Learning Single Periodic Neurons
    • [cs.LG]Open-set Label Noise Can Improve Robustness Against Inherent Label Noise
    • [cs.LG]Opportunities and challenges in partitioning the graph measure space of real-world networks
    • [cs.LG]OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
    • [cs.LG]Optimal Strategies for Decision Theoretic Online Learning
    • [cs.LG]Practical Assessment of Generalization Performance Robustness for Deep Networks via Contrastive Examples
    • [cs.LG]Prediction of the facial growth direction with Machine Learning methods
    • [cs.LG]Prediction-Free, Real-Time Flexible Control of Tidal Lagoons through Proximal Policy Optimisation: A Case Study for the Swansea Lagoon
    • [cs.LG]QuaPy: A Python-Based Framework for Quantification
    • [cs.LG]Regularization is all you Need: Simple Neural Nets can Excel on Tabular Data
    • [cs.LG]Robust M-estimation-based Tensor Ring Completion: a Half-quadratic Minimization Approach
    • [cs.LG]Robust Regression via Model Based Methods
    • [cs.LG]STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
    • [cs.LG]Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments
    • [cs.LG]Secure Distributed Training at Scale
    • [cs.LG]Semi-supervised Optimal Transport with Self-paced Ensemble for Cross-hospital Sepsis Early Detection
    • [cs.LG]Smooth Sequential Optimisation with Delayed Feedback
    • [cs.LG]Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
    • [cs.LG]Stability of Graph Convolutional Neural Networks to Stochastic Perturbations
    • [cs.LG]TD-GEN: Graph Generation With Tree Decomposition
    • [cs.LG]Task Attended Meta-Learning for Few-Shot Learning
    • [cs.LG]Teacher’s pet: understanding and mitigating biases in distillation
    • [cs.LG]The Perils of Learning Before Optimizing
    • [cs.LG]TinyML: Analysis of Xtensa LX6 microprocessor for Neural Network Applications by ESP32 SoC
    • [cs.LG]Towards Better Shale Gas Production Forecasting Using Transfer Learning
    • [cs.LG]Towards a Query-Optimal and Time-Efficient Algorithm for Clustering with a Faulty Oracle
    • [cs.LG]Transfer Bayesian Meta-learning via Weighted Free Energy Minimization
    • [cs.LG]Variance-Dependent Best Arm Identification
    • [cs.LG]Vehicle Trajectory Prediction in City-scale Road Networks using a Direction-based Sequence-to-Sequence Model with Spatiotemporal Attention Mechanisms
    • [cs.LG]iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
    • [cs.LO]Defeasible Reasoning via Datalog$^\neg$
    • [cs.MA]Curriculum-Driven Multi-Agent Learning and the Role of Implicit Communication in Teamwork
    • [cs.MM]Multi-Contextual Design of Convolutional Neural Network for Steganalysis
    • [cs.NE]The Role of Evolution in Machine Intelligence
    • [cs.PF]AutoTune: Improving End-to-end Performance and Resource Efficiency for Microservice Applications
    • [cs.RO]Domain and Modality Gaps for LiDAR-based Person Detection on Mobile Robots
    • [cs.RO]Exoskeleton-Based Multimodal Action and Movement Recognition: Identifying and Developing the Optimal Boosted Learning Approach
    • [cs.RO]Grasping Benchmarks: Normalizing for Object Size & Approximating Hand Workspaces
    • [cs.RO]Guiding vector fields in Paparazzi autopilot
    • [cs.RO]HapFIC: An Adaptive Force/Position Controller for Safe Environment Interaction in Articulated Systems
    • [cs.RO]High-level Features for Resource Economy and Fast Learning in Skill Transfer
    • [cs.RO]Image-guided Breast Biopsy of MRI-visible Lesions with a Hand-mounted Motorised Needle Steering Tool
    • [cs.RO]Investigating the role of educational robotics in formal mathematics education: the case of geometry for 15-year-old students
    • [cs.RO]On the Importance of Environments in Human-Robot Coordination
    • [cs.RO]PHYSFRAME: Type Checking Physical Frames of Reference for Robotic Systems
    • [cs.RO]Sample Efficient Social Navigation Using Inverse Reinforcement Learning
    • [cs.RO]Towards a Framework for Changing-Contact Robot Manipulation
    • [cs.SD]Advances in Speech Vocoding for Text-to-Speech with Continuous Parameters
    • [cs.SD]Affinity Mixup for Weakly Supervised Sound Event Detection
    • [cs.SD]EML Online Speech Activity Detection for the Fearless Steps Challenge Phase-III
    • [cs.SE]GLIB: Towards Automated Test Oracle for Graphically-Rich Applications
    • [cs.SI]Dynamics of Disruption in Science and Technology
    • [cs.SI]FauxWard: A Graph Neural Network Approach to Fauxtography Detection Using Social Media Comments
    • [cs.SI]Finding critical edges in complex networks through local information
    • [cs.SI]Flipping Stance: Social Influence on Bot’s and Non Bot’s COVID Vaccine Stance
    • [cs.SI]Large-Scale Network Embedding in Apache Spark
    • [cs.SI]MetaDetector: Meta Event Knowledge Transfer for Fake News Detection
    • [cs.SI]Overall Behavioural Index (OBI) For Measuring Segregation
    • [cs.SI]Predicting Critical Nodes in Temporal Networks by Dynamic Graph Convolutional Networks
    • [cs.SI]Pricing Social Visibility Service in Online Social Networks: Modeling and Algorithms
    • [cs.SI]Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd
    • [cs.SI]Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling
    • [econ.EM]On Testing Equal Conditional Predictive Ability Under Measurement Error
    • [eess.AS]GPLA-12: An Acoustic Signal Dataset of Gas Pipeline Leakage
    • [eess.AS]Non-native English lexicon creation for bilingual speech synthesis
    • [eess.AS]UniTTS: Residual Learning of Unified Embedding Space for Speech Style Control
    • [eess.IV]Applying VertexShuffle Toward 360-Degree Video Super-Resolution on Focused-Icosahedral-Mesh
    • [eess.IV]Brain tumor grade classification Using LSTM Neural Networks with Domain Pre-Transforms
    • [eess.IV]CataNet: Predicting remaining cataract surgery duration
    • [eess.IV]Direct Reconstruction of Linear Parametric Images from Dynamic PET Using Nonlocal Deep Image Prior
    • [eess.IV]Estimating MRI Image Quality via Image Reconstruction Uncertainty
    • [eess.IV]Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation
    • [eess.IV]Generative Model Adversarial Training for Deep Compressed Sensing
    • [eess.IV]Implementing a Detection System for COVID-19 based on Lung Ultrasound Imaging and Deep Learning
    • [eess.IV]Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
    • [eess.IV]One-to-many Approach for Improving Super-Resolution
    • [eess.IV]Reversible Colour Density Compression of Images using cGANs
    • [eess.IV]Underwater Image Restoration via Contrastive Learning and a Real-world Dataset
    • [eess.SP]Active and Dynamic Beam Tracking UnderStochastic Mobility
    • [eess.SP]EMG Signal Classification Using Reflection Coefficients and Extreme Value Machine
    • [eess.SP]Electromagnetic Interference in RIS-Aided Communications
    • [eess.SP]Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification
    • [eess.SP]Machine Learning based optimization for interval uncertainty propagation with application to vibro-acoustic models
    • [eess.SP]Parallel frequency function-deep neural network for efficient complex broadband signal approximation
    • [eess.SP]Signal Processing Based Deep Learning for Blind Symbol Decoding and Modulation Classification
    • [eess.SY]Brushless Motor Performance Optimization by Eagle Strategy with Firefly and PSO
    • [eess.SY]DiffLoop: Tuning PID controllers by differentiating through the feedback loop
    • [eess.SY]Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information
    • [eess.SY]Minimizing Delay in Network Function Visualization with Quantum Computing
    • [eess.SY]Parallel Statistical Model Checking for Safety Verification in Smart Grids
    • [math.NT]Solving the linear approximation problem
    • [math.OC]Complexity-Free Generalization via Distributionally Robust Optimization
    • [math.OC]Distributed Picard Iteration: Application to Distributed EM and Distributed PCA
    • [math.OC]QUBO transformation using Eigenvalue Decomposition
    • [math.ST]Some smooth sequential empirical copula processes and their multiplier bootstraps under strong mixing
    • [math.ST]Weighted Fractional Generalized Cumulative Past Entropy
    • [physics.chem-ph]Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery
    • [physics.flu-dyn]Scientific multi-agent reinforcement learning for wall-models of turbulent flows
    • [physics.optics]Fundamental bounds on the precision of iSCAT, COBRI and dark-field microscopy for 3D localization and mass photometry
    • [physics.soc-ph]Cumulative structure and path length in networks of knowledge
    • [physics.soc-ph]Intersectional synergies: untangling irreducible effects of intersecting identities via information decomposition
    • [quant-ph]QFCNN: Quantum Fourier Convolutional Neural Network
    • [quant-ph]Quantum Machine Learning: Fad or Future?
    • [quant-ph]Rényi divergence inequalities via interpolation, with applications to generalised entropic uncertainty relations
    • [stat.AP]Bayesian decision theory for tree-based adaptive screening tests with an application to youth delinquency
    • [stat.AP]Combined tests based on restricted mean time lost for competing risks data
    • [stat.AP]Dynamic prediction and analysis based on restricted mean survival time in survival analysis with nonproportional hazards
    • [stat.AP]Geographic and Racial Disparities in the Incidence of Low Birthweight in Pennsylvania
    • [stat.AP]The Expected Value of Perfect Information for Risk Prediction Models
    • [stat.CO]Circuits for robust designs
    • [stat.CO]Life-cycle assessment for flutter probability of a long-span suspension bridge based on field monitoring data
    • [stat.ME]A generalized EMS algorithm for model selection with incomplete data
    • [stat.ME]Bayesian inference for continuous-time hidden Markov models with an unknown number of states
    • [stat.ME]Choosing the Estimand When Matching or Weighting in Observational Studies
    • [stat.ME]Constrained randomization and statistical inference for multi-arm parallel cluster randomized controlled trials
    • [stat.ME]Discussion on Competition for Spatial Statistics for Large Datasets
    • [stat.ME]Dynamic group testing to control and monitor disease progression in a population
    • [stat.ME]Estimation of time-specific intervention effects on continuously distributed time-to-event outcomes by targeted maximum likelihood estimation
    • [stat.ME]Fasano-Franceschini Test: an Implementation of a 2-Dimensional Kolmogorov-Smirnov test in R
    • [stat.ME]Generalized Spatial and Spatiotemporal ARCH Models
    • [stat.ME]On the bimodal Gumbel model with application to environmental data
    • [stat.ME]Robust Hierarchical Modeling of Counts under Zero-inflation and Outliers
    • [stat.ME]Scalable Bayesian change point detection with spike and slab priors
    • [stat.ME]Scalable Bayesian inference for time series via divide-and-conquer
    • [stat.ME]Sparse logistic regression on functional data
    • [stat.ME]Systemic Infinitesimal Over-dispersion on General Stochastic Graphical Models
    • [stat.ME]The Tangent Exponential Model
    • [stat.ME]Tumor Radiogenomics with Bayesian Layered Variable Selection
    • [stat.ME]maars: Tidy Inference under the ‘Models as Approximations’ Framework in R
    • [stat.ML]Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis
    • [stat.ML]Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation
    • [stat.ML]Deep Learning for Functional Data Analysis with Adaptive Basis Layers
    • [stat.ML]Differentiable Particle Filtering without Modifying the Forward Pass
    • [stat.ML]Learning the Preferences of Uncertain Humans with Inverse Decision Theory
    • [stat.ML]Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation
    • [stat.ML]Nested Variational Inference
    • [stat.ML]On the benefits of maximum likelihood estimation for Regression and Forecasting
    • [stat.ML]Outlier Detection and Spatial Analysis Algorithms
    • [stat.ML]Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo
    • [stat.ML]Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series
    • [stat.ML]Stratified Learning: a general-purpose statistical method for improved learning under Covariate Shift
    ·····································
    • [cs.AI]Attribute Selection using Contranominal Scales
    Dominik Dürrschnabel, Maren Koyda, Gerd Stumme
    http://arxiv.org/abs/2106.10978v1
    • [cs.AI]Discrepancies in Epidemiological Modeling of Aggregated Heterogeneous Data
    Anna L. Trella, Peniel N. Argaw, Michelle M. Li, James A. Hay
    http://arxiv.org/abs/2106.10610v1
    • [cs.AI]Improving Label Quality by Jointly Modeling Items and Annotators
    Tharindu Cyril Weerasooriya, Alexander G. Ororbia, Christopher M. Homan
    http://arxiv.org/abs/2106.10600v1
    • [cs.AI]Learning Space Partitions for Path Planning
    Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian
    http://arxiv.org/abs/2106.10544v1
    • [cs.AI]MILP, pseudo-boolean, and OMT solvers for optimal fault-tolerant placements of relay nodes in mission critical wireless networks
    Quian Matteo Chen, Alberto Finzi, Toni Mancini, Igor Melatti, Enrico Tronci
    http://arxiv.org/abs/2106.10685v1
    • [cs.AI]Multi-Task Learning for User Engagement and Adoption in Live Video Streaming Events
    Stefanos Antaris, Dimitrios Rafailidis, Romina Arriaza
    http://arxiv.org/abs/2106.10305v1
    • [cs.AI]On Limited-Memory Subsampling Strategies for Bandits
    Dorian Baudry, Yoan Russac, Olivier Cappé
    http://arxiv.org/abs/2106.10935v1
    • [cs.AI]Optimal personalised treatment computation through in silico clinical trials on patient digital twins
    Stefano Sinisi, Vadim Alimguzhin, Toni Mancini, Enrico Tronci, Federico Mari, Brigitte Leeners
    http://arxiv.org/abs/2106.10684v1
    • [cs.AI]Proper Value Equivalence
    Christopher Grimm, André Barreto, Gregory Farquhar, David Silver, Satinder Singh
    http://arxiv.org/abs/2106.10316v1
    • [cs.AI]Score-Based Explanations in Data Management and Machine Learning: An Answer-Set Programming Approach to Counterfactual Analysis
    Leopoldo Bertossi
    http://arxiv.org/abs/2106.10562v1
    • [cs.CL]A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss
    Prasanna Parthasarathi, Mohamed Abdelsalam, Joelle Pineau, Sarath Chandar
    http://arxiv.org/abs/2106.10619v1
    • [cs.CL]A Condense-then-Select Strategy for Text Summarization
    Hou Pong Chan, Irwin King
    http://arxiv.org/abs/2106.10468v1
    • [cs.CL]A Discriminative Entity-Aware Language Model for Virtual Assistants
    Mandana Saebi, Ernest Pusateri, Aaksha Meghawat, Christophe Van Gysel
    http://arxiv.org/abs/2106.11292v1
    • [cs.CL]Ad Text Classification with Transformer-Based Natural Language Processing Methods
    Umut Özdil, Büşra Arslan, D. Emre Taşar, Gökçe Polat, Şükrü Ozan
    http://arxiv.org/abs/2106.10899v1
    • [cs.CL]ArgFuse: A Weakly-Supervised Framework for Document-Level Event Argument Aggregation
    Debanjana Kar, Sudeshna Sarkar, Pawan Goyal
    http://arxiv.org/abs/2106.10862v1
    • [cs.CL]CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction
    Tao Chen, Haizhou Shi, Siliang Tang, Zhigang Chen, Fei Wu, Yueting Zhuang
    http://arxiv.org/abs/2106.10855v1
    • [cs.CL]CPM-2: Large-scale Cost-effective Pre-trained Language Models
    Zhengyan Zhang, Yuxian Gu, Xu Han, Shengqi Chen, Chaojun Xiao, Zhenbo Sun, Yuan Yao, Fanchao Qi, Jian Guan, Pei Ke, Yanzheng Cai, Guoyang Zeng, Zhixing Tan, Zhiyuan Liu, Minlie Huang, Wentao Han, Yang Liu, Xiaoyan Zhu, Maosong Sun
    http://arxiv.org/abs/2106.10715v1
    • [cs.CL]Calliar: An Online Handwritten Dataset for Arabic Calligraphy
    Zaid Alyafeai, Maged S. Al-shaibani, Mustafa Ghaleb, Yousif Ahmed Al-Wajih
    http://arxiv.org/abs/2106.10745v1
    • [cs.CL]Challenges in Translation of Emotions in Multilingual User-Generated Content: Twitter as a Case Study
    Hadeel Saadany, Constantin Orasan, Rocio Caro Quintana, Felix do Carmo, Leonardo Zilio
    http://arxiv.org/abs/2106.10719v1
    • [cs.CL]Conversational Agents in Software Engineering: Survey, Taxonomy and Challenges
    Quim Motger, Xavier Franch, Jordi Marco
    http://arxiv.org/abs/2106.10901v1
    • [cs.CL]Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ?
    Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar
    http://arxiv.org/abs/2106.10622v1
    • [cs.CL]Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification
    Yada Pruksachatkun, Satyapriya Krishna, Jwala Dhamala, Rahul Gupta, Kai-Wei Chang
    http://arxiv.org/abs/2106.10826v1
    • [cs.CL]Empower Distantly Supervised Relation Extraction with Collaborative Adversarial Training
    Tao Chen, Haochen Shi, Liyuan Liu, Siliang Tang, Jian Shao, Zhigang Chen, Yueting Zhuang
    http://arxiv.org/abs/2106.10835v1
    • [cs.CL]Enhancing Question Generation with Commonsense Knowledge
    Xin Jia, Hao Wang, Dawei Yin, Yunfang Wu
    http://arxiv.org/abs/2106.10454v1
    • [cs.CL]Explicit Interaction Network for Aspect Sentiment Triplet Extraction
    Peiyi Wang, Lianzhe Huang, Tianyu Liu, Damai Dai, Runxin Xu, Houfeng Wang, Baobao Chang, Zhifang Sui
    http://arxiv.org/abs/2106.11148v1
    • [cs.CL]Extractive approach for text summarisation using graphs
    Kastriot Kadriu, Milenko Obradovic
    http://arxiv.org/abs/2106.10955v1
    • [cs.CL]Hybrid approach to detecting symptoms of depression in social media entries
    Agnieszka Wołk, Karol Chlasta, Paweł Holas
    http://arxiv.org/abs/2106.10485v1
    • [cs.CL]Iterative Network Pruning with Uncertainty Regularization for Lifelong Sentiment Classification
    Binzong Geng, Min Yang, Fajie Yuan, Shupeng Wang, Xiang Ao, Ruifeng Xu
    http://arxiv.org/abs/2106.11197v1
    • [cs.CL]JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
    Pei Ke, Haozhe Ji, Yu Ran, Xin Cui, Liwei Wang, Linfeng Song, Xiaoyan Zhu, Minlie Huang
    http://arxiv.org/abs/2106.10502v1
    • [cs.CL]Learning to Rank Question Answer Pairs with Bilateral Contrastive Data Augmentation
    Yang Deng, Wenxuan Zhang, Wai Lam
    http://arxiv.org/abs/2106.11096v1
    • [cs.CL]Multi-Pair Text Style Transfer on Unbalanced Data
    Xing Han, Jessica Lundin
    http://arxiv.org/abs/2106.10608v1
    • [cs.CL]Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis
    Bowen Xing, Ivor W. Tsang
    http://arxiv.org/abs/2106.10816v1
    • [cs.CL]Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence Modeling
    Hongyu Gong, Yun Tang, Juan Pino, Xian Li
    http://arxiv.org/abs/2106.10840v1
    • [cs.CL]Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets
    Irene Solaiman, Christy Dennison
    http://arxiv.org/abs/2106.10328v1
    • [cs.CL]ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction
    Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok Popat, Tomas Pfister
    http://arxiv.org/abs/2106.10786v1
    • [cs.CL]STEP-EZ: Syntax Tree guided semantic ExPlanation for Explainable Zero-shot modeling of clinical depression symptoms from text
    Nawshad Farruque, Randy Goebel, Osmar Zaiane, Sudhakar Sivapalan
    http://arxiv.org/abs/2106.10928v1
    • [cs.CL]Self-Calibrating Neural-Probabilistic Model for Authorship Verification Under Covariate Shift
    Benedikt Boenninghoff, Dorothea Kolossa, Robert M. Nickel
    http://arxiv.org/abs/2106.11196v1
    • [cs.CL]Transformers for Headline Selection for Russian News Clusters
    Pavel Voropaev, Olga Sopilnyak
    http://arxiv.org/abs/2106.10487v1
    • [cs.CL]TweeNLP: A Twitter Exploration Portal for Natural Language Processing
    Viraj Shah, Shruti Singh, Mayank Singh
    http://arxiv.org/abs/2106.10512v1
    • [cs.CR]Non-parametric Differentially Private Confidence Intervals for the Median
    Joerg Drechsler, Ira Globus-Harris, Audra McMillan, Jayshree Sarathy, Adam Smith
    http://arxiv.org/abs/2106.10333v1
    • [cs.CR]Privacy-preserving Publication and Sharing of COVID-19 Pandemic Data
    Dong Wang, Fang Liu
    http://arxiv.org/abs/2106.10339v1
    • [cs.CV]3D Object Detection for Autonomous Driving: A Survey
    Rui Qian, Xin Lai, Xirong Li
    http://arxiv.org/abs/2106.10823v1
    • [cs.CV]3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching
    Avinash Sharma, Radu Horaud, Diana Mateus
    http://arxiv.org/abs/2106.11166v1
    • [cs.CV]A system of vision sensor based deep neural networks for complex driving scene analysis in support of crash risk assessment and prevention
    Muhammad Monjurul Karim, Yu Li, Ruwen Qin, Zhaozheng Yin
    http://arxiv.org/abs/2106.10319v1
    • [cs.CV]AdaZoom: Adaptive Zoom Network for Multi-Scale Object Detection in Large Scenes
    Jingtao Xu, Yali Li, Shengjin Wang
    http://arxiv.org/abs/2106.10409v1
    • [cs.CV]Adversarial Manifold Matching via Deep Metric Learning for Generative Modeling
    Mengyu Dai, Haibin Hang
    http://arxiv.org/abs/2106.10777v1
    • [cs.CV]Affect-driven Engagement Measurement from Videos
    Ali Abedi, Shehroz Khan
    http://arxiv.org/abs/2106.10882v1
    • [cs.CV]An End-to-End Khmer Optical Character Recognition using Sequence-to-Sequence with Attention
    Rina Buoy, Sokchea Kor, Nguonly Taing
    http://arxiv.org/abs/2106.10875v1
    • [cs.CV]Attack to Fool and Explain Deep Networks
    Naveed Akhtar, Muhammad A. A. K. Jalwana, Mohammed Bennamoun, Ajmal Mian
    http://arxiv.org/abs/2106.10606v1
    • [cs.CV]Attend What You Need: Motion-Appearance Synergistic Networks for Video Question Answering
    Ahjeong Seo, Gi-Cheon Kang, Joonhan Park, Byoung-Tak Zhang
    http://arxiv.org/abs/2106.10446v1
    • [cs.CV]Augmented 2D-TAN: A Two-stage Approach for Human-centric Spatio-Temporal Video Grounding
    Chaolei Tan, Zihang Lin, Jian-Fang Hu, Xiang Li, Wei-Shi Zheng
    http://arxiv.org/abs/2106.10634v1
    • [cs.CV]Automated Deepfake Detection
    Ping Liu
    http://arxiv.org/abs/2106.10705v1
    • [cs.CV]Automatic Plant Cover Estimation with CNNs Automatic Plant Cover Estimation with Convolutional Neural Networks
    Matthias Körschens, Paul Bodesheim, Christine Römermann, Solveig Franziska Bucher, Mirco Migliavacca, Josephine Ulrich, Joachim Denzler
    http://arxiv.org/abs/2106.11154v1
    • [cs.CV]CAMERAS: Enhanced Resolution And Sanity preserving Class Activation Mapping for image saliency
    Mohammad A. A. K. Jalwana, Naveed Akhtar, Mohammed Bennamoun, Ajmal Mian
    http://arxiv.org/abs/2106.10649v1
    • [cs.CV]CLIP2Video: Mastering Video-Text Retrieval via Image CLIP
    Han Fang, Pengfei Xiong, Luhui Xu, Yu Chen
    http://arxiv.org/abs/2106.11097v1
    • [cs.CV]CUDA-GR: Controllable Unsupervised Domain Adaptation for Gaze Redirection
    Swati Jindal, Xin Eric Wang
    http://arxiv.org/abs/2106.10852v1
    • [cs.CV]Can poachers find animals from public camera trap images?
    Sara Beery, Elizabeth Bondi
    http://arxiv.org/abs/2106.11236v1
    • [cs.CV]CenterAtt: Fast 2-stage Center Attention Network
    Jianyun Xu, Xin Tang, Jian Dou, Xu Shu, Yushi Zhu
    http://arxiv.org/abs/2106.10493v1
    • [cs.CV]CompConv: A Compact Convolution Module for Efficient Feature Learning
    Chen Zhang, Yinghao Xu, Yujun Shen
    http://arxiv.org/abs/2106.10486v1
    • [cs.CV]Confidence-Guided Radiology Report Generation
    Yixin Wang, Zihao Lin, Jiang Tian, zhongchao shi, Yang Zhang, Jianping Fan, Zhiqiang He
    http://arxiv.org/abs/2106.10887v1
    • [cs.CV]Crop-Transform-Paste: Self-Supervised Learning for Visual Tracking
    Xin Li, Wenjie Pei, Zikun Zhou, Zhenyu He, Huchuan Lu, Ming-Hsuan Yang
    http://arxiv.org/abs/2106.10900v1
    • [cs.CV]Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification
    Chenyu Guo, Jiyang Xie, Kongming Liang, Xian Sun, Zhanyu Ma
    http://arxiv.org/abs/2106.10920v1
    • [cs.CV]Delving into the pixels of adversarial samples
    Blerta Lindqvist
    http://arxiv.org/abs/2106.10996v1
    • [cs.CV]DiGS : Divergence guided shape implicit neural representation for unoriented point clouds
    Yizhak Ben-Shabat, Chamin Hewa Koneputugodage, Stephen Gould
    http://arxiv.org/abs/2106.10811v1
    • [cs.CV]Distilling effective supervision for robust medical image segmentation with noisy labels
    Jialin Shi, Ji Wu
    http://arxiv.org/abs/2106.11099v1
    • [cs.CV]Dynamical Deep Generative Latent Modeling of 3D Skeletal Motion
    Amirreza Farnoosh, Sarah Ostadabbas
    http://arxiv.org/abs/2106.10393v1
    • [cs.CV]Exploring Semantic Relationships for Unpaired Image Captioning
    Fenglin Liu, Meng Gao, Tianhao Zhang, Yuexian Zou
    http://arxiv.org/abs/2106.10658v1
    • [cs.CV]Exploring Vision Transformers for Fine-grained Classification
    Marcos V. Conde, Kerem Turgutlu
    http://arxiv.org/abs/2106.10587v1
    • [cs.CV]Exploring Visual Context for Weakly Supervised Person Search
    Yichao Yan, Jinpeng Li, Shengcai Liao, Jie Qin, Bingbing Ni, Xiaokang Yang, Ling Shao
    http://arxiv.org/abs/2106.10506v1
    • [cs.CV]FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild
    Yiming Lin, Jie Shen, Yujiang Wang, Maja Pantic
    http://arxiv.org/abs/2106.11145v1
    • [cs.CV]Fast Simultaneous Gravitational Alignment of Multiple Point Sets
    Vladislav Golyanik, Soshi Shimada, Christian Theobalt
    http://arxiv.org/abs/2106.11308v1
    • [cs.CV]FloorPP-Net: Reconstructing Floor Plans using Point Pillars for Scan-to-BIM
    Yijie Wu, Fan Xue
    http://arxiv.org/abs/2106.10635v1
    • [cs.CV]Hard hat wearing detection based on head keypoint localization
    Bartosz Wójcik, Mateusz Żarski, Kamil Książek, Jarosław Adam Miszczak, Mirosław Jan Skibniewski
    http://arxiv.org/abs/2106.10944v1
    • [cs.CV]Humble Teachers Teach Better Students for Semi-Supervised Object Detection
    Yihe Tang, Weifeng Chen, Yijun Luo, Yuting Zhang
    http://arxiv.org/abs/2106.10456v1
    • [cs.CV]Informative Class Activation Maps
    Zhenyue Qin, Dongwoo Kim, Tom Gedeon
    http://arxiv.org/abs/2106.10472v1
    • [cs.CV]Interactive Object Segmentation with Dynamic Click Transform
    Chun-Tse Lin, Wei-Chih Tu, Chih-Ting Liu, Shao-Yi Chien
    http://arxiv.org/abs/2106.10465v1
    • [cs.CV]Interpretable Face Manipulation Detection via Feature Whitening
    Yingying Hua, Daichi Zhang, Pengju Wang, Shiming Ge
    http://arxiv.org/abs/2106.10834v1
    • [cs.CV]Interventional Video Grounding with Dual Contrastive Learning
    Guoshun Nan, Rui Qiao, Yao Xiao, Jun Liu, Sicong Leng, Hao Zhang, Wei Lu
    http://arxiv.org/abs/2106.11013v1
    • [cs.CV]Knowledge Distillation via Instance-level Sequence Learning
    Haoran Zhao, Xin Sun, Junyu Dong, Zihe Dong, Qiong Li
    http://arxiv.org/abs/2106.10885v1
    • [cs.CV]Large-scale image segmentation based on distributed clustering algorithms
    Ran Lu, Aleksandar Zlateski, H. Sebastian Seung
    http://arxiv.org/abs/2106.10795v1
    • [cs.CV]Learning to Track Object Position through Occlusion
    Satyaki Chakraborty, Martial Hebert
    http://arxiv.org/abs/2106.10766v1
    • [cs.CV]Low-Power Multi-Camera Object Re-Identification using Hierarchical Neural Networks
    Abhinav Goel, Caleb Tung, Xiao Hu, Haobo Wang, James C. Davis, George K. Thiruvathukal, Yung-Hsiang Lu
    http://arxiv.org/abs/2106.10588v1
    • [cs.CV]MSN: Efficient Online Mask Selection Network for Video Instance Segmentation
    Vidit Goel, Jiachen Li, Shubhika Garg, Harsh Maheshwari, Humphrey Shi
    http://arxiv.org/abs/2106.10452v1
    • [cs.CV]Mobile Sensing for Multipurpose Applications in Transportation
    Armstrong Aboah, Michael Boeding, Yaw Adu-Gyamfi
    http://arxiv.org/abs/2106.10733v1
    • [cs.CV]More than Encoder: Introducing Transformer Decoder to Upsample
    Yijiang Li, Wentian Cai, Ying Gao, Xiping Hu
    http://arxiv.org/abs/2106.10637v1
    • [cs.CV]Moving in a 360 World: Synthesizing Panoramic Parallaxes from a Single Panorama
    Ching-Yu Hsu, Cheng Sun, Hwann-Tzong Chen
    http://arxiv.org/abs/2106.10859v1
    • [cs.CV]Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering
    Jie Xu, Yazhou Ren, Huayi Tang, Xiaorong Pu, Xiaofeng Zhu, Ming Zeng, Lifang He
    http://arxiv.org/abs/2106.11232v1
    • [cs.CV]Multiple Object Tracking with Mixture Density Networks for Trajectory Estimation
    Andreu Girbau, Xavier Giró-i-Nieto, Ignasi Rius, Ferran Marqués
    http://arxiv.org/abs/2106.10950v1
    • [cs.CV]Neighborhood Contrastive Learning for Novel Class Discovery
    Zhun Zhong, Enrico Fini, Subhankar Roy, Zhiming Luo, Elisa Ricci, Nicu Sebe
    http://arxiv.org/abs/2106.10731v1
    • [cs.CV]NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction
    Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, Wenping Wang
    http://arxiv.org/abs/2106.10689v1
    • [cs.CV]Neural Marching Cubes
    Zhiqin Chen, Hao Zhang
    http://arxiv.org/abs/2106.11272v1
    • [cs.CV]Neural Network Facial Authentication for Public Electric Vehicle Charging Station
    Muhamad Amin Husni Abdul Haris, Sin Liang Lim
    http://arxiv.org/abs/2106.10432v1
    • [cs.CV]OadTR: Online Action Detection with Transformers
    Xiang Wang, Shiwei Zhang, Zhiwu Qing, Yuanjie Shao, Zhengrong Zuo, Changxin Gao, Nong Sang
    http://arxiv.org/abs/2106.11149v1
    • [cs.CV]Obstacle Detection for BVLOS Drones
    Jan Moros Esteban
    http://arxiv.org/abs/2106.11098v1
    • [cs.CV]One Million Scenes for Autonomous Driving: ONCE Dataset
    Jiageng Mao, Minzhe Niu, Chenhan Jiang, Hanxue Liang, Xiaodan Liang, Yamin Li, Chaoqiang Ye, Wei Zhang, Zhenguo Li, Jie Yu, Hang Xu, Chunjing Xu
    http://arxiv.org/abs/2106.11037v1
    • [cs.CV]PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging
    Yuwei Li, Minye Wu, Yuyao Zhang, Lan Xu, Jingyi Yu
    http://arxiv.org/abs/2106.10893v1
    • [cs.CV]Place recognition survey: An update on deep learning approaches
    Tiago Barros, Ricardo Pereira, Luís Garrote, Cristiano Premebida, Urbano J. Nunes
    http://arxiv.org/abs/2106.10458v1
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    Pranesh Kulkarni, Atharva Karwande, Tejas Kolhe, Soham Kamble, Akshay Joshi, Medha Wyawahare
    http://arxiv.org/abs/2106.10698v1
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    Yang Tan, Yang Li, Shao-Lun Huang
    http://arxiv.org/abs/2106.10479v1
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    Jiaming Zhang, Jitao Sang, Qi Yi, Huiwen Dong, Jian Yu
    http://arxiv.org/abs/2106.10989v1
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    Tianfei Zhou, Liulei Li, Gustav Bredell, Jianwu Li, Ender Konukoglu
    http://arxiv.org/abs/2106.10686v1
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    Yaxiong Wang, Yunchao Wei, Xueming Qian, Li Zhu, Yi Yang
    http://arxiv.org/abs/2106.10601v1
    • [cs.CV]Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model via a Self-Supervised Contrastive Learning Method
    Haifeng Li, Yi Li, Guo Zhang, Ruoyun Liu, Haozhe Huang, Qing Zhu, Chao Tao
    http://arxiv.org/abs/2106.10605v1
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    Ayman Mukhaimar, Ruwan Tennakoon, Chow Yin Lai, Reza Hoseinnezhad, AlirezaBab-Hadiashar
    http://arxiv.org/abs/2106.10850v1
    • [cs.CV]SHREC 2021: Track on Skeleton-based Hand Gesture Recognition in the Wild
    Ariel Caputo, Andrea Giachetti, Simone Soso, Deborah Pintani, Andrea D’Eusanio, Stefano Pini, Guido Borghi, Alessandro Simoni, Roberto Vezzani, Rita Cucchiara, Andrea Ranieri, Franca Giannini, Katia Lupinetti, Marina Monti, Mehran Maghoumi, Joseph J. LaViola Jr, Minh-Quan Le, Hai-Dang Nguyen, Minh-Triet Tran
    http://arxiv.org/abs/2106.10980v1
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    Jianhua Han, Xiwen Liang, Hang Xu, Kai Chen, Lanqing Hong, Chaoqiang Ye, Wei Zhang, Zhenguo Li, Chunjing Xu, Xiaodan Liang
    http://arxiv.org/abs/2106.11118v1
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    Urtzi Otamendi, Iñigo Martinez, Marco Quartulli, Igor G. Olaizola, Elisabeth Viles, Werther Cambarau
    http://arxiv.org/abs/2106.10962v1
    • [cs.CV]Simple Distillation Baselines for Improving Small Self-supervised Models
    Jindong Gu, Wei Liu, Yonglong Tian
    http://arxiv.org/abs/2106.11304v1
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    Xiaohan Fei, Henry Wang, Xiangyu Zeng, Lin Lee Cheong, Meng Wang, Joseph Tighe
    http://arxiv.org/abs/2106.10335v1
    • [cs.CV]Solution for Large-scale Long-tailed Recognition with Noisy Labels
    Yuqiao Xian, Jia-Xin Zhuang, Fufu Yu
    http://arxiv.org/abs/2106.10683v1
    • [cs.CV]Structured Sparse R-CNN for Direct Scene Graph Generation
    Yao Teng, Limin Wang
    http://arxiv.org/abs/2106.10815v1
    • [cs.CV]Supervised learning for crop/weed classification based on color and texture features
    Faiza Mekhalfa, Fouad Yacef
    http://arxiv.org/abs/2106.10581v1
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    Pietro Mascagni, Deepak Alapatt, Alain Garcia, Nariaki Okamoto, Armine Vardazaryan, Guido Costamagna, Bernard Dallemagne, Nicolas Padoy
    http://arxiv.org/abs/2106.10916v1
    • [cs.CV]TCIC: Theme Concepts Learning Cross Language and Vision for Image Captioning
    Zhihao Fan, Zhongyu Wei, Siyuan Wang, Ruize Wang, Zejun Li, Haijun Shan, Xuanjing Huang
    http://arxiv.org/abs/2106.10936v1
    • [cs.CV]TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition
    Wenyuan Xue, Baosheng Yu, Wen Wang, Dacheng Tao, Qingyong Li
    http://arxiv.org/abs/2106.10598v1
    • [cs.CV]TNT: Text-Conditioned Network with Transductive Inference for Few-Shot Video Classification
    Andrés Villa, Juan-Manuel Perez-Rua, Vladimir Araujo, Juan Carlos Niebles, Victor Escorcia, Alvaro Soto
    http://arxiv.org/abs/2106.11173v1
    • [cs.CV]Tag, Copy or Predict: A Unified Weakly-Supervised Learning Framework for Visual Information Extraction using Sequences
    Jiapeng Wang, Tianwei Wang, Guozhi Tang, Lianwen Jin, Weihong Ma, Kai Ding, Yichao Huang
    http://arxiv.org/abs/2106.10681v1
    • [cs.CV]Temporal Early Exits for Efficient Video Object Detection
    Amin Sabet, Jonathon Hare, Bashir Al-Hashimi, Geoff V. Merrett
    http://arxiv.org/abs/2106.11208v1
    • [cs.CV]The Animal ID Problem: Continual Curation
    Charles V. Stewart, Jason R. Parham, Jason Holmberg, Tanya Y. Berger-Wolf
    http://arxiv.org/abs/2106.10377v1
    • [cs.CV]The Arm-Swing Is Discriminative in Video Gait Recognition for Athlete Re-Identification
    Yapkan Choi, Yeshwanth Napolean, Jan C. van Gemert
    http://arxiv.org/abs/2106.11280v1
    • [cs.CV]ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation
    Guoqiang Wei, Cuiling Lan, Wenjun Zeng, Zhibo Chen
    http://arxiv.org/abs/2106.10812v1
    • [cs.CV]TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?
    Michael S. Ryoo, AJ Piergiovanni, Anurag Arnab, Mostafa Dehghani, Anelia Angelova
    http://arxiv.org/abs/2106.11297v1
    • [cs.CV]Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes
    Hao Tang, Nicu Sebe
    http://arxiv.org/abs/2106.10876v1
    • [cs.CV]Towards Long-Form Video Understanding
    Chao-Yuan Wu, Philipp Krähenbühl
    http://arxiv.org/abs/2106.11310v1
    • [cs.CV]Towards Single Stage Weakly Supervised Semantic Segmentation
    Peri Akiva, Kristin Dana
    http://arxiv.org/abs/2106.10309v1
    • [cs.CV]Trainable Class Prototypes for Few-Shot Learning
    Jianyi Li, Guizhong Liu
    http://arxiv.org/abs/2106.10846v1
    • [cs.CV]Two-Stream Consensus Network: Submission to HACS Challenge 2021 Weakly-Supervised Learning Track
    Yuanhao Zhai, Le Wang, David Doermann, Junsong Yuan
    http://arxiv.org/abs/2106.10829v1
    • [cs.CV]Unbalanced Feature Transport for Exemplar-based Image Translation
    Fangneng Zhan, Yingchen Yu, Kaiwen Cui, Gongjie Zhang, Shijian Lu, Jianxiong Pan, Changgong Zhang, Feiying Ma, Xuansong Xie, Chunyan Miao
    http://arxiv.org/abs/2106.10482v1
    • [cs.CV]Understanding Object Dynamics for Interactive Image-to-Video Synthesis
    Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer
    http://arxiv.org/abs/2106.11303v1
    • [cs.CV]Unsupervised Deep Learning by Injecting Low-Rank and Sparse Priors
    Tomoya Sakai
    http://arxiv.org/abs/2106.10923v1
    • [cs.CV]VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning
    Hao Tan, Jie Lei, Thomas Wolf, Mohit Bansal
    http://arxiv.org/abs/2106.11250v1
    • [cs.CV]VQA-Aid: Visual Question Answering for Post-Disaster Damage Assessment and Analysis
    Argho Sarkar, Maryam Rahnemoonfar
    http://arxiv.org/abs/2106.10548v1
    • [cs.CV]Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net
    Tianrui Liu, Qingjie Meng, Jun-Jie Huang, Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz
    http://arxiv.org/abs/2106.10528v1
    • [cs.CV]Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations
    Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki, Michał Górszczak, Barbara Rychalska, Koryna Lewandowska, Tomasz Trzciński, Bartosz Zieliński
    http://arxiv.org/abs/2106.11054v1
    • [cs.CY]A Comparative Study of Online Disinformation and Offline Protests
    Jukka Ruohonen
    http://arxiv.org/abs/2106.11000v1
    • [cs.CY]Fostering Student Engagement in a Mobile Formative Assessment System for High-School Economics
    Fotis Lazarinis, Dimitris Kanellopoulos
    http://arxiv.org/abs/2106.10910v1
    • [cs.CY]Reassessing Measures for Press Freedom
    Jukka Ruohonen
    http://arxiv.org/abs/2106.10427v1
    • [cs.DB]A Generic Distributed Clustering Framework for Massive Data
    Pingyi Luo, Qiang Huang, Anthony K. H. Tung
    http://arxiv.org/abs/2106.10515v1
    • [cs.DB]Demonstration of Panda: A Weakly Supervised Entity Matching System
    Renzhi Wu, Prem Sakala, Peng Li, Xu Chu, Yeye He
    http://arxiv.org/abs/2106.10821v1
    • [cs.DC]Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication
    Gordon E. Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna
    http://arxiv.org/abs/2106.10499v1
    • [cs.DC]Jolteon and Ditto: Network-Adaptive Efficient Consensus with Asynchronous Fallback
    Rati Gelashvili, Lefteris Kokoris-Kogias, Alberto Sonnino, Alexander Spiegelman, Zhuolun Xiang
    http://arxiv.org/abs/2106.10362v1
    • [cs.DL]On predicting research grants productivity
    Jorge A. V. Tohalino, Diego R. Amancio
    http://arxiv.org/abs/2106.10700v1
    • [cs.DM]Abstract Geometrical Computation 11: Slanted Firing Squad Synchronisation on Signal Machines
    Jérôme Durand-Lose, Aurélien Emmanuel
    http://arxiv.org/abs/2106.11176v1
    • [cs.G 32ee T]Proceedings Eighteenth Conference on Theoretical Aspects of Rationality and Knowledge
    Joseph Halpern, Andrés Perea
    http://arxiv.org/abs/2106.10886v1
    • [cs.HC]Anticipatory Detection of Compulsive Body-focused Repetitive Behaviors with Wearables
    Benjamin Lucas Searle, Dimitris Spathis, Marios Constantinides, Daniele Quercia, Cecilia Mascolo
    http://arxiv.org/abs/2106.10970v1
    • [cs.IR]A Comprehensive Review on Non-Neural Networks Collaborative Filtering Recommendation Systems
    Carmel Wenga, Majirus Fansi, Sébastien Chabrier, Jean-Martial Mari, Alban Gabillon
    http://arxiv.org/abs/2106.10679v1
    • [cs.IR]BanditMF: Multi-Armed Bandit Based Matrix Factorization Recommender System
    Shenghao Xu
    http://arxiv.org/abs/2106.10898v1
    • [cs.IR]Computational Pronunciation Analysis in Sung Utterances
    Emir Demirel, Sven Ahlback, Simon Dixon
    http://arxiv.org/abs/2106.10977v1
    • [cs.IR]Context-Aware Legal Citation Recommendation using Deep Learning
    Zihan Huang, Charles Low, Mengqiu Teng, Hongyi Zhang, Daniel E. Ho, Mark S. Krass, Matthias Grabmair
    http://arxiv.org/abs/2106.10776v1
    • [cs.IR]Data Optimisation for a Deep Learning Recommender System
    Gustav Hertz, Sandhya Sachidanandan, Balázs Tóth, Emil S. Jørgensen, Martin Tegnér
    http://arxiv.org/abs/2106.11218v1
    • [cs.IR]DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation
    Yifan Wang, Suyao Tang, Yuntong Lei, Weiping Song, Sheng Wang, Ming Zhang
    http://arxiv.org/abs/2106.10879v1
    • [cs.IR]Leveraging Multiple Online Sources for Accurate Income Verification
    Chirag Mahapatra, Kedar Bellare
    http://arxiv.org/abs/2106.10547v1
    • [cs.IR]On Sampling Top-K Recommendation Evaluation
    Dong Li, Ruoming Jin, Jing Gao, Zhi Liu
    http://arxiv.org/abs/2106.10621v1
    • [cs.IR]Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
    Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis
    http://arxiv.org/abs/2106.11251v1
    • [cs.IT]Algorithm Unrolling for Massive Access via Deep Neural Network with Theoretical Guarantee
    Yandong Shi, Hayoung Choi, Yuanming Shi, Yong Zhou
    http://arxiv.org/abs/2106.10426v1
    • [cs.IT]Coded Faster-than-Nyquist Signaling for Short Packet Communications
    Emre Cerci, Adem Cicek, Enver Cavus, Ebrahim Bedeer, Halim Yanikomeroglu
    http://arxiv.org/abs/2106.10574v1
    • [cs.IT]Competitive MA-DRL for Transmit Power Pool Design in Semi-Grant-Free NOMA Systems
    Muhammad Fayaz, Wenqiang Yi, Yuanwei Liu, Arumugam Nallanathan
    http://arxiv.org/abs/2106.11190v1
    • [cs.IT]Deep Learning for Intelligent Wireless MAC: Exploiting Real Data Sampled on 2.4GHz Frequency Band
    Jiantao Xin, Wensen Xu, Yucheng Cai, Taotao Wang, Shengli Zhang, Peng Liu, Ziyang Guo, Jiajun Luo
    http://arxiv.org/abs/2106.10307v1
    • [cs.IT]Deep Learning-Based Active User Detection for Grant-free SCMA Systems
    Thushan Sivalingam, Samad Ali, Nurul Huda Mahmood, Nandana Rajatheva, Matti Latva-Aho
    http://arxiv.org/abs/2106.11198v1
    • [cs.IT]Deep Neural Network-Based Blind Multiple User Detection for Grant-free Multi-User Shared Access
    Thushan Sivalingam, Samad Ali, Nurul Huda Mahmood, Nandana Rajatheva, Matti Latva-Aho
    http://arxiv.org/abs/2106.11204v1
    • [cs.IT]Improved Private and Secure Distributed (Batch) Matrix Multiplication
    Jie Li, Camilla Hollanti
    http://arxiv.org/abs/2106.11214v1
    • [cs.IT]Infinite families of linear codes supporting more $t$-designs
    Qianqian Yan, Junling Zhou
    http://arxiv.org/abs/2106.10903v1
    • [cs.IT]Linear Codes Associated to Symmetric Determinantal Varieties: Even Rank Case
    Peter Beelen, Trygve Johnsen, Prasant Singh
    http://arxiv.org/abs/2106.11080v1
    • [cs.IT]ML and MAP Device Activity Detections for Grant-Free Massive Access in Multi-Cell Networks
    Dongdong Jiang, Ying Cui
    http://arxiv.org/abs/2106.10438v1
    • [cs.IT]Near-Optimal Pool Testing under Urgency Constraints
    Éric Brier, Megi Dervishi, Rémi Géraud-Stewart, David Naccache, Ofer Yifrach-Stav
    http://arxiv.org/abs/2106.10971v1
    • [cs.IT]On decoding of a specific type of self-dual codes
    Radinka Yorgova
    http://arxiv.org/abs/2106.11146v1
    • [cs.IT]On the Capacity-Achieving Input of Channels with Phase Quantization
    Neil Irwin Bernardo, Jingge Zhu, Jamie Evans
    http://arxiv.org/abs/2106.11007v1
    • [cs.IT]On the Ergodic Capacity of Reconfigurable Intelligent Surface (RIS)-Aided MIMO Channels
    Chongjun Ouyang, Sheng Wu, Chunxiao Jiang, Yuanwei Liu, Hongwen Yang
    http://arxiv.org/abs/2106.10444v1
    • [cs.IT]Performance Evaluation of Cooperative NOMA-based Improved Hybrid SWIPT Protocol
    Ahmed Al Amin, Soo Young Shin
    http://arxiv.org/abs/2106.10799v1
    • [cs.IT]Realizing Neural Decoder at the Edge with Ensembled BNN
    Devannagari Vikas, Nancy Nayak, Sheetal Kalyani
    http://arxiv.org/abs/2106.09925v1
    • [cs.IT]Spatial Covariance Matrix Reconstruction for DOA Estimation in Hybrid Massive MIMO Systems with Multiple Radio Frequency Chains
    Yinsheng Liu, Yiwei Yan, Li You, Wenji Wang, Hongtao Duan
    http://arxiv.org/abs/2106.10709v1
    • [cs.IT]Strong Singleton type upper bounds for linear insertion-deletion codes
    Hao Chen
    http://arxiv.org/abs/2106.10782v1
    • [cs.IT]Universal Rate-Distortion-Perception Representations for Lossy Compression
    George Zhang, Jingjing Qian, Jun Chen, Ashish Khisti
    http://arxiv.org/abs/2106.10311v1
    • [cs.IT]Wireless Communication Aided by Intelligent Reflecting Surface: Active or Passive?
    Changsheng You, Rui Zhang
    http://arxiv.org/abs/2106.10963v1
    • [cs.LG]A Game-Theoretic Taxonomy of Visual Concepts in DNNs
    Xu Cheng, Chuntung Chu, Yi Zheng, Jie Ren, Quanshi Zhang
    http://arxiv.org/abs/2106.10938v1
    • [cs.LG]A Max-Min Entropy Framework for Reinforcement Learning
    Seungyul Han, Youngchul Sung
    http://arxiv.org/abs/2106.10517v1
    • [cs.LG]A Unified View of Algorithms for Path Planning Using Probabilistic Inference on Factor Graphs
    Francesco A. N. Palmieri, Krishna R. Pattipati, Giovanni Di Gennaro, Giovanni Fioretti, Francesco Verolla, Amedeo Buonanno
    http://arxiv.org/abs/2106.10442v1
    • [cs.LG]A causal view on compositional data
    Elisabeth Ailer, Christian L. Müller, Niki Kilbertus
    http://arxiv.org/abs/2106.11234v1
    • [cs.LG]A compressive multi-kernel method for privacy-preserving machine learning
    Thee Chanyaswad, J. Morris Chang, S. Y. Kung
    http://arxiv.org/abs/2106.10671v1
    • [cs.LG]AOMD: An Analogy-aware Approach to Offensive Meme Detection on Social Media
    Lanyu Shang, Yang Zhang, Yuheng Zha, Yingxi Chen, Christina Youn, Dong Wang
    http://arxiv.org/abs/2106.11229v1
    • [cs.LG]Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling
    Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao
    http://arxiv.org/abs/2106.10566v1
    • [cs.LG]Active Learning for Deep Neural Networks on Edge Devices
    Yuya Senzaki, Christian Hamelain
    http://arxiv.org/abs/2106.10836v1
    • [cs.LG]Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem
    Jiaqi Ma, Junwei Deng, Qiaozhu Mei
    http://arxiv.org/abs/2106.10785v1
    • [cs.LG]Adversarial Examples Make Strong Poisons
    Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojtek Czaja, Tom Goldstein
    http://arxiv.org/abs/2106.10807v1
    • [cs.LG]Analytically Tractable Bayesian Deep Q-Learning
    Luong Ha, Nguyen, James-A. Goulet
    http://arxiv.org/abs/2106.11086v1
    • [cs.LG]Approximation capabilities of measure-preserving neural networks
    Aiqing Zhu, Pengzhan Jin, Yifa Tang
    http://arxiv.org/abs/2106.10911v1
    • [cs.LG]Attention-based Neural Network for Driving Environment Complexity Perception
    Ce Zhang, Azim Eskandarian, Xuelai Du
    http://arxiv.org/abs/2106.11277v1
    • [cs.LG]Bayesian inference of ODEs with Gaussian processes
    Pashupati Hegde, Çağatay Yıldız, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen
    http://arxiv.org/abs/2106.10905v1
    • [cs.LG]BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation
    Mingguo He, Zhewei Wei, Zengfeng Huang, Hongteng Xu
    http://arxiv.org/abs/2106.10994v1
    • [cs.LG]Better Training using Weight-Constrained Stochastic Dynamics
    Benedict Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos Storkey
    http://arxiv.org/abs/2106.10704v1
    • [cs.LG]Boosting Offline Reinforcement Learning with Residual Generative Modeling
    Hua Wei, Deheng Ye, Zhao Liu, Hao Wu, Bo Yuan, Qiang Fu, Wei Yang, Zhenhui, Li
    http://arxiv.org/abs/2106.10411v1
    • [cs.LG]Boundary Graph Neural Networks for 3D Simulations
    Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter
    http://arxiv.org/abs/2106.11299v1
    • [cs.LG]CD-SGD: Distributed Stochastic Gradient Descent with Compression and Delay Compensation
    Enda Yu, Dezun Dong, Yemao Xu, Shuo Ouyang, Xiangke Liao
    http://arxiv.org/abs/2106.10796v1
    • [cs.LG]Can contrastive learning avoid shortcut solutions?
    Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra
    http://arxiv.org/abs/2106.11230v1
    • [cs.LG]Cogradient Descent for Dependable Learning
    Runqi Wang, Baochang Zhang, Li’an Zhuo, Qixiang Ye, David Doermann
    http://arxiv.org/abs/2106.10617v1
    • [cs.LG]Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning
    Feihu Huang, Junyi Li, Heng Huang
    http://arxiv.org/abs/2106.11264v1
    • [cs.LG]Compressing Deep ODE-Nets using Basis Function Expansions
    Alejandro Queiruga, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney
    http://arxiv.org/abs/2106.10820v1
    • [cs.LG]Conditional Neural Relational Inference for Interacting Systems
    Joao A. Candido Ramos, Lionel Blondé, Stéphane Armand, Alexandros Kalousis
    http://arxiv.org/abs/2106.11083v1
    • [cs.LG]Contrastive Multi-Modal Clustering
    Jie Xu, Huayi Tang, Yazhou Ren, Xiaofeng Zhu, Lifang He
    http://arxiv.org/abs/2106.11193v1
    • [cs.LG]Corruption Robust Active Learning
    Yifang Chen, Simon S. Du, Kevin Jamieson
    http://arxiv.org/abs/2106.11220v1
    • [cs.LG]Decadal Forecasts with ResDMD: a Residual DMD Neural Network
    Eduardo Rodrigues, Bianca Zadrozny, Campbell Watson, David Gold
    http://arxiv.org/abs/2106.11111v1
    • [cs.LG]Deep Generative Learning via Schrödinger Bridge
    Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
    http://arxiv.org/abs/2106.10410v1
    • [cs.LG]Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand
    Frederik Boe Hüttel, Inon Peled, Filipe Rodrigues, Francisco C. Pereira
    http://arxiv.org/abs/2106.10940v1
    • [cs.LG]Dependency Structure Misspecification in Multi-Source Weak Supervision Models
    Salva Rühling Cachay, Benedikt Boecking, Artur Dubrawski
    http://arxiv.org/abs/2106.10302v1
    • [cs.LG]Does Optimal Source Task Performance Imply Optimal Pre-training for a Target Task?
    Steven Gutstein, Brent Lance, Sanjay Shakkottai
    http://arxiv.org/abs/2106.11174v1
    • [cs.LG]Effects of boundary conditions in fully convolutional networks for learning spatio-temporal dynamics
    Antonio Alguacil andr Gonçalves Pinto, Michael Bauerheim, Marc C. Jacob, Stéphane Moreau
    http://arxiv.org/abs/2106.11160v1
    • [cs.LG]EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization
    Ondrej Bohdal, Yongxin Yang, Timothy Hospedales
    http://arxiv.org/abs/2106.10575v1
    • [cs.LG]Fast PDN Impedance Prediction Using Deep Learning
    Ling Zhang, Jack Juang, Zurab Kiguradze, Bo Pu, Shuai Jin, Songping Wu, Zhiping Yang, Chulsoon Hwang
    http://arxiv.org/abs/2106.10693v1
    • [cs.LG]FedCM: Federated Learning with Client-level Momentum
    Jing Xu, Sen Wang, Liwei Wang, Andrew Chi-Chih Yao
    http://arxiv.org/abs/2106.10874v1
    • [cs.LG]FedXGBoost: Privacy-Preserving XGBoost for Federated Learning
    Nhan Khanh Le, Yang Liu, Quang Minh Nguyen, Qingchen Liu, Fangzhou Liu, Quanwei Cai, Sandra Hirche
    http://arxiv.org/abs/2106.10662v1
    • [cs.LG]Federated Learning with Positive and Unlabeled Data
    Xinyang Lin, Hanting Chen, Yixing Xu, Chao Xu, Xiaolin Gui, Yiping Deng, Yunhe Wang
    http://arxiv.org/abs/2106.10904v1
    • [cs.LG]Friendly Training: Neural Networks Can Adapt Data To Make Learning Easier
    Simone Marullo, Matteo Tiezzi, Marco Gori, Stefano Melacci
    http://arxiv.org/abs/2106.10974v1
    • [cs.LG]GRAND: Graph Neural Diffusion
    Benjamin Paul Chamberlain, James Rowbottom, Maria Gorinova, Stefan Webb, Emanuele Rossi, Michael M. Bronstein
    http://arxiv.org/abs/2106.10934v1
    • [cs.LG]Generalization in the Face of Adaptivity: A Bayesian Perspective
    Moshe Shenfeld, Katrina Ligett
    http://arxiv.org/abs/2106.10761v1
    • [cs.LG]Graceful Degradation and Related Fields
    Jack Dymond
    http://arxiv.org/abs/2106.11119v1
    • [cs.LG]Graph Attention Networks with LSTM-based Path Reweighting
    Jianpeng Chen, Yujing Wang, Ming Zeng, Zongyi Xiang, Yazhou Ren
    http://arxiv.org/abs/2106.10866v1
    • [cs.LG]Graph Neural Networks for Learning Real-Time Prices in Electricity Market
    Shaohui Liu, Chengyang Wu, Hao Zhu
    http://arxiv.org/abs/2106.10529v1
    • [cs.LG]GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction
    Lirong Wu, Haitao Lin, Zhangyang Gao, Cheng Tan, Stan. Z. Li
    http://arxiv.org/abs/2106.11133v1
    • [cs.LG]Group-Structured Adversarial Training
    Farzan Farnia, Amirali Aghazadeh, James Zou, David Tse
    http://arxiv.org/abs/2106.10324v1
    • [cs.LG]Heterogeneous Multi-task Learning with Expert Diversity
    Raquel Aoki, Frederick Tung, Gabriel L. Oliveira
    http://arxiv.org/abs/2106.10595v1
    • [cs.LG]How Do Adam and Training Strategies Help BNNs Optimization?
    Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng
    http://arxiv.org/abs/2106.11309v1
    • [cs.LG]Improving Compositional Generalization in Classification Tasks via Structure Annotations
    Juyong Kim, Pradeep Ravikumar, Joshua Ainslie, Santiago Ontañón
    http://arxiv.org/abs/2106.10434v1
    • [cs.LG]Improving Multi-Modal Learning with Uni-Modal Teachers
    Chenzhuang Du, Tingle Li, Yichen Liu, Zixin Wen, Tianyu Hua, Yue Wang, Hang Zhao
    http://arxiv.org/abs/2106.11059v1
    • [cs.LG]Is Shapley Value fair? Improving Client Selection for Mavericks in Federated Learning
    Jiyue Huang, Chi Hong, Lydia Y. Chen, Stefanie Roos
    http://arxiv.org/abs/2106.10734v1
    • [cs.LG]Learning Timestamp-Level Representations for Time Series with Hierarchical Contrastive Loss
    Zhihan Yue, Yujing Wang, Juanyong Duan, Tianmeng Yang, Congrui Huang, Bixiong Xu
    http://arxiv.org/abs/2106.10466v1
    • [cs.LG]Learning and Generalization in Overparameterized Normalizing Flows
    Kulin Shah, Amit Deshpande, Navin Goyal
    http://arxiv.org/abs/2106.10535v1
    • [cs.LG]Leveraging Conditional Generative Models in a General Explanation Framework of Classifier Decisions
    Martin Charachon, Paul-Henry Cournède, Céline Hudelot, Roberto Ardon
    http://arxiv.org/abs/2106.10947v1
    • [cs.LG]Leveraging Language to Learn Program Abstractions and Search Heuristics
    Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas
    http://arxiv.org/abs/2106.11053v1
    • [cs.LG]Lossy Compression for Lossless Prediction
    Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison
    http://arxiv.org/abs/2106.10800v1
    • [cs.LG]Low-rank Dictionary Learning for Unsupervised Feature Selection
    Mohsen Ghassemi Parsa, Hadi Zare, Mehdi Ghatee
    http://arxiv.org/abs/2106.11102v1
    • [cs.LG]Machine learning in the social and health sciences
    Anja K. Leist, Matthias Klee, Jung Hyun Kim, David H. Rehkopf, Stéphane P. A. Bordas, Graciela Muniz-Terrera, Sara Wade
    http://arxiv.org/abs/2106.10716v1
    • [cs.LG]Matrix Encoding Networks for Neural Combinatorial Optimization
    Yeong-Dae Kwon, Jinho Choo, Iljoo Yoon, Minah Park, Duwon Park, Youngjune Gwon
    http://arxiv.org/abs/2106.11113v1
    • [cs.LG]Memory Augmented Optimizers for Deep Learning
    Paul-Aymeric McRae, Prasanna Parthasarathi, Mahmoud Assran, Sarath Chandar
    http://arxiv.org/abs/2106.10708v1
    • [cs.LG]Multiplying Matrices Without Multiplying
    Davis Blalock, John Guttag
    http://arxiv.org/abs/2106.10860v1
    • [cs.LG]Multirate Training of Neural Networks
    Tiffany Vlaar, Benedict Leimkuhler
    http://arxiv.org/abs/2106.10771v1
    • [cs.LG]Multivariate Data Explanation by Jumping Emerging Patterns Visualization
    Mário Popolin Neto, Fernando V. Paulovich
    http://arxiv.org/abs/2106.11112v1
    • [cs.LG]Nearly Minimax Optimal Adversarial Imitation Learning with Known and Unknown Transitions
    Tian Xu, Ziniu Li, Yang Yu
    http://arxiv.org/abs/2106.10424v1
    • [cs.LG]Neural Controlled Differential Equations for Online Prediction Tasks
    James Morrill, Patrick Kidger, Lingyi Yang, Terry Lyons
    http://arxiv.org/abs/2106.11028v1
    • [cs.LG]Neural Network Classifier as Mutual Information Evaluator
    Zhenyue Qin, Dongwoo Kim, Tom Gedeon
    http://arxiv.org/abs/2106.10471v1
    • [cs.LG]Neural Spectral Marked Point Processes
    Shixiang Zhu, Haoyun Wang, Xiuyuan Cheng, Yao Xie
    http://arxiv.org/abs/2106.10773v1
    • [cs.LG]Neural network interpretability for forecasting of aggregated renewable generation
    Yucun Lu, Ilgiz Murzakhanov, Spyros Chatzivasileiadis
    http://arxiv.org/abs/2106.10476v1
    • [cs.LG]On Stein Variational Neural Network Ensembles
    Francesco D’Angelo, Vincent Fortuin, Florian Wenzel
    http://arxiv.org/abs/2106.10760v1
    • [cs.LG]On fine-tuning of Autoencoders for Fuzzy rule classifiers
    Rahul Kumar Sevakula, Nishchal Kumar Verma, Hisao Ishibuchi
    http://arxiv.org/abs/2106.11182v1
    • [cs.LG]On the Cryptographic Hardness of Learning Single Periodic Neurons
    Min Jae Song, Ilias Zadik, Joan Bruna
    http://arxiv.org/abs/2106.10744v1
    • [cs.LG]Open-set Label Noise Can Improve Robustness Against Inherent Label Noise
    Hongxin Wei, Lue Tao, Renchunzi Xie, Bo An
    http://arxiv.org/abs/2106.10891v1
    • [cs.LG]Opportunities and challenges in partitioning the graph measure space of real-world networks
    Máté Józsa, Alpár S. Lázár, Zsolt I. Lázár
    http://arxiv.org/abs/2106.10753v1
    • [cs.LG]OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
    Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
    http://arxiv.org/abs/2106.10783v1
    • [cs.LG]Optimal Strategies for Decision Theoretic Online Learning
    Yoav Freund
    http://arxiv.org/abs/2106.10717v1
    • [cs.LG]Practical Assessment of Generalization Performance Robustness for Deep Networks via Contrastive Examples
    Xuanyu Wu, Xuhong Li, Haoyi Xiong, Xiao Zhang, Siyu Huang, Dejing Dou
    http://arxiv.org/abs/2106.10653v1
    • [cs.LG]Prediction of the facial growth direction with Machine Learning methods
    Stanisław Kaźmierczak, Zofia Juszka, Piotr Fudalej, Jacek Mańdziuk
    http://arxiv.org/abs/2106.10464v1
    • [cs.LG]Prediction-Free, Real-Time Flexible Control of Tidal Lagoons through Proximal Policy Optimisation: A Case Study for the Swansea Lagoon
    Túlio Marcondes Moreira, Jackson Geraldo de Faria Jr, Pedro O. S. Vaz de Melo, Luiz Chaimowicz, Gilberto Medeiros-Ribeiro
    http://arxiv.org/abs/2106.10360v1
    • [cs.LG]QuaPy: A Python-Based Framework for Quantification
    Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani
    http://arxiv.org/abs/2106.11057v1
    • [cs.LG]Regularization is all you Need: Simple Neural Nets can Excel on Tabular Data
    Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka
    http://arxiv.org/abs/2106.11189v1
    • [cs.LG]Robust M-estimation-based Tensor Ring Completion: a Half-quadratic Minimization Approach
    Yicong He, George K. Atia
    http://arxiv.org/abs/2106.10422v1
    • [cs.LG]Robust Regression via Model Based Methods
    Armin Moharrer, Khashayar Kamran, Edmund Ye, Stratis Ioannidis
    http://arxiv.org/abs/2106.10759v1
    • [cs.LG]STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
    Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney
    http://arxiv.org/abs/2106.10435v1
    • [cs.LG]Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments
    Abdus Salam Azad, Edward Kim, Qiancheng Wu, Kimin Lee, Ion Stoica, Pieter Abbeel, Sanjit A. Seshia
    http://arxiv.org/abs/2106.10365v1
    • [cs.LG]Secure Distributed Training at Scale
    Eduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin
    http://arxiv.org/abs/2106.11257v1
    • [cs.LG]Semi-supervised Optimal Transport with Self-paced Ensemble for Cross-hospital Sepsis Early Detection
    Ruiqing Ding, Yu Zhou, Jie Xu, Yan Xie, Qiqiang Liang, He Ren, Yixuan Wang, Yanlin Chen, Leye Wang, Man Huang
    http://arxiv.org/abs/2106.10352v1
    • [cs.LG]Smooth Sequential Optimisation with Delayed Feedback
    Srivas Chennu, Jamie Martin, Puli Liyanagama, Phil Mohr
    http://arxiv.org/abs/2106.11294v1
    • [cs.LG]Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
    Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
    http://arxiv.org/abs/2106.10404v1
    • [cs.LG]Stability of Graph Convolutional Neural Networks to Stochastic Perturbations
    Zhan Gao, Elvin Isufi, Alejandro Ribeiro
    http://arxiv.org/abs/2106.10526v1
    • [cs.LG]TD-GEN: Graph Generation With Tree Decomposition
    Hamed Shirzad, Hossein Hajimirsadeghi, Amir H. Abdi, Greg Mori
    http://arxiv.org/abs/2106.10656v1
    • [cs.LG]Task Attended Meta-Learning for Few-Shot Learning
    Aroof Aimen, Sahil Sidheekh, Narayanan C. Krishnan
    http://arxiv.org/abs/2106.10642v1
    • [cs.LG]Teacher’s pet: understanding and mitigating biases in distillation
    Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
    http://arxiv.org/abs/2106.10494v1
    • [cs.LG]The Perils of Learning Before Optimizing
    Chris Cameron, Jason Hartford, Taylor Lundy, Kevin Leyton-Brown
    http://arxiv.org/abs/2106.10349v1
    • [cs.LG]TinyML: Analysis of Xtensa LX6 microprocessor for Neural Network Applications by ESP32 SoC
    Md Ziaul Haque Zim
    http://arxiv.org/abs/2106.10652v1
    • [cs.LG]Towards Better Shale Gas Production Forecasting Using Transfer Learning
    Omar S. Alolayan, Samuel J. Raymond, Justin B. Montgomery, John R. Williams
    http://arxiv.org/abs/2106.11051v1
    • [cs.LG]Towards a Query-Optimal and Time-Efficient Algorithm for Clustering with a Faulty Oracle
    Pan Peng, Jiapeng Zhang
    http://arxiv.org/abs/2106.10374v1
    • [cs.LG]Transfer Bayesian Meta-learning via Weighted Free Energy Minimization
    Yunchuan Zhang, Sharu Theresa Jose, Osvaldo Simeone
    http://arxiv.org/abs/2106.10711v1
    • [cs.LG]Variance-Dependent Best Arm Identification
    Pinyan Lu, Chao Tao, Xiaojin Zhang
    http://arxiv.org/abs/2106.10417v1
    • [cs.LG]Vehicle Trajectory Prediction in City-scale Road Networks using a Direction-based Sequence-to-Sequence Model with Spatiotemporal Attention Mechanisms
    Yuebing Liang, Zhan Zhao
    http://arxiv.org/abs/2106.11175v1
    • [cs.LG]iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
    Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Ehsan Abbasnejad, Reza Haffari
    http://arxiv.org/abs/2106.10784v1
    • [cs.LO]Defeasible Reasoning via Datalog$^\neg$
    Michael J. Maher
    http://arxiv.org/abs/2106.10946v1
    • [cs.MA]Curriculum-Driven Multi-Agent Learning and the Role of Implicit Communication in Teamwork
    Niko A. Grupen, Daniel D. Lee, Bart Selman
    http://arxiv.org/abs/2106.11156v1
    • [cs.MM]Multi-Contextual Design of Convolutional Neural Network for Steganalysis
    Brijesh Singh, Arijit Sur, Pinaki Mitra
    http://arxiv.org/abs/2106.10430v1
    • [cs.NE]The Role of Evolution in Machine Intelligence
    Awni Hannun
    http://arxiv.org/abs/2106.11151v1
    • [cs.PF]AutoTune: Improving End-to-end Performance and Resource Efficiency for Microservice Applications
    Michael Alan Chang, Aurojit Panda, Hantao Wang, Yuancheng Tsai, Rahul Balakrishnan, Scott Shenker
    http://arxiv.org/abs/2106.10334v1
    • [cs.RO]Domain and Modality Gaps for LiDAR-based Person Detection on Mobile Robots
    Dan Jia, Alexander Hermans, Bastian Leibe
    http://arxiv.org/abs/2106.11239v1
    • [cs.RO]Exoskeleton-Based Multimodal Action and Movement Recognition: Identifying and Developing the Optimal Boosted Learning Approach
    Nirmalya Thakur, Chia Y. Han
    http://arxiv.org/abs/2106.10331v1
    • [cs.RO]Grasping Benchmarks: Normalizing for Object Size & Approximating Hand Workspaces
    John Morrow, Nuha Nishat, Joshua Campbell, Ravi Balasubramanian, Cindy Grimm
    http://arxiv.org/abs/2106.10402v1
    • [cs.RO]Guiding vector fields in Paparazzi autopilot
    Hector Garcia de Marina, Murat Bronz, Gautier Hattenberger
    http://arxiv.org/abs/2106.10680v1
    • [cs.RO]HapFIC: An Adaptive Force/Position Controller for Safe Environment Interaction in Articulated Systems
    Carlo Tiseo, Wolfgang Merkt, Keyhan Kouhkiloui Babarahmati, Wouter Wolfslag, Ioannis Havoutis, Sethu Vijayakumar, Michael Mistry
    http://arxiv.org/abs/2106.10648v1
    • [cs.RO]High-level Features for Resource Economy and Fast Learning in Skill Transfer
    Alper Ahmetoglu, Emre Ugur, Minoru Asada, Erhan Oztop
    http://arxiv.org/abs/2106.10354v1
    • [cs.RO]Image-guided Breast Biopsy of MRI-visible Lesions with a Hand-mounted Motorised Needle Steering Tool
    Marta Lagomarsino, Vincent Groenhuis, Maura Casadio, Marcel K. Welleweerd, Francoise J. Siepel, Stefano Stramigioli
    http://arxiv.org/abs/2106.10672v1
    • [cs.RO]Investigating the role of educational robotics in formal mathematics education: the case of geometry for 15-year-old students
    Jérôme Brender, Laila El-Hamamsy, Barbara Bruno, Frédérique Chessel-Lazzarotto, Jessica Dehler Zufferey, Francesco Mondada
    http://arxiv.org/abs/2106.10925v1
    • [cs.RO]On the Importance of Environments in Human-Robot Coordination
    Matthew C. Fontaine, Ya-Chuan Hsu, Yulun Zhang, Bryon Tjakana, Stefanos Nikolaidis
    http://arxiv.org/abs/2106.10853v1
    • [cs.RO]PHYSFRAME: Type Checking Physical Frames of Reference for Robotic Systems
    Sayali Kate, Michael Chinn, Hongjun Choi, Xiangyu Zhang, Sebastian Elbaum
    http://arxiv.org/abs/2106.11266v1
    • [cs.RO]Sample Efficient Social Navigation Using Inverse Reinforcement Learning
    Bobak H. Baghi, Gregory Dudek
    http://arxiv.org/abs/2106.10318v1
    • [cs.RO]Towards a Framework for Changing-Contact Robot Manipulation
    Saif Sidhik, Mohan Sridharan, Dirk Ruiken
    http://arxiv.org/abs/2106.10969v1
    • [cs.SD]Advances in Speech Vocoding for Text-to-Speech with Continuous Parameters
    Mohammed Salah Al-Radhi, Tamás Gábor Csapó, Géza Németh
    http://arxiv.org/abs/2106.10481v1
    • [cs.SD]Affinity Mixup for Weakly Supervised Sound Event Detection
    Mohammad Rasool Izadi, Robert Stevenson, Laura N. Kloepper
    http://arxiv.org/abs/2106.11233v1
    • [cs.SD]EML Online Speech Activity Detection for the Fearless Steps Challenge Phase-III
    Omid Ghahabi, Volker Fischer
    http://arxiv.org/abs/2106.11075v1
    • [cs.SE]GLIB: Towards Automated Test Oracle for Graphically-Rich Applications
    Ke Chen, Yufei Li, Yingfeng Chen, Changjie Fan, Zhipeng Hu, Wei Yang
    http://arxiv.org/abs/2106.10507v1
    • [cs.SI]Dynamics of Disruption in Science and Technology
    Michael Park, Erin Leahey, Russell Funk
    http://arxiv.org/abs/2106.11184v1
    • [cs.SI]FauxWard: A Graph Neural Network Approach to Fauxtography Detection Using Social Media Comments
    Lanyu Shang, Yang Zhang, Daniel Zhang, Dong Wang
    http://arxiv.org/abs/2106.11227v1
    • [cs.SI]Finding critical edges in complex networks through local information
    En-Yu Yu, Yan Fu, Jun-Lin Zhou, Hong-Liang Sun, Duan-Bing Chen
    http://arxiv.org/abs/2106.10420v1
    • [cs.SI]Flipping Stance: Social Influence on Bot’s and Non Bot’s COVID Vaccine Stance
    Lynnette Hui Xian Ng, Kathleen Carley
    http://arxiv.org/abs/2106.11076v1
    • [cs.SI]Large-Scale Network Embedding in Apache Spark
    Wenqing Lin
    http://arxiv.org/abs/2106.10620v1
    • [cs.SI]MetaDetector: Meta Event Knowledge Transfer for Fake News Detection
    Yasan Ding, Bin Guo, Yan Liu, Yunji Liang, Haocheng Shen, Zhiwen Yu
    http://arxiv.org/abs/2106.11177v1
    • [cs.SI]Overall Behavioural Index (OBI) For Measuring Segregation
    Rahul Goel, Rajesh Sharma, Anto Aasa
    http://arxiv.org/abs/2106.10676v1
    • [cs.SI]Predicting Critical Nodes in Temporal Networks by Dynamic Graph Convolutional Networks
    En-Yu Yu, Yan Fu, Jun-Lin Zhou, Hong-Liang Sun, Duan-Bing Chen
    http://arxiv.org/abs/2106.10419v1
    • [cs.SI]Pricing Social Visibility Service in Online Social Networks: Modeling and Algorithms
    Shiyuan Zheng, Hong Xie, John C. S. Lui
    http://arxiv.org/abs/2106.10473v1
    • [cs.SI]Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd
    Henry H. Wu, Ryan J. Gallagher, Thayer Alshaabi, Jane L. Adams, Joshua R. Minot, Michael V. Arnold, Brooke Foucault Welles, Randall Harp, Peter Sheridan Dodds, Christopher M. Danforth
    http://arxiv.org/abs/2106.10281v1
    • [cs.SI]Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling
    Qi Yang, Aleksandr Farseev, Andrey Filchenkov
    http://arxiv.org/abs/2106.10673v1
    • [econ.EM]On Testing Equal Conditional Predictive Ability Under Measurement Error
    Yannick Hoga, Timo Dimitriadis
    http://arxiv.org/abs/2106.11104v1
    • [eess.AS]GPLA-12: An Acoustic Signal Dataset of Gas Pipeline Leakage
    Jie Li, Lizhong Yao
    http://arxiv.org/abs/2106.10277v1
    • [eess.AS]Non-native English lexicon creation for bilingual speech synthesis
    Arun Baby, Pranav Jawale, Saranya Vinnaitherthan, Sumukh Badam, Nagaraj Adiga, Sharath Adavanne
    http://arxiv.org/abs/2106.10870v1
    • [eess.AS]UniTTS: Residual Learning of Unified Embedding Space for Speech Style Control
    Minsu Kang, Sungjae Kim, Injung Kim
    http://arxiv.org/abs/2106.11171v1
    • [eess.IV]Applying VertexShuffle Toward 360-Degree Video Super-Resolution on Focused-Icosahedral-Mesh
    Na Li, Yao Liu
    http://arxiv.org/abs/2106.11253v1
    • [eess.IV]Brain tumor grade classification Using LSTM Neural Networks with Domain Pre-Transforms
    Maedeh Sadat Fasihi, Wasfy B. Mikhael
    http://arxiv.org/abs/2106.10889v1
    • [eess.IV]CataNet: Predicting remaining cataract surgery duration
    Andrés Marafioti, Michel Hayoz, Mathias Gallardo, Pablo Márquez Neila, Sebastian Wolf, Martin Zinkernagel, Raphael Sznitman
    http://arxiv.org/abs/2106.11048v1
    • [eess.IV]Direct Reconstruction of Linear Parametric Images from Dynamic PET Using Nonlocal Deep Image Prior
    Kuang Gong, Ciprian Catana, Jinyi Qi, Quanzheng Li
    http://arxiv.org/abs/2106.10359v1
    • [eess.IV]Estimating MRI Image Quality via Image Reconstruction Uncertainty
    Richard Shaw, Carole H. Sudre, Sebastien Ourselin, M. Jorge Cardoso
    http://arxiv.org/abs/2106.10992v1
    • [eess.IV]Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation
    Nader Aldoj, Federico Biavati, Marc Dewey, Anja Hennemuth, Patrick Asbach, Ingolf Sack
    http://arxiv.org/abs/2106.11284v1
    • [eess.IV]Generative Model Adversarial Training for Deep Compressed Sensing
    Ashkan Esmaeili
    http://arxiv.org/abs/2106.10696v1
    • [eess.IV]Implementing a Detection System for COVID-19 based on Lung Ultrasound Imaging and Deep Learning
    Carlos Rojas-Azabache, Karen Vilca-Janampa, Renzo Guerrero-Huayta, Dennis Núñez-Fernández
    http://arxiv.org/abs/2106.10651v1
    • [eess.IV]Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
    Zeyu Gao, Jiangbo Shi, Xianli Zhang, Yang Li, Haichuan Zhang, Jialun Wu, Chunbao Wang, Deyu Meng, Chen Li
    http://arxiv.org/abs/2106.10641v1
    • [eess.IV]One-to-many Approach for Improving Super-Resolution
    Sieun Park, Eunho Lee
    http://arxiv.org/abs/2106.10437v1
    • [eess.IV]Reversible Colour Density Compression of Images using cGANs
    Arun Jose, Abraham Francis
    http://arxiv.org/abs/2106.10542v1
    • [eess.IV]Underwater Image Restoration via Contrastive Learning and a Real-world Dataset
    Junlin Han, Mehrdad Shoeiby, Tim Malthus, Elizabeth Botha, Janet Anstee, Saeed Anwar, Ran Wei, Mohammad Ali Armin, Hongdong Li, Lars Petersson
    http://arxiv.org/abs/2106.10718v1
    • [eess.SP]Active and Dynamic Beam Tracking UnderStochastic Mobility
    Nancy Ronquillo, Tara Javidi
    http://arxiv.org/abs/2106.11281v1
    • [eess.SP]EMG Signal Classification Using Reflection Coefficients and Extreme Value Machine
    Reza Bagherian Azhiri, Mohammad Esmaeili, Mohsen Jafarzadeh, Mehrdad Nourani
    http://arxiv.org/abs/2106.10561v1
    • [eess.SP]Electromagnetic Interference in RIS-Aided Communications
    Andrea De Jesus Torres, Luca Sanguinetti, Emil Björnson
    http://arxiv.org/abs/2106.11107v1
    • [eess.SP]Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification
    Michela C. Massi, Francesca Ieva
    http://arxiv.org/abs/2106.10633v1
    • [eess.SP]Machine Learning based optimization for interval uncertainty propagation with application to vibro-acoustic models
    Alice Cicirello, Filippo Giunta
    http://arxiv.org/abs/2106.11215v1
    • [eess.SP]Parallel frequency function-deep neural network for efficient complex broadband signal approximation
    Zhi Zeng, Pengpeng Shi, Fulei Ma, Peihan Qi
    http://arxiv.org/abs/2106.10401v1
    • [eess.SP]Signal Processing Based Deep Learning for Blind Symbol Decoding and Modulation Classification
    Samer Hanna, Chris Dick, Danijela Cabric
    http://arxiv.org/abs/2106.10543v1
    • [eess.SY]Brushless Motor Performance Optimization by Eagle Strategy with Firefly and PSO
    Appalabathula Venkatesh, Pradeepa H, Chidanandappa R, Shankar Nalinakshan, Jayasankar V N
    http://arxiv.org/abs/2106.11135v1
    • [eess.SY]DiffLoop: Tuning PID controllers by differentiating through the feedback loop
    Athindran Ramesh Kumar, Peter J. Ramadge
    http://arxiv.org/abs/2106.10516v1
    • [eess.SY]Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information
    Franck Djeumou, Ufuk Topcu
    http://arxiv.org/abs/2106.10533v1
    • [eess.SY]Minimizing Delay in Network Function Visualization with Quantum Computing
    Wenlu Xuan, Zhongqi Zhao, Lei Fan, Zhu Han
    http://arxiv.org/abs/2106.10707v1
    • [eess.SY]Parallel Statistical Model Checking for Safety Verification in Smart Grids
    T. Mancini, F. Mari, I. Melatti, I. Salvo, E. Tronci, J. K. Gruber, B. Hayes, M. Prodanovic, L. Elmegaard
    http://arxiv.org/abs/2106.10692v1
    • [math.NT]Solving the linear approximation problem
    Avraham Bourla
    http://arxiv.org/abs/2106.10712v1
    • [math.OC]Complexity-Free Generalization via Distributionally Robust Optimization
    Henry Lam, Yibo Zeng
    http://arxiv.org/abs/2106.11180v1
    • [math.OC]Distributed Picard Iteration: Application to Distributed EM and Distributed PCA
    Francisco L. Andrade, Mário A. T. Figueiredo, João Xavier
    http://arxiv.org/abs/2106.10665v1
    • [math.OC]QUBO transformation using Eigenvalue Decomposition
    Amit Verma, Mark Lewis
    http://arxiv.org/abs/2106.10532v1
    • [math.ST]Some smooth sequential empirical copula processes and their multiplier bootstraps under strong mixing
    Ivan Kojadinovic, Bingqing Yi
    http://arxiv.org/abs/2106.10726v1
    • [math.ST]Weighted Fractional Generalized Cumulative Past Entropy
    Suchandan Kayal
    http://arxiv.org/abs/2106.10312v1
    • [physics.chem-ph]Representations and Strategies for Transferable Machine Learning Models in Chemical Discovery
    Daniel R. Harper, Aditya Nandy, Naveen Arunachalam, Chenru Duan, Jon Paul Janet, Heather J. Kulik
    http://arxiv.org/abs/2106.10768v1
    • [physics.flu-dyn]Scientific multi-agent reinforcement learning for wall-models of turbulent flows
    H. Jane Bae, Petros Koumoutsakos
    http://arxiv.org/abs/2106.11144v1
    • [physics.optics]Fundamental bounds on the precision of iSCAT, COBRI and dark-field microscopy for 3D localization and mass photometry
    Jonathan Dong, Dante Maestre, Clara Conrad-Billroth, Thomas Juffmann
    http://arxiv.org/abs/2106.10758v1
    • [physics.soc-ph]Cumulative structure and path length in networks of knowledge
    P. G. J. Persoon
    http://arxiv.org/abs/2106.10480v1
    • [physics.soc-ph]Intersectional synergies: untangling irreducible effects of intersecting identities via information decomposition
    Thomas F. Varley
    http://arxiv.org/abs/2106.10338v1
    • [quant-ph]QFCNN: Quantum Fourier Convolutional Neural Network
    Feihong Shen, Jun Liu
    http://arxiv.org/abs/2106.10421v1
    • [quant-ph]Quantum Machine Learning: Fad or Future?
    Arhum Ishtiaq, Sara Mahmood
    http://arxiv.org/abs/2106.10714v1
    • [quant-ph]Rényi divergence inequalities via interpolation, with applications to generalised entropic uncertainty relations
    Alexander McKinlay
    http://arxiv.org/abs/2106.10415v1
    • [stat.AP]Bayesian decision theory for tree-based adaptive screening tests with an application to youth delinquency
    Chelsea Krantsevich, P. Richard Hahn, Yi Zheng, Charles Katz
    http://arxiv.org/abs/2106.10364v1
    • [stat.AP]Combined tests based on restricted mean time lost for competing risks data
    Jingjing Lyu, Yawen Hou, Zheng Chen
    http://arxiv.org/abs/2106.10624v1
    • [stat.AP]Dynamic prediction and analysis based on restricted mean survival time in survival analysis with nonproportional hazards
    Zijing Yang, Hongji Wu, Yawen Hou, Hao Yuan, Zheng Chen
    http://arxiv.org/abs/2106.10625v1
    • [stat.AP]Geographic and Racial Disparities in the Incidence of Low Birthweight in Pennsylvania
    Guangzi Song, Loni Philip Tabb, Harrison Quick
    http://arxiv.org/abs/2106.10571v1
    • [stat.AP]The Expected Value of Perfect Information for Risk Prediction Models
    Mohsen Sadatsafavi, Tae Yoon Lee, Paul Gustafson
    http://arxiv.org/abs/2106.10721v1
    • [stat.CO]Circuits for robust designs
    Roberto Fontana, Fabio Rapallo, Henry P. Wynn
    http://arxiv.org/abs/2106.11213v1
    • [stat.CO]Life-cycle assessment for flutter probability of a long-span suspension bridge based on field monitoring data
    Xiaolei Chu, Hung Nguyen Sinh, Wei Cui, Lin Zhao, Yaojun Ge
    http://arxiv.org/abs/2106.10694v1
    • [stat.ME]A generalized EMS algorithm for model selection with incomplete data
    Ping-Feng Xu, Lai-Xu Shang, Man-Lai Tang, Na Shan, Guoliang Tian
    http://arxiv.org/abs/2106.10983v1
    • [stat.ME]Bayesian inference for continuous-time hidden Markov models with an unknown number of states
    Yu Luo, David A. Stephens
    http://arxiv.org/abs/2106.10660v1
    • [stat.ME]Choosing the Estimand When Matching or Weighting in Observational Studies
    Noah Greifer, Elizabeth A. Stuart
    http://arxiv.org/abs/2106.10577v1
    • [stat.ME]Constrained randomization and statistical inference for multi-arm parallel cluster randomized controlled trials
    Yunji Zhou, Elizabeth L. Turner, Ryan A. Simmons, Fan Li
    http://arxiv.org/abs/2106.10720v1
    • [stat.ME]Discussion on Competition for Spatial Statistics for Large Datasets
    Roman Flury, Reinhard Furrer
    http://arxiv.org/abs/2106.10462v1
    • [stat.ME]Dynamic group testing to control and monitor disease progression in a population
    Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas Diggavi
    http://arxiv.org/abs/2106.10765v1
    • [stat.ME]Estimation of time-specific intervention effects on continuously distributed time-to-event outcomes by targeted maximum likelihood estimation
    Helene Charlotte Wiese Rytgaard, Frank Eriksson, Mark van der Laan
    http://arxiv.org/abs/2106.11009v1
    • [stat.ME]Fasano-Franceschini Test: an Implementation of a 2-Dimensional Kolmogorov-Smirnov test in R
    Elan Ness-Cohn, Rosemary Braun
    http://arxiv.org/abs/2106.10539v1
    • [stat.ME]Generalized Spatial and Spatiotemporal ARCH Models
    Philipp Otto, Wolfgang Schmid
    http://arxiv.org/abs/2106.10477v1
    • [stat.ME]On the bimodal Gumbel model with application to environmental data
    Cira E. G. Otiniano, Roberto Vila, Pedro C. Brom, Marcelo Bourguignon
    http://arxiv.org/abs/2106.10398v1
    • [stat.ME]Robust Hierarchical Modeling of Counts under Zero-inflation and Outliers
    Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
    http://arxiv.org/abs/2106.10503v1
    • [stat.ME]Scalable Bayesian change point detection with spike and slab priors
    Lorenzo Cappello, Oscar Hernan Madrid Padilla, Julia A. Palacios
    http://arxiv.org/abs/2106.10383v1
    • [stat.ME]Scalable Bayesian inference for time series via divide-and-conquer
    Rihui Ou, Deborshee Sen, David Dunson
    http://arxiv.org/abs/2106.11043v1
    • [stat.ME]Sparse logistic regression on functional data
    Yunnan Xu, Pang Du, John Robertson, Ryan Senger
    http://arxiv.org/abs/2106.10583v1
    • [stat.ME]Systemic Infinitesimal Over-dispersion on General Stochastic Graphical Models
    Ning Ning, Edward L. Ionides
    http://arxiv.org/abs/2106.10387v1
    • [stat.ME]The Tangent Exponential Model
    Anthony C. Davison, Nancy Reid
    http://arxiv.org/abs/2106.10496v1
    • [stat.ME]Tumor Radiogenomics with Bayesian Layered Variable Selection
    Shariq Mohammed, Sebastian Kurtek, Karthik Bharath, Arvind Rao, Veerabhadran Baladandayuthapani
    http://arxiv.org/abs/2106.10941v1
    • [stat.ME]maars: Tidy Inference under the ‘Models as Approximations’ Framework in R
    Riccardo Fogliato, Shamindra Shrotriya, Arun Kumar Kuchibhotla
    http://arxiv.org/abs/2106.11188v1
    • [stat.ML]Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis
    Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
    http://arxiv.org/abs/2106.11068v1
    • [stat.ML]Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation
    Ke Wang, Vidya Muthukumar, Christos Thrampoulidis
    http://arxiv.org/abs/2106.10865v1
    • [stat.ML]Deep Learning for Functional Data Analysis with Adaptive Basis Layers
    Junwen Yao, Jonas Mueller, Jane-Ling Wang
    http://arxiv.org/abs/2106.10414v1
    • [stat.ML]Differentiable Particle Filtering without Modifying the Forward Pass
    Adam Ścibior, Vaden Masrani, Frank Wood
    http://arxiv.org/abs/2106.10314v1
    • [stat.ML]Learning the Preferences of Uncertain Humans with Inverse Decision Theory
    Cassidy Laidlaw, Stuart Russell
    http://arxiv.org/abs/2106.10394v1
    • [stat.ML]Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation
    Magda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos
    http://arxiv.org/abs/2106.10591v1
    • [stat.ML]Nested Variational Inference
    Heiko Zimmermann, Hao Wu, Babak Esmaeili, Jan-Willem van de Meent
    http://arxiv.org/abs/2106.11302v1
    • [stat.ML]On the benefits of maximum likelihood estimation for Regression and Forecasting
    Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh
    http://arxiv.org/abs/2106.10370v1
    • [stat.ML]Outlier Detection and Spatial Analysis Algorithms
    Jacob John
    http://arxiv.org/abs/2106.10669v1
    • [stat.ML]Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo
    Robert J. Webber, Michael Lindsey
    http://arxiv.org/abs/2106.10558v1
    • [stat.ML]Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series
    Elena Ehrlich, Laurent Callot, François-Xavier Aubet
    http://arxiv.org/abs/2106.10952v1
    • [stat.ML]Stratified Learning: a general-purpose statistical method for improved learning under Covariate Shift
    Maximilian Autenrieth, David A. van Dyk, Roberto Trotta, David C. Stenning
    http://arxiv.org/abs/2106.11211v1