astro-ph.IM - 仪器仪表和天体物理学方法
    cond-mat.dis-nn - 无序系统与神经网络
    cond-mat.mtrl-sci - 材料科学
    cs.AI - 人工智能
    cs.AR - 硬件体系结构
    cs.CL - 计算与语言
    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.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    cs.DS - 数据结构与算法
    cs.FL - 形式语言与自动机理论
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    cs.MS - 数学软件
    cs.NE - 神经与进化计算
    cs.NI - 网络和互联网体系结构
    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
    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
    gr-qc - 广义相对论与量子宇宙学
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.ao-ph - 大气和海洋物理
    physics.soc-ph - 物理学与社会
    q-bio.PE - 人口与发展
    q-fin.CP -计算金融学
    q-fin.TR - 贸易与市场微观结构
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [astro-ph.IM]Astronomical source finding services for the CIRASA visual analytic platform
    • [astro-ph.IM]Convolutional Deep Denoising Autoencoders for Radio Astronomical Images
    • [cond-mat.dis-nn]Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising
    • [cond-mat.mtrl-sci]Neural message passing for predicting abnormal grain growth in Monte Carlo simulations of microstructural evolution
    • [cs.AI]A Formalisation of Abstract Argumentation in Higher-Order Logic
    • [cs.AI]A model for full local image interpretation
    • [cs.AI]Analyzing Wikipedia Membership Dataset and PredictingUnconnected Nodes in the Signed Networks
    • [cs.AI]Arjun: An Efficient Independent Support Computation Technique and its Applications to Counting and Sampling
    • [cs.AI]Conceptual Modeling and Artificial Intelligence: Mutual Benefits from Complementary Worlds
    • [cs.AI]Finding Backdoors to Integer Programs: A Monte Carlo Tree Search Framework
    • [cs.AI]Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative Adversarial Neural Networks
    • [cs.AI]In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications
    • [cs.AI]Learning Cooperation and Online Planning Through Simulation and Graph Convolutional Network
    • [cs.AI]Learning UI Navigation through Demonstrations composed of Macro Actions
    • [cs.AI]Lifting DecPOMDPs for Nanoscale Systems — A Work in Progress
    • [cs.AI]Neuro-Symbolic Forward Reasoning
    • [cs.AI]On the Completness and Complexity of the Lifted Dynamic Junction Tree Algorithm
    • [cs.AI]Projected Model Counting: Beyond Independent Support
    • [cs.AI]SS-MAIL: Self-Supervised Multi-Agent Imitation Learning
    • [cs.AI]Self-Annotated Training for Controllable Image Captioning
    • [cs.AI]Value alignment: a formal approach
    • [cs.AR]A Learning-based Approach Towards Automated Tuning of SSD Configurations
    • [cs.AR]Characterizing and Improving the Resilience of Accelerators in Autonomous Robots
    • [cs.AR]Energon: Towards Efficient Acceleration of Transformers Using Dynamic Sparse Attention
    • [cs.AR]Vega: A 10-Core SoC for IoT End-Nodes with DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode
    • [cs.C
    77b
    L]Pro-KD: Progressive Distillation by Following the Footsteps of the Teacher
    • [cs.CL]A Dataset for Discourse Structure in Peer Review Discussions
    • [cs.CL]An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-Trained Language Models
    • [cs.CL]Analysis of French Phonetic Idiosyncrasies for Accent Recognition
    • [cs.CL]Analyzing Dynamic Adversarial Training Data in the Limit
    • [cs.CL]Automatic Learning of Subword Dependent Model Scales
    • [cs.CL]BEAMetrics: A Benchmark for Language Generation Evaluation Evaluation
    • [cs.CL]Case-based Reasoning for Better Generalization in Text-Adventure Games
    • [cs.CL]Ceasing hate withMoH: Hate Speech Detection in Hindi-English Code-Switched Language
    • [cs.CL]Contextual Hate Speech Detection in Code Mixed Text using Transformer Based Approaches
    • [cs.CL]Deep Transfer Learning & Beyond: Transformer Language Models in Information Systems Research
    • [cs.CL]Efficient Sequence Training of Attention Models using Approximative Recombination
    • [cs.CL]Ensembling Graph Predictions for AMR Parsing
    • [cs.CL]Fine-Grained Opinion Summarization with Minimal Supervision
    • [cs.CL]FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metricsfor Automatic Text Generation
    • [cs.CL]GNN-LM: Language Modeling based on Global Contexts via GNN
    • [cs.CL]HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression
    • [cs.CL]Improving Compositional Generalization with Self-Training for Data-to-Text Generation
    • [cs.CL]Information-Theoretic Measures of Dataset Difficulty
    • [cs.CL]Intent Classification Using Pre-Trained Embeddings For Low Resource Languages
    • [cs.CL]Learning to Solve Complex Tasks by Talking to Agents
    • [cs.CL]Leveraging Knowledge in Multilingual Commonsense Reasoning
    • [cs.CL]Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora
    • [cs.CL]MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding
    • [cs.CL]Measuring Cognitive Status from Speech in a Smart Home Environment
    • [cs.CL]Multimodal Dialogue Response Generation
    • [cs.CL]NormFormer: Improved Transformer Pretraining with Extra Normalization
    • [cs.CL]On the Robustness of Reading Comprehension Models to Entity Renaming
    • [cs.CL]On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark
    • [cs.CL]PAGnol: An Extra-Large French Generative Model
    • [cs.CL]PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
    • [cs.CL]Predicting the Performance of Multilingual NLP Models
    • [cs.CL]Quantifying the Task-Specific Information in Text-Based Classifications
    • [cs.CL]Ranking Facts for Explaining Answers to Elementary Science Questions
    • [cs.CL]Reminding the Incremental Language Model via Data-Free Self-Distillation
    • [cs.CL]Schrödinger’s Tree — On Syntax and Neural Language Models
    • [cs.CL]Seeking Patterns, Not just Memorizing Procedures: Contrastive Learning for Solving Math Word Problems
    • [cs.CL]SentimentArcs: A Novel Method for Self-Supervised Sentiment Analysis of Time Series Shows SOTA Transformers Can Struggle Finding Narrative Arcs
    • [cs.CL]Sharpness-Aware Minimization Improves Language Model Generalization
    • [cs.CL]Sparse Distillation: Speeding Up Text Classification by Using Bigger Models
    • [cs.CL]Substructure Distribution Projection for Zero-Shot Cross-Lingual Dependency Parsing
    • [cs.CL]Tackling Multi-Answer Open-Domain Questions via a Recall-then-Verify Framework
    • [cs.CL]The Arabic Parallel Gender Corpus 2.0: Extensions and Analyses
    • [cs.CL]The Power of Prompt Tuning for Low-Resource Semantic Parsing
    • [cs.CL]Think Before You Speak: Using Self-talk to Generate Implicit Commonsense Knowledge for Response Generation
    • [cs.CL]Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation
    • [cs.CL]Understanding Procedural Knowledge by Sequencing Multimodal Instructional Manuals
    • [cs.CL]Unsupervised Natural Language Inference Using PHL Triplet Generation
    • [cs.CL]Using Natural Language Processing to Understand Reasons and Motivators Behind Customer Calls in Financial Domain
    • [cs.CL]ViraPart: A Text Refinement Framework for ASR and NLP Tasks in Persian
    • [cs.CL]Virtual Augmentation Supported Contrastive Learning of Sentence Representations
    • [cs.CL]n-stage Latent Dirichlet Allocation: A Novel Approach for LDA
    • [cs.CR]Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing
    • [cs.CR]HIDE & SEEK: Privacy-Preserving Rebalancing on Payment Channel Networks
    • [cs.CR]Scaling Blockchains: Can Elected Committees Help?
    • [cs.CR]TESDA: Transform Enabled Statistical Detection of Attacks in Deep Neural Networks
    • [cs.CV]3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers
    • [cs.CV]A DCT-based Tensor Completion Approach for Recovering Color Images and Videos from Highly Undersampled Data
    • [cs.CV]A Deep Learning-based Approach for Real-time Facemask Detection
    • [cs.CV]A Good Prompt Is Worth Millions of Parameters? Low-resource Prompt-based Learning for Vision-Language Models
    • [cs.CV]A Unified Framework for Generalized Low-Shot Medical Image Segmentation with Scarce Data
    • [cs.CV]AE-StyleGAN: Improved Training of Style-Based Auto-Encoders
    • [cs.CV]ASFormer: Transformer for Action Segmentation
    • [cs.CV]Abnormal Occupancy Grid Map Recognition using Attention Network
    • [cs.CV]Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix
    • [cs.CV]An Acceleration Method Based on Deep Learning and Multilinear Feature Space
    • [cs.CV]Asymmetric Modality Translation For Face Presentation Attack Detection
    • [cs.CV]Automated Remote Sensing Forest Inventory Using Satelite Imagery
    • [cs.CV]BNAS v2: Learning Architectures for Binary Networks with Empirical Improvements
    • [cs.CV]Boosting Image Outpainting with Semantic Layout Prediction
    • [cs.CV]Boosting the Transferability of Video Adversarial Examples via Temporal Translation
    • [cs.CV]CMTR: Cross-modality Transformer for Visible-infrared Person Re-identification
    • [cs.CV]Color Image Segmentation Using Multi-Objective Swarm Optimizer and Multi-level Histogram Thresholding
    • [cs.CV]Comparing Human and Machine Bias in Face Recognition
    • [cs.CV]Compression-aware Projection with Greedy Dimension Reduction for Convolutional Neural Network Activations
    • [cs.CV]Continuation of Famous Art with AI: A Conditional Adversarial Network Inpainting Approach
    • [cs.CV]Contrastive Learning of Visual-Semantic Embeddings
    • [cs.CV]Counting Objects by Diffused Index: geometry-free and training-free approach
    • [cs.CV]DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction
    • [cs.CV]Dataset Knowledge Transfer for Class-Incremental Learning without Memory
    • [cs.CV]Deep CNNs for Peripheral Blood Cell Classification
    • [cs.CV]Deep Mode
    f9b
    ls with Fusion Strategies for MVP Point Cloud Registration
    • [cs.CV]Differentiable Rendering with Perturbed Optimizers
    • [cs.CV]Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection
    • [cs.CV]Disentangled Representation with Dual-stage Feature Learning for Face Anti-spoofing
    • [cs.CV]Distinguishing Natural and Computer-Generated Images using Multi-Colorspace fused EfficientNet
    • [cs.CV]Domain Generalisation for Apparent Emotional Facial Expression Recognition across Age-Groups
    • [cs.CV]Don’t Judge Me by My Face : An Indirect Adversarial Approach to Remove Sensitive Information From Multimodal Neural Representation in Asynchronous Job Video Interviews
    • [cs.CV]Dynamic Slimmable Denoising Network
    • [cs.CV]Explore before Moving: A Feasible Path Estimation and Memory Recalling Framework for Embodied Navigation
    • [cs.CV]Exploring Novel Pooling Strategies for Edge Preserved Feature Maps in Convolutional Neural Networks
    • [cs.CV]FAST3D: Flow-Aware Self-Training for 3D Object Detectors
    • [cs.CV]FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation
    • [cs.CV]Face Verification with Challenging Imposters and Diversified Demographics
    • [cs.CV]FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces
    • [cs.CV]Fast tree skeleton extraction using voxel thinning based on tree point cloud
    • [cs.CV]Finding Strong Gravitational Lenses Through Self-Attention
    • [cs.CV]Fully-Connected Tensor Network Decomposition for Robust Tensor Completion Problem
    • [cs.CV]Graph Convolution Neural Network For Weakly Supervised Abnormality Localization In Long Capsule Endoscopy Videos
    • [cs.CV]Grayscale Based Algorithm for Remote Sensing with Deep Learning
    • [cs.CV]HRFormer: High-Resolution Transformer for Dense Prediction
    • [cs.CV]Hybrid Mutimodal Fusion for Dimensional Emotion Recognition
    • [cs.CV]Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation
    • [cs.CV]InfAnFace: Bridging the infant-adult domain gap in facial landmark estimation in the wild
    • [cs.CV]Intelligent Video Editing: Incorporating Modern Talking Face Generation Algorithms in a Video Editor
    • [cs.CV]Joint 3D Human Shape Recovery from A Single Imag with Bilayer-Graph
    • [cs.CV]Learning multiplane images from single views with self-supervision
    • [cs.CV]Leveraging MoCap Data for Human Mesh Recovery
    • [cs.CV]Localization with Sampling-Argmax
    • [cs.CV]LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
    • [cs.CV]MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation
    • [cs.CV]MeronymNet: A Hierarchical Approach for Unified and Controllable Multi-Category Object Generation
    • [cs.CV]Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes
    • [cs.CV]Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks
    • [cs.CV]Multi-View Stereo Network with attention thin volume
    • [cs.CV]NYU-VPR: Long-Term Visual Place Recognition Benchmark with View Direction and Data Anonymization Influences
    • [cs.CV]Natural Image Reconstruction from fMRI using Deep Learning: A Survey
    • [cs.CV]Network Augmentation for Tiny Deep Learning
    • [cs.CV]Neural Network Pruning Through Constrained Reinforcement Learning
    • [cs.CV]NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric Mapping
    • [cs.CV]No RL, No Simulation: Learning to Navigate without Navigating
    • [cs.CV]Nonlinear Transform Induced Tensor Nuclear Norm for Tensor Completion
    • [cs.CV]On the Effect of Selfie Beautification Filters on Face Detection and Recognition
    • [cs.CV]Online Continual Learning Via Candidates Voting
    • [cs.CV]Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning
    • [cs.CV]Patch-Based Deep Autoencoder for Point Cloud Geometry Compression
    • [cs.CV]PixelPyramids: Exact Inference Models from Lossless Image Pyramids
    • [cs.CV]Predicting Rebar Endpoints using Sin Exponential Regression Model
    • [cs.CV]Pseudo-label refinement using superpixels for semi-supervised brain tumour segmentation
    • [cs.CV]Revealing Disocclusions in Temporal View Synthesis through Infilling Vector Prediction
    • [cs.CV]Robust Pedestrian Attribute Recognition Using Group Sparsity for Occlusion Videos
    • [cs.CV]SIN:Superpixel Interpolation Network
    • [cs.CV]Self-Supervised Monocular DepthEstimation with Internal Feature Fusion
    • [cs.CV]Siamese Transformer Pyramid Networks for Real-Time UAV Tracking
    • [cs.CV]StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis
    • [cs.CV]Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks
    • [cs.CV]SynCoLFinGer: Synthetic Contactless Fingerprint Generator
    • [cs.CV]TEAM-Net: Multi-modal Learning for Video Action Recognition with Partial Decoding
    • [cs.CV]TLDR: Twin Learning for Dimensionality Reduction
    • [cs.CV]Taming Visually Guided Sound Generation
    • [cs.CV]Temporally stable video segmentation without video annotations
    • [cs.CV]TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models
    • [cs.CV]Towards Language-guided Visual Recognition via Dynamic Convolutions
    • [cs.CV]Uncertainty-Aware Semi-Supervised Few Shot Segmentation
    • [cs.CV]Understanding Dimensional Collapse in Contrastive Self-supervised Learning
    • [cs.CV]Unsupervised Finetuning
    • [cs.CV]Unsupervised Image Fusion Using Deep Image Priors
    • [cs.CV]Unsupervised Shot Boundary Detection for Temporal Segmentation of Long Capsule Endoscopy Videos
    • [cs.CV]Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analytics
    • [cs.CV]Visual-aware Attention Dual-stream Decoder for Video Captioning
    • [cs.CV]VoteHMR: Occlusion-Aware Voting Network for Robust 3D Human Mesh Recovery from Partial Point Clouds
    • [cs.CY]Carbon Neutrality in Data Center
    • [cs.CY]Ctrl-Shift: How Privacy Sentiment Changed from 2019 to 2021
    • [cs.CY]Directional forces in the evolution of grammar
    • [cs.CY]Explainable Student Performance Prediction With Personalized Attention for Explaining Why A Student Fails
    • [cs.CY]How to Effectively Identify and Communicate Person-Targeting Media Bias in Daily News Consumption?
    • [cs.CY]Modelling Behaviour Change using Cognitive Agent Simulations
    • [cs.CY]Newsalyze: Effective Communication of Person-Targeting Biases in News Articles
    • [cs.CY]Ride Sharing & Data Privacy: An Analysis of the State of Practice
    • [cs.DC]Adaptive and Fair Transformation for Recoverable Mutual Exclusion
    • [cs.DC]Hydra: A System for Large Multi-Model Deep Learning
    • [cs.DC]Self-stabilizing Byzantine- and Intrusion-tolerant Consensus
    • [cs.DL]Deep forecasting of translational impact in medical research
    • [cs.DL]Return migration of German-affiliated researchers: Analyzing departure and return by gender, cohort, and discipline using Scopus bibliometric data 1996-2020
    • [cs.DL]Statistics in everyone’s backyard: an impact study via citation network analysis
    • [cs.DS]Dimensionality Reduction for Wasserstein Barycenter
    • [cs.DS]Terminal Embeddings in Sublinear Time
    • [cs.FL]What can we learn from universal Turing machines?
    • [cs.HC]Comparing Deep Neural Nets with UMAP Tour
    • [cs.HC]MAAD: A Model and Dataset for “Attended Awareness” in Driving
    • [cs.IR]Context-aware Reranking with Utility Maximization for Recommendation
    • [cs.IR]Demographic Biases of Crowd Workers in Key Opinion Leaders Finding
    • [cs.IR]Learning to Learn a Cold-start Sequential Recommender
    • [cs.IR]Low-Precision Quantization for Efficient Nearest Neighbor Search
    • [cs.IR]Prioritization of COVID-19-related literature via unsupervised keyphrase extraction and document representation learning
    • [cs.IR]Revisiting Popularity and Demographic Biases in Recommender Evaluation and Effectiveness
    • [cs.IR]Towards More Accountable Search Engines: Online Evaluation of Representation Bias
    • [cs.IT]A Framework of Mahalanobis-Distance Metric with Supervised Learning for Clustering Multipath Components in MIMO Channel Analysis
    • [cs.IT]A Primer on the Statistical Relation between Wireless Ultra-Reliability and Location Estimation
    • [cs.IT]A Q-Learning-based Approach for Distributed Beam Scheduling in mmWave Networks
    • [cs.IT]Affine Hermitian Grassmann Codes
    • [cs.IT]Capacity Region Bounds for the K user Dispersive Nonlinear Optical WDM Channel with Peak Power Constraints
    • [cs.IT]Coverage Probability of Double-IRS Assisted Communication Systems
    • [cs.IT]DNA Codes over the Ring 今日学术视野(2021.10.20) - 图1
    • [cs.IT]Deep Learning-Based Power Control for Uplink Cell-Free Massive MIMO Systems
    • [cs.IT]Deep Reinforcement Learning for Practical Phase Shift Optimization in RIS-aided MISO URLLC Systems
    • [cs.IT]Joint Spatial Division and Coaxial Multiplexing for Downlink Multi-User OAM Wireless Backhaul
    • [cs.IT]Location Information Assisted Beamforming Design for Reconfigurable Intelligent Surface Aided Communication Systems
    • [cs.IT]Multifractal of mass function
    • [cs.IT]Novel Secret-Key-Assisted Schemes for Secure MISOME-OFDM Systems
    • [cs.IT]Reconfigurable Intelligent Surface-Enhanced OFDM Communications via Delay Adjustable Metasurface
    • [cs.IT]Spectral Efficiency of OTFS Based Orthogonal Multiple Access with Rectangular Pulses
    • [cs.IT]System Outage Probability and Diversity Analysis of SWIPT Enabled Two-Way DF Relaying under Hardware Impairments
    • [cs.IT]The search of Type I codes
    • [cs.LG]A Dimensionality Reduction Approach for Convolutional Neural Networks
    • [cs.LG]A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization
    • [cs.LG]A Heterogeneous Graph Based Framework for Multimodal Neuroimaging Fusion Learning
    • [cs.LG]A Riemannian Mean Field Formulation for Two-layer Neural Networks with Batch Normalization
    • [cs.LG]Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
    • [cs.LG]Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications
    • [cs.LG]An LSTM-based Plagiarism Detection via Attention Mechanism and a Population-based Approach for Pre-Training Parameters with imbalanced Classes
    • [cs.LG]Beltrami Flow and Neural Diffusion on Graphs
    • [cs.LG]Black-box Adversarial Attacks on Network-wide Multi-step Traffic State Prediction Models
    • [cs.LG]Capsule Graph Neural Networks with EM Routing
    • [cs.LG]Centroid Approximation for Bootstrap
    • [cs.LG]Classical-to-Quantum Transfer Learning for Spoken Command Recognition Based on Quantum Neural Networks
    • [cs.LG]Compositional Attention: Disentangling Search and Retrieval
    • [cs.LG]Correlation-based Discovery of Disease Patterns for Syndromic Surveillance
    • [cs.LG]DFW-PP: Dynamic Feature Weighting based Popularity Prediction for Social Media Content
    • [cs.LG]DPNAS: Neural Architecture Search for Deep Learningwith Differential Privacy
    • [cs.LG]Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization
    • [cs.LG]Data Driven and Visualization based Strategization for University Rank Improvement using Decision Trees
    • [cs.LG]Deep Active Learning by Leveraging Training Dynamics
    • [cs.LG]Deep Learning and Spectral Embedding for Graph Partitioning
    • [cs.LG]Demystifying How Self-Supervised Features Improve Training from Noisy Labels
    • [cs.LG]Developing a novel fair-loan-predictor through a mul
    f9b
    ti-sensitive debiasing pipeline: DualFair
    • [cs.LG]Discovering and Achieving Goals via World Models
    • [cs.LG]Dynamic Graph Echo State Networks
    • [cs.LG]Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient
    • [cs.LG]EmbRace: Accelerating Sparse Communication for Distributed Training of NLP Neural Networks
    • [cs.LG]Equivariant Discrete Normalizing Flows
    • [cs.LG]Explaining generalization in deep learning: progress and fundamental limits
    • [cs.LG]Exploiting Domain-Specific Features to Enhance Domain Generalization
    • [cs.LG]Exploring Deep Neural Networks on Edge TPU
    • [cs.LG]Fair Tree Learning
    • [cs.LG]FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
    • [cs.LG]Finding Everything within Random Binary Networks
    • [cs.LG]Goal Agnostic Planning using Maximum Likelihood Paths in Hypergraph World Models
    • [cs.LG]GradSign: Model Performance Inference with Theoretical Insights
    • [cs.LG]Graph Partner Neural Networks for Semi-Supervised Learning on Graphs
    • [cs.LG]Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation
    • [cs.LG]Green Simulation Assisted Policy Gradient to Accelerate Stochastic Process Control
    • [cs.LG]Growing Representation Learning
    • [cs.LG]Hand Gesture Recognition Using Temporal Convolutions and Attention Mechanism
    • [cs.LG]Improving Robustness using Generated Data
    • [cs.LG]Intrusion-Free Graph Mixup
    • [cs.LG]Learning Optimal Conformal Classifiers
    • [cs.LG]Learning Prototype-oriented Set Representations for Meta-Learning
    • [cs.LG]Learning in High Dimension Always Amounts to Extrapolation
    • [cs.LG]Learning velocity model for complex media with deep convolutional neural networks
    • [cs.LG]Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning
    • [cs.LG]Low-rank Matrix Recovery With Unknown Correspondence
    • [cs.LG]MDP Abstraction with Successor Features
    • [cs.LG]MEMO: Test Time Robustness via Adaptation and Augmentation
    • [cs.LG]MG-GCN: Scalable Multi-GPU GCN Training Framework
    • [cs.LG]Mapping illegal waste dumping sites with neural-network classification of satellite imagery
    • [cs.LG]Natural Attribute-based Shift Detection
    • [cs.LG]NeuralArTS: Structuring Neural Architecture Search with Type Theory
    • [cs.LG]Noise-Resilient Ensemble Learning using Evidence Accumulation Clustering
    • [cs.LG]Noise-robust Clustering
    • [cs.LG]On Predictive Explanation of Data Anomalies
    • [cs.LG]On the Pareto Frontier of Regret Minimization and Best Arm Identification in Stochastic Bandits
    • [cs.LG]On the Statistical Analysis of Complex Tree-shaped 3D Objects
    • [cs.LG]On-board Fault Diagnosis of a Laboratory Mini SR-30 Gas Turbine Engine
    • [cs.LG]Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits
    • [cs.LG]Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs
    • [cs.LG]Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs
    • [cs.LG]Physics-guided Deep Markov Models for Learning Nonlinear Dynamical Systems with Uncertainty
    • [cs.LG]Poisoning Attacks on Fair Machine Learning
    • [cs.LG]Protecting Anonymous Speech: A Generative Adversarial Network Methodology for Removing Stylistic Indicators in Text
    • [cs.LG]Provable Hierarchy-Based Meta-Reinforcement Learning
    • [cs.LG]Provable RL with Exogenous Distractors via Multistep Inverse Dynamics
    • [cs.LG]Real-time Mortality Prediction Using MIMIC-IV ICU Data Via Boosted Nonparametric Hazards
    • [cs.LG]Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models
    • [cs.LG]S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based Networks
    • [cs.LG]SPAP: Simultaneous Demand Prediction and Planning for Electric Vehicle Chargers in a New City
    • [cs.LG]Self-Supervised Learning for Binary Networks by Joint Classifier Training
    • [cs.LG]Self-Supervised Representation Learning: Introduction, Advances and Challenges
    • [cs.LG]Semi-asynchronous Hierarchical Federated Learning for Cooperative Intelligent Transportation Systems
    • [cs.LG]Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection
    • [cs.LG]Speeding-Up Back-Propagation in DNN: Approximate Outer Product with Memory
    • [cs.LG]Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning
    • [cs.LG]State-Space Constraints Improve the Generalization of the Differentiable Neural Computer in some Algorithmic Tasks
    • [cs.LG]Streaming Decision Trees and Forests
    • [cs.LG]Tackling the Imbalance for GNNs
    • [cs.LG]Temporal Knowledge Graph Reasoning Triggered by Memories
    • [cs.LG]Topologically Regularized Data Embeddings
    • [cs.LG]Towards Better Long-range Time Series Forecasting using Generative Adversarial Networks
    • [cs.LG]Towards Federated Bayesian Network Structure Learning with Continuous Optimization
    • [cs.LG]Towards General Deep Leakage in Federated Learning
    • [cs.LG]Towards Instance-Optimal Offline Reinforcement Learning with Pessimism
    • [cs.LG]Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization
    • [cs.LG]Transformer with a Mixture of Gaussian Keys
    • [cs.LG]Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions
    • [cs.LG]Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry
    • [cs.LG]When Are Linear Stochastic Bandits Attackable?
    • [cs.LG]pygrank: A Python Package for Graph Node Ranking
    • [cs.LO]Learning First-Order Rules with Relational Path Contrast for Inductive Relation Reasoning
    • [cs.LO]Semantics of Conjectures
    • [cs.MS]Least Squares on GPUs in Multiple Double Precision
    • [cs.NE]Backpropagation with Biologically Plausible Spatio-Temporal Adjustment For Training Deep Spiking Neural Networks
    • [cs.NE]Learning Continuous Chaotic Attractors with a Reservoir Computer
    • [cs.NE]Minimal Conditions for Beneficial Local Search
    • [cs.NE]Result Diversification by Multi-objective Evolutionary Algorithms with Theoretical Guarantees
    • [cs.NI]Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing
    • [cs.RO]A New Approach to Complex Dynamic Geofencing for Unmanned Aerial Vehicles
    • [cs.RO]A Tactile-enabled Grasping Method for Robotic Fruit Harvesting
    • [cs.RO]A unified framework for walking and running of bipedal robots
    • [cs.RO]Accurate and Robust Object-oriented SLAM with 3D Quadric Landmark Construction in Outdoor Environment
    • [cs.RO]CLASP: Constrained Latent Shape Projection for Refining Object Shape from Robot Contact
    • [cs.RO]Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks
    • [cs.RO]Deep Tactile Experience: Estimating Tactile Sensor Output from Depth Sensor Data
    • [cs.RO]Does human-robot trust need reciprocity?
    • [cs.RO]Dynamic Compressed Sensing of Unsteady Flows with a Mobile Robot
    • [cs.RO]Electric Vehicle Automatic Charging System Based on Vision-force Fusion
    • [cs.RO]Enhancing exploration algorithms for navigation with visual SLAM
    • [cs.RO]Extended Version of Reactive Task Allocation and Planning of A Heterogeneous Multi-Robot System
    • [cs.RO]FAR Planner: Fast, Attemptable Route Planner using Dynamic Visibility Update
    • [cs.RO]Generative Adversarial Imitation Learning for End-to-End Autonomous Driving on Urban Environments
    • [cs.RO]How Far Two UAVs Should Be subject to Communication Uncertainties
    • [cs.RO]Keypoint-Based Bimanual Shaping of Deformable Linear Objects under Environmental Constraints using Hierarchical Action Planning
    • [cs.RO]Learning Cloth Folding Tasks with Refined Flow Based Spatio-Temporal Graphs
    • [cs.RO]Lifelong Topological Visual Navigation
    • [cs.RO]On-line Optimal Ranging Sensor Deployment for Robotic Exploration
    • [cs.RO]Online Motion Planning with Soft Timed Temporal Logic in Dynamic and Unknown Environment
    • [cs.RO]Partial Hierarchical Pose Graph Optimization for SLAM
    • [cs.RO]Probabilistic Inference in Planning for Partially Observable Long Horizon Problems
    • [cs.RO]Reinforcement Learning-Based Coverage Path Planning with Implicit Cellular Decomposition
    • [cs.RO]Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper
    • [cs.RO]TIP: Task-Informed Motion Prediction for Intelligent Systems
    • [cs.RO]Trajectory Optimization for Thermally-Actuated Soft Planar Robot Limbs
    • [cs.RO]sbp-env: A Python Package for Sampling-based Motion Planner and Samplers
    • [cs.SD]Deep Clustering For General-Purpose Audio Representations
    • [cs.SD]FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech Detection
    • [cs.SD]Improving End-To-End Modeling for Mispronunciation Detection with Effective Augmentation Mechanisms
    • [cs.SD]LDNet: Unified Listener Dependent Modeling in MOS Prediction for Synthetic Speech
    • [cs.SD]Real Additive Margin Softmax for Speaker Verification
    • [cs.SD]Towards Robust Waveform-Based Acoustic Models
    • [cs.SE]AugmentedCode: Examining the Effects of Natural Language Resources in Code Retrieval Models
    • [cs.SE]Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review
    • [cs.SI]Information Operations in Turkey: Manufacturing Resilience with Free Twitter Accounts
    • [cs.SI]Measuring the influence of beliefs in belief networks
    • [cs.SI]Robust Correlation Clustering with Asymmetric Noise
    • [cs.SI]Stability evaluation of the Russian sociologists online community: 2011-2018 years
    • [eess.AS]A Unified Speaker Adaptation Approach for ASR
    • [eess.AS]A Variational Bayesian Approach to Learning Latent Variables for Acoustic Knowledge Transfer
    • [eess.AS]ASR4REAL: An extended benchmark for speech models
    • [eess.AS]Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Features
    • [eess.IV]A deep learning pipeline for localization, differentiation, and uncertainty estimation of liver lesions using multi-phasic and multi-sequence MRI
    • [eess.IV]An Analysis and Implementation of the HDR+ Burst Denoising Method
    • [eess.IV]Attention W-Net: Improved Skip Connections for better Representations
    • [eess.IV]BAPGAN: GAN-based Bone Age Progression of Femur and Phalange X-ray Images
    • [eess.IV]Body Part Regression for CT Images
    • [eess.IV]Bridging the gap between paired and unpaired medical image translation
    • [eess.IV]CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans
    • [eess.IV]COVID-19 Detection in Chest X-ray Images Using Swin-Transformer and Transformer in Transformer
    • [eess.IV]DBSegment: Fast and robust segmentation of deep brain structures — Evaluation of transportability across acquisition domains
    • [eess.IV]Data Shapley Value for Handling Noisy Labels: An application in Screening COVID-19 Pneumonia from Chest CT Scans
    • [eess.IV]Deep Image Debanding
    • [eess.IV]Deep learning-based detection of intravenous contrast in computed tomography scans
    • [eess.IV]Fast Strain Estimation and Frame Selection in Ultrasound Elastography using Machine Learning
    • [eess.IV]GAN-based disentanglement learning for chest X-ray rib suppression
    • [eess.IV]Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep Learning
    • [eess.IV]Locally Adaptive Structure and Texture Similarity for Image Quality Assessment
    • [eess.IV]Rheumatoid Arthritis: Automated Scoring of Radiographic Joint Damage
    • [eess.IV]SAGAN: Adversarial Spatial-asymmetric Attention for Noisy Nona-Bayer Reconstruction
    • [eess.IV]Salt and pepper noise removal method based on stationary Framelet transform with non-convex sparsity regularization
    • [eess.IV]Self-Supervised U-Net for Segmenting Flat and Sessile Polyps
    • [eess.SP]A MIMO Radar-based Few-Shot Learning Approach for Human-ID
    • [eess.SP]Unsupervised Learned Kalman Filtering
    • [eess.SY]Improving Robustness of Reinforcement Learning for Power System Control with Adversarial Training
    • [eess.SY]MARTINI: Smart Meter Driven Estimation of HVAC Schedules and Energy Savings Based on WiFi Sensing and Clustering
    • [gr-qc]Gravitational wave surrogates through automated machine learning
    • [math.OC]A portfolio approach to massively parallel Bayesian optimization
    • [math.OC]A theoretical and empirical study of new adaptive algorithms with additional momentum steps and shifted updates for stochastic non-convex optimization
    • [math.OC]An actor-critic algorithm with deep double recurrent agents to solve the job shop scheduling problem
    • [math.OC]Computing Semilinear Sparse Models for Approximately Eventually Periodic Signals
    • [math.OC]Fast Projection onto the Capped Simplex withApplications to Sparse Regression in Bioinformatics
    • [math.OC]Koopman Operator Theory for Nonlinear Dynamic Modeling using Dynamic Mode Decomposition
    • [math.OC]Nys-Curve: Nyström-Approximated Curvature for Stochastic Optimization
    • [math.OC]Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto Set
    • [math.ST]Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches
    • [math.ST]Minimum 今日学术视野(2021.10.20) - 图2-norm interpolators: Precise asymptotics and multiple descent
    • [math.ST]On minimax estimation problem for stationary stochastic sequences from observations in special sets of points
    • [math.ST]Regression with Missing Data, a Comparison Study of TechniquesBased on Random Forests
    • [math.ST]Spectral measures of empirical autocovariance matrices of high dimensional Gaussian stationary processes
    • [physics.ao-ph]Graph-based Local Climate Classification in Iran
    • [physics.soc-ph]Directed Percolation in Random Temporal Network Models with Heterogeneities
    • [physics.soc-ph]Understanding the network formation pattern for better link prediction
    • [q-bio.PE]Estimating individual admixture from finite reference databases
    • [q-fin.CP]Sector Volatility Prediction Performance Using GARCH Models and Artificial Neural Networks
    • [q-fin.TR]Understanding jumps in high frequency digital asset markets
    • [quant-ph]Quantum Error Correction with Reflexive Stabilizer Codes and Cayley Graphs
    • [stat.AP]A Bayesian Selection Model for Correcting Outcome Reporting Bias With Application to a Meta-analysis on Heart Failure Interventions
    • [stat.AP]A Space-time Model for Inferring A Susceptibility Map for An Infectious Disease
    • [stat.AP]Assessing Ecosystem State Space Models: Identifiability and Estimation
    • [stat.AP]Building Degradation Index with Variable Selection for Multivariate Sensory Data
    • [stat.AP]Exploitation of error correlation in a large analysis validation: GlobCurrent case study
    • [stat.AP]Gradient boosting with extreme-value theory for wildfire prediction
    • [stat.AP]Minding non-collapsibility of odds ratios when recalibrating risk prediction models
    • [stat.AP]On completing a measurement model by symmetry
    • [stat.AP]Spatio-temporal extreme event modeling of terror insurgencies
    • [stat.ME]A Bayesian approach to multi-task learning with network lasso
    • [stat.ME]A Reduced-Bias Weighted least square estimation of the Extreme Value Index
    • [stat.ME]Double Robust Mass-Imputation with Matching Estimators
    • [stat.ME]Exact Bias Correction for Linear Adjustment of Randomized Controlled Trials
    • [stat.ME]JEL ratio test for independence of time to failure and cause of failure in competing risks
    • [stat.ME]Multi-group Gaussian Processes
    • [stat.ME]Optimal designs for experiments for scalar-on-function linear models
    • [stat.ME]Quantile Regression by Dyadic CART
    • [stat.ME]Sample size calculations for n-of-1 trials
    • [stat.ME]Variance Reduction in Stochastic Reaction Networks using Control Variates
    • [stat.ML]Adversarial Attacks on Gaussian Process Bandits
    • [stat.ML]Efficient Exploration in Binary and Preferential Bayesian Optimization
    • [stat.ML]Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approach
    • [stat.ML]Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling
    • [stat.ML]Nuances in Margin Conditions Determine Gains in Active Learning
    • [stat.ML]On Model Selection Consistency of Lasso for High-Dimensional Ising Models on Tree-like Graphs
    • [stat.ML]Persuasion by Dimension Reduction
    • [stat.ML]Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning
    • [stat.ML]RKHS-SHAP: Shapley Values for Kernel Methods
    • [stat.ML]Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules
    • [stat.ML]Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference

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

    • [astro-ph.IM]Astronomical source finding services for the CIRASA visual analytic platform
    S. Riggi, C. Bordiu, F. Vitello, G. Tudisco, E. Sciacca, D. Magro, R. Sortino, C. Pino, M. Molinaro, M. Benedettini, S. Leurini, F. Bufano, M. Raciti, U. Becciani
    http://arxiv.org/abs/2110.08211v2

    • [astro-ph.IM]Convolutional Deep Denoising Autoencoders for Radio Astronomical Images
    Claudio Gheller, Franco Vazza
    http://arxiv.org/abs/2110.08618v1

    • [cond-mat.dis-nn]Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising
    Antoine Maillard, Florent Krzakala, Marc Mézard, Lenka Zdeborová
    http://arxiv.org/abs/2110.08775v1

    • [cond-mat.mtrl-sci]Neural message passing for predicting abnormal grain growth in Monte Carlo simulations of microstructural evolution
    Ryan Cohn, Elizabeth Holm
    http://arxiv.org/abs/2110.09326v1

    • [cs.AI]A Formalisation of Abstract Argumentation in Higher-Order Logic
    Alexander Steen, David Fuenmayor
    http://arxiv.org/abs/2110.09174v1

    • [cs.AI]A model for full local image interpretation
    Guy Ben-Yosef, Liav Assif, Daniel Harari, Shimon Ullman
    http://arxiv.org/abs/2110.08744v1

    • [cs.AI]Analyzing Wikipedia Membership Dataset and PredictingUnconnected Nodes in the Signed Networks
    Zhihao Wu, Taoran Li, Ray Roman
    http://arxiv.org/abs/2110.09111v1

    • [cs.AI]Arjun: An Efficient Independent Support Computation Technique and its Applications to Counting and Sampling
    Mate Soos, Kuldeep S. Meel
    http://arxiv.org/abs/2110.09026v1

    • [cs.AI]Conceptual Modeling and Artificial Intelligence: Mutual Benefits from Complementary Worlds
    Dominik Bork
    http://arxiv.org/abs/2110.08637v1

    • [cs.AI]Finding Backdoors to Integer Programs: A Monte Carlo Tree Search Framework
    Elias B. Khalil, Pashootan Vaezipoor, Bistra Dilkina
    http://arxiv.org/abs/2110.08423v1

    • [cs.AI]Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative Adversarial Neural Networks
    Nguyen Tan Viet Tuyen, Oya Celiktutan
    http://arxiv.org/abs/2110.09378v1

    • [cs.AI]In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications
    Borja G. León, Murray Shanahan, Francesco Belardinelli
    http://arxiv.org/abs/2110.09461v1

    • [cs.AI]Learning Cooperation and Online Planning Through Simulation and Graph Convolutional Network
    Rafid Ameer Mahmud, Fahim Faisal, Saaduddin Mahmud, Md. Mosaddek Khan
    http://arxiv.org/abs/2110.08480v1

    • [cs.AI]Learning UI Navigation through Demonstrations composed of Macro Actions
    Wei Li
    http://arxiv.org/abs/2110.08653v1

    • [cs.AI]Lifting DecPOMDPs for Nanoscale Systems — A Work in Progress
    Tanya Braun, Stefan Fischer, Florian Lau, Ralf Möller
    http://arxiv.org/abs/2110.09152v1

    • [cs.AI]Neuro-Symbolic Forward Reasoning
    Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
    http://arxiv.org/abs/2110.09383v1

    • [cs.AI]On the Completness and Complexity of the Lifted Dynamic Junction Tree Algorithm
    Marcel Gehrke
    http://arxiv.org/abs/2110.09197v1

    • [cs.AI]Projected Model Counting: Beyond Independent Support
    Jiong Yang, Supratik Chakraborty, Kuldeep S. Meel
    http://arxiv.org/abs/2110.09171v1

    • [cs.AI]SS-MAIL: Self-Supervised Multi-Agent Imitation Learning
    Akshay Dharmavaram, Tejus Gupta, Jiachen Li, Katia P. Sycara
    http://arxiv.org/abs/2110.08963v1

    • [cs.AI]Self-Annotated Training for Controllable Image Captioning
    Zhangzi Zhu, Tianlei Wang, Hong Qu
    http://arxiv.org/abs/2110.08446v1

    • [cs.AI]Value alignment: a formal approach
    Carles Sierra, Nardine Osman, Pablo Noriega, Jordi Sabater-Mir, Antoni Perelló
    http://arxiv.org/abs/2110.09240v1

    • [cs.AR]A Learning-based Approach Towards Automated Tuning of SSD Configurations
    Daixuan Li, Jian Huang
    http://arxiv.org/abs/2110.08685v1

    • [cs.AR]Characterizing and Improving the Resilience of Accelerators in Autonomous Robots
    Deval Shah, Zi Yu Xue, Karthik Pattabiraman, Tor M. Aamodt
    http://arxiv.org/abs/2110.08906v1

    • [cs.AR]Energon: Towards Efficient Acceleration of Transformers Using Dynamic Sparse Attention
    Zhe Zhou, Junlin Liu, Zhenyu Gu, Guangyu Sun
    http://arxiv.org/abs/2110.09310v1

    • [cs.AR]Vega: A 10-Core SoC for IoT End-Nodes with DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode
    Davide Rossi, Francesco Conti, Manuel Eggimann, Alfio Di Mauro, Giuseppe Tagliavini, Stefan Mach, Marco Guermandi, Antonio Pullini, Igor Loi, Jie Chen, Eric Flamand, Luca Benini
    http://arxiv.org/abs/2110.09101v1

    • [cs.C
    77b
    L]Pro-KD: Progressive Distillation by Following the Footsteps of the Teacher
    Mehdi Rezagholizadeh, Aref Jafari, Puneeth Salad, Pranav Sharma, Ali Saheb Pasand, Ali Ghodsi
    http://arxiv.org/abs/2110.08532v1

    • [cs.CL]A Dataset for Discourse Structure in Peer Review Discussions
    Neha Nayak Kennard, Tim O’Gorman, Akshay Sharma, Chhandak Bagchi, Matthew Clinton, Pranay Kumar Yelugam, Rajarshi Das, Hamed Zamani, Andrew McCallum
    http://arxiv.org/abs/2110.08520v1

    • [cs.CL]An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-Trained Language Models
    Nicholas Meade, Elinor Poole-Dayan, Siva Reddy
    http://arxiv.org/abs/2110.08527v1

    • [cs.CL]Analysis of French Phonetic Idiosyncrasies for Accent Recognition
    Pierre Berjon, Avishek Nag, Soumyabrata Dev
    http://arxiv.org/abs/2110.09179v1

    • [cs.CL]Analyzing Dynamic Adversarial Training Data in the Limit
    Eric Wallace, Adina Williams, Robin Jia, Douwe Kiela
    http://arxiv.org/abs/2110.08514v1

    • [cs.CL]Automatic Learning of Subword Dependent Model Scales
    Felix Meyer, Wilfried Michel, Mohammad Zeineldeen, Ralf Schlüter, Hermann Ney
    http://arxiv.org/abs/2110.09324v1

    • [cs.CL]BEAMetrics: A Benchmark for Language Generation Evaluation Evaluation
    Thomas Scialom, Felix Hill
    http://arxiv.org/abs/2110.09147v1

    • [cs.CL]Case-based Reasoning for Better Generalization in Text-Adventure Games
    Mattia Atzeni, Shehzaad Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan
    http://arxiv.org/abs/2110.08470v1

    • [cs.CL]Ceasing hate withMoH: Hate Speech Detection in Hindi-English Code-Switched Language
    Arushi Sharma, Anubha Kabra, Minni Jain
    http://arxiv.org/abs/2110.09393v1

    • [cs.CL]Contextual Hate Speech Detection in Code Mixed Text using Transformer Based Approaches
    Ravindra Nayak, Raviraj Joshi
    http://arxiv.org/abs/2110.09338v1

    • [cs.CL]Deep Transfer Learning & Beyond: Transformer Language Models in Information Systems Research
    Ross Gruetzemacher, David Paradice
    http://arxiv.org/abs/2110.08975v1

    • [cs.CL]Efficient Sequence Training of Attention Models using Approximative Recombination
    Nils-Philipp Wynands, Wilfried Michel, Jan Rosendahl, Ralf Schlüter, Hermann Ney
    http://arxiv.org/abs/2110.09245v1

    • [cs.CL]Ensembling Graph Predictions for AMR Parsing
    Hoang Thanh Lam, Gabriele Picco, Yufang Hou, Young-Suk Lee, Lam M. Nguyen, Dzung T. Phan, Vanessa López, Ramon Fernandez Astudillo
    http://arxiv.org/abs/2110.09131v1

    • [cs.CL]Fine-Grained Opinion Summarization with Minimal Supervision
    Suyu Ge, Jiaxin Huang, Yu Meng, Sharon Wang, Jiawei Han
    http://arxiv.org/abs/2110.08845v1

    • [cs.CL]FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metricsfor Automatic Text Generation
    Moussa Kamal Eddine, Guokan Shang, Antoine J. -P. Tixier, Michalis Vazirgiannis
    http://arxiv.org/abs/2110.08559v1

    • [cs.CL]GNN-LM: Language Modeling based on Global Contexts via GNN
    Yuxian Meng, Shi Zong, Xiaoya Li, Xiaofei Sun, Tianwei Zhang, Fei Wu, Jiwei Li
    http://arxiv.org/abs/2110.08743v1

    • [cs.CL]HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression
    Chenhe Dong, Yaliang Li, Ying Shen, Minghui Qiu
    http://arxiv.org/abs/2110.08551v1

    • [cs.CL]Improving Compositional Generalization with Self-Training for Data-to-Text Generation
    Sanket Vaibhav Mehta, Jinfeng Rao, Yi Tay, Mihir Kale, Ankur Parikh, Hongtao Zhong, Emma Strubell
    http://arxiv.org/abs/2110.08467v1

    • [cs.CL]Information-Theoretic Measures of Dataset Difficulty
    Kawin Ethayarajh, Yejin Choi, Swabha Swayamdipta
    http://arxiv.org/abs/2110.08420v1

    • [cs.CL]Intent Classification Using Pre-Trained Embeddings For Low Resource Languages
    Hemant Yadav, Akshat Gupta, Sai Krishna Rallabandi, Alan W Black, Rajiv Ratn Shah
    http://arxiv.org/abs/2110.09264v1

    • [cs.CL]Learning to Solve Complex Tasks by Talking to Agents
    Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal
    http://arxiv.org/abs/2110.08542v1

    • [cs.CL]Leveraging Knowledge in Multilingual Commonsense Reasoning
    Yuwei Fang, Shuohang Wang, Yichong Xu, Ruochen Xu, Siqi Sun, Chenguang Zhu, Michael Zeng
    http://arxiv.org/abs/2110.08462v1

    • [cs.CL]Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora
    Xisen Jin, Dejiao Zhang, Henghui Zhu, Wei Xiao, Shang-Wen Li, Xiaokai Wei, Andrew Arnold, Xiang Ren
    http://arxiv.org/abs/2110.08534v1

    • [cs.CL]MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding
    Junlong Li, Yiheng Xu, Lei Cui, Furu Wei
    http://arxiv.org/abs/2110.08518v1

    • [cs.CL]Measuring Cognitive Status from Speech in a Smart Home Environment
    Kathleen C. Fraser, Majid Komeili
    http://arxiv.org/abs/2110.09421v1

    • [cs.CL]Multimodal Dialogue Response Generation
    Qingfeng Sun, Yujing Wang, Can Xu, Kai Zheng, Yaming Yang, Huang Hu, Fei Xu, Jessica Zhang, Xiubo Geng, Daxin Jiang
    http://arxiv.org/abs/2110.08515v1

    • [cs.CL]NormFormer: Improved Transformer Pretraining with Extra Normalization
    Sam Shleifer, Jason Weston, Myle Ott
    http://arxiv.org/abs/2110.09456v1

    • [cs.CL]On the Robustness of Reading Comprehension Models to Entity Renaming
    Jun Yan, Yang Xiao, Sagnik Mukherjee, Bill Yuchen Lin, Robin Jia, Xiang Ren
    http://arxiv.org/abs/2110.08555v1

    • [cs.CL]On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark
    Hao Sun, Guangxuan Xu, Jiawen Deng, Jiale Cheng, Chujie Zheng, Hao Zhou, Nanyun Peng, Xiaoyan Zhu, Minlie Huang
    http://arxiv.org/abs/2110.08466v1

    • [cs.CL]PAGnol: An Extra-Large French Generative Model
    Julien Launay, E. L. Tommasone, Baptiste Pannier, François Boniface, Amélie Chatelain, Alessandro Cappelli, Iacopo Poli, Djamé Seddah
    http://arxiv.org/abs/2110.08554v1

    • [cs.CL]PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
    Wen Xiao, Iz Beltagy, Giuseppe Carenini, Arman Cohan
    http://arxiv.org/abs/2110.08499v1

    • [cs.CL]Predicting the Performance of Multilingual NLP Models
    Anirudh Srinivasan, Sunayana Sitaram, Tanuja Ganu, Sandipan Dandapat, Kalika Bali, Monojit Choudhury
    http://arxiv.org/abs/2110.08875v1

    • [cs.CL]Quantifying the Task-Specific Information in Text-Based Classifications
    Zining Zhu, Aparna Balagopalan, Marzyeh Ghassemi, Frank Rudzicz
    http://arxiv.org/abs/2110.08931v1

    • [cs.CL]Ranking Facts for Explaining Answers to Elementary Science Questions
    Jennifer D’Souza, Isaiah Onando Mulang’, Soeren Auer
    http://arxiv.org/abs/2110.09036v1

    • [cs.CL]Reminding the Incremental Language Model via Data-Free Self-Distillation
    Han Wang, Ruiliu Fu, Chengzhang Li, Xuejun Zhang, Jun Zhou, Yonghong Yan
    http://arxiv.org/abs/2110.08745v1

    • [cs.CL]Schrödinger’s Tree — On Syntax and Neural Language Models
    Artur Kulmizev, Joakim Nivre
    http://arxiv.org/abs/2110.08887v1

    • [cs.CL]Seeking Patterns, Not just Memorizing Procedures: Contrastive Learning for Solving Math Word Problems
    Zhongli Li, Wenxuan Zhang, Chao Yan, Qingyu Zhou, Chao Li, Hongzhi Liu, Yunbo Cao
    http://arxiv.org/abs/2110.08464v1

    • [cs.CL]SentimentArcs: A Novel Method for Self-Supervised Sentiment Analysis of Time Series Shows SOTA Transformers Can Struggle Finding Narrative Arcs
    Jon Chun
    http://arxiv.org/abs/2110.09454v1

    • [cs.CL]Sharpness-Aware Minimization Improves Language Model Generalization
    Dara Bahri, Hossein Mobahi, Yi Tay
    http://arxiv.org/abs/2110.08529v1

    • [cs.CL]Sparse Distillation: Speeding Up Text Classification by Using Bigger Models
    Qinyuan Ye, Madian Khabsa, Mike Lewis, Sinong Wang, Xiang Ren, Aaron Jaech
    http://arxiv.org/abs/2110.08536v1

    • [cs.CL]Substructure Distribution Projection for Zero-Shot Cross-Lingual Dependency Parsing
    Haoyue Shi, Kevin Gimpel, Karen Livescu
    http://arxiv.org/abs/2110.08538v1

    • [cs.CL]Tackling Multi-Answer Open-Domain Questions via a Recall-then-Verify Framework
    Zhihong Shao, Minlie Huang
    http://arxiv.org/abs/2110.08544v1

    • [cs.CL]The Arabic Parallel Gender Corpus 2.0: Extensions and Analyses
    Bashar Alhafni, Nizar Habash, Houda Bouamor
    http://arxiv.org/abs/2110.09216v1

    • [cs.CL]The Power of Prompt Tuning for Low-Resource Semantic Parsing
    Nathan Schucher, Siva Reddy, Harm de Vries
    http://arxiv.org/abs/2110.08525v1

    • [cs.CL]Think Before You Speak: Using Self-talk to Generate Implicit Commonsense Knowledge for Response Generation
    Pei Zhou, Karthik Gopalakrishnan, Behnam Hedayatnia, Seokhwan Kim, Jay Pujara, Xiang Ren, Yang Liu, Dilek Hakkani-Tur
    http://arxiv.org/abs/2110.08501v1

    • [cs.CL]Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation
    Guanhua Chen, Shuming Ma, Yun Chen, Dongdong Zhang, Jia Pan, Wenping Wang, Furu Wei
    http://arxiv.org/abs/2110.08547v1

    • [cs.CL]Understanding Procedural Knowledge by Sequencing Multimodal Instructional Manuals
    Te-Lin Wu, Alex Spangher, Pegah Alipoormolabashi, Marjorie Freedman, Ralph Weischedel, Nanyun Peng
    http://arxiv.org/abs/2110.08486v1

    • [cs.CL]Unsupervised Natural Language Inference Using PHL Triplet Generation
    Neeraj Varshney, Pratyay Banerjee, Tejas Gokhale, Chitta Baral
    http://arxiv.org/abs/2110.08438v1

    • [cs.CL]Using Natural Language Processing to Understand Reasons and Motivators Behind Customer Calls in Financial Domain
    Ankit Patil, Ankush Chopra, Sohom Ghosh, Vamshi Vadla
    http://arxiv.org/abs/2110.09094v1

    • [cs.CL]ViraPart: A Text Refinement Framework for ASR and NLP Tasks in Persian
    Narges Farokhshad, Milad Molazadeh, Saman Jamalabbasi, Hamed Babaei Giglou, Saeed Bibak
    http://arxiv.org/abs/2110.09086v1

    • [cs.CL]Virtual Augmentation Supported Contrastive Learning of Sentence Representations
    Dejiao Zhang, Wei Xiao, Henghui Zhu, Xiaofei Ma, Andrew O. Arnold
    http://arxiv.org/abs/2110.08552v1

    • [cs.CL]n-stage Latent Dirichlet Allocation: A Novel Approach for LDA
    Zekeriya Anil Guven, Banu Diri, Tolgahan Cakaloglu
    http://arxiv.org/abs/2110.08591v1

    • [cs.CR]Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing
    Qin Hu, Zhilin Wang, Minghui Xu, Xiuzhen Cheng
    http://arxiv.org/abs/2110.08671v1

    • [cs.CR]HIDE & SEEK: Privacy-Preserving Rebalancing on Payment Channel Networks
    Zeta Avarikioti, Krzysztof Pietrzak, Iosif Salem, Stefan Schmid, Samarth Tiwari, Michelle Yeo
    http://arxiv.org/abs/2110.08848v1

    • [cs.CR]Scaling Blockchains: Can Elected Committees Help?
    Alon Benhaim, Brett Hemenway Falk, Gerry Tsoukalas
    http://arxiv.org/abs/2110.08673v1

    • [cs.CR]TESDA: Transform Enabled Statistical Detection of Attacks in Deep Neural Networks
    Chandramouli Amarnath, Aishwarya H. Balwani, Kwondo Ma, Abhijit Chatterjee
    http://arxiv.org/abs/2110.08447v1

    • [cs.CV]3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers
    Zai Shi, Zhao Meng, Yiran Xing, Yunpu Ma, Roger Wattenhofer
    http://arxiv.org/abs/2110.08861v1

    • [cs.CV]A DCT-based Tensor Completion Approach for Recovering Color Images and Videos from Highly Undersampled Data
    Chenjian Pan, Chen Ling, Hongjin He, Liqun Qi, Yanwei Xu
    http://arxiv.org/abs/2110.09298v1

    • [cs.CV]A Deep Learning-based Approach for Real-time Facemask Detection
    Wadii Boulila, Ayyub Alzahem, Aseel Almoudi, Muhanad Afifi, Ibrahim Alturki, Maha Driss
    http://arxiv.org/abs/2110.08732v1

    • [cs.CV]A Good Prompt Is Worth Millions of Parameters? Low-resource Prompt-based Learning for Vision-Language Models
    Woojeong Jin, Yu Cheng, Yelong Shen, Weizhu Chen, Xiang Ren
    http://arxiv.org/abs/2110.08484v1

    • [cs.CV]A Unified Framework for Generalized Low-Shot Medical Image Segmentation with Scarce Data
    Hengji Cui, Dong Wei, Kai Ma, Shi Gu, Yefeng Zheng
    http://arxiv.org/abs/2110.09260v1

    • [cs.CV]AE-StyleGAN: Improved Training of Style-Based Auto-Encoders
    Ligong Han, Sri Harsha Musunuri, Martin Renqiang Min, Ruijiang Gao, Yu Tian, Dimitris Metaxas
    http://arxiv.org/abs/2110.08718v1

    • [cs.CV]ASFormer: Transformer for Action Segmentation
    Fangqiu Yi, Hongyu Wen, Tingting Jiang
    http://arxiv.org/abs/2110.08568v1

    • [cs.CV]Abnormal Occupancy Grid Map Recognition using Attention Network
    Fuqin Deng, Hua Feng, Mingjian Liang, Qi Feng, Ningbo Yi, Yong Yang, Yuan Gao, Junfeng Chen, Tin Lun Lam
    http://arxiv.org/abs/2110.09047v1

    • [cs.CV]Alleviating Noisy-label Effects in Image Classification via Probability Transition Matrix
    Ziqi Zhang, Yuexiang Li, Hongxin Wei, Kai Ma, Tao Xu, Yefeng Zheng
    http://arxiv.org/abs/2110.08866v1

    • [cs.CV]An Acceleration Method Based on Deep Learning and Multilinear Feature Space
    Michel Vinagreiro Edson Kitani Armando Lagana Leopoldo Yoshioka
    http://arxiv.org/abs/2110.08679v1

    • [cs.CV]Asymmetric Modality Translation For Face Presentation Attack Detection
    Zhi Li, Haoliang Li, Xin Luo, Xin Luo, Kwok-Yan Lam, Alex C. Kot
    http://arxiv.org/abs/2110.09108v1

    • [cs.CV]Automated Remote Sensing Forest Inventory Using Satelite Imagery
    Abduragim Shtanchaev, Artur Bille, Olga Sutyrina, Sara Elelimy
    http://arxiv.org/abs/2110.08590v1

    • [cs.CV]BNAS v2: Learning Architectures for Binary Networks with Empirical Improvements
    Dahyun Kim, Kunal Pratap Singh, Jonghyun Choi
    http://arxiv.org/abs/2110.08562v1

    • [cs.CV]Boosting Image Outpainting with Semantic Layout Prediction
    Ye Ma, Jin Ma, Min Zhou, Quan Chen, Tiezheng Ge, Yuning Jiang, Tong Lin
    http://arxiv.org/abs/2110.09267v1

    • [cs.CV]Boosting the Transferability of Video Adversarial Examples via Temporal Translation
    Zhipeng Wei, Jingjing Chen, Zuxuan Wu, Yu-Gang Jiang
    http://arxiv.org/abs/2110.09075v1

    • [cs.CV]CMTR: Cross-modality Transformer for Visible-infrared Person Re-identification
    Tengfei Liang, Yi Jin, Yajun Gao, Wu Liu, Songhe Feng, Tao Wang, Yidong Li
    http://arxiv.org/abs/2110.08994v1

    • [cs.CV]Color Image Segmentation Using Multi-Objective Swarm Optimizer and Multi-level Histogram Thresholding
    Mohammadreza Naderi Boldaji, Samaneh Hosseini Semnani
    http://arxiv.org/abs/2110.09217v1

    • [cs.CV]Comparing Human and Machine Bias in Face Recognition
    Samuel Dooley, Ryan Downing, George Wei, Nathan Shankar, Bradon Thymes, Gudrun Thorkelsdottir, Tiye Kurtz-Miott, Rachel Mattson, Olufemi Obiwumi, Valeriia Cherepanova, Micah Goldblum, John P Dickerson, Tom Goldstein
    http://arxiv.org/abs/2110.08396v1

    • [cs.CV]Compression-aware Projection with Greedy Dimension Reduction for Convolutional Neural Network Activations
    Yu-Shan Tai, Chieh-Fang Teng, Cheng-Yang Chang, An-Yeu Wu
    http://arxiv.org/abs/2110.08828v1

    • [cs.CV]Continuation of Famous Art with AI: A Conditional Adversarial Network Inpainting Approach
    Jordan J. Bird
    http://arxiv.org/abs/2110.09170v1

    • [cs.CV]Contrastive Learning of Visual-Semantic Embeddings
    Anurag Jain, Yashaswi Verma
    http://arxiv.org/abs/2110.08872v1

    • [cs.CV]Counting Objects by Diffused Index: geometry-free and training-free approach
    Mengyi Tang, Maryam Yashtini, Sung Ha Kang
    http://arxiv.org/abs/2110.08365v1

    • [cs.CV]DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction
    Itai Lang, Dvir Ginzburg, Shai Avidan, Dan Raviv
    http://arxiv.org/abs/2110.08636v1

    • [cs.CV]Dataset Knowledge Transfer for Class-Incremental Learning without Memory
    Habib Slim, Eden Belouadah, Adrian Popescu, Darian Onchis
    http://arxiv.org/abs/2110.08421v1

    • [cs.CV]Deep CNNs for Peripheral Blood Cell Classification
    Ekta Gavas, Kaustubh Olpadkar
    http://arxiv.org/abs/2110.09508v1

    • [cs.CV]Deep Mode
    f9b
    ls with Fusion Strategies for MVP Point Cloud Registration
    Lifa Zhu, Changwei Lin, Dongrui Liu, Xin Li, Francisco Gómez-Fernández
    http://arxiv.org/abs/2110.09129v1

    • [cs.CV]Differentiable Rendering with Perturbed Optimizers
    Quentin Le Lidec, Ivan Laptev, Cordelia Schmid, Justin Carpentier
    http://arxiv.org/abs/2110.09107v1

    • [cs.CV]Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection
    Shiwei Zhang, Wei Ke, Lin Yang, Qixiang Ye, Xiaopeng Hong, Yihong Gong, Tong Zhang
    http://arxiv.org/abs/2110.09060v1

    • [cs.CV]Disentangled Representation with Dual-stage Feature Learning for Face Anti-spoofing
    Yu-Chun Wang, Chien-Yi Wang, Shang-Hong Lai
    http://arxiv.org/abs/2110.09157v1

    • [cs.CV]Distinguishing Natural and Computer-Generated Images using Multi-Colorspace fused EfficientNet
    Manjary P Gangan, Anoop K, Lajish V L
    http://arxiv.org/abs/2110.09428v1

    • [cs.CV]Domain Generalisation for Apparent Emotional Facial Expression Recognition across Age-Groups
    Rafael Poyiadzi, Jie Shen, Stavros Petridis, Yujiang Wang, Maja Pantic
    http://arxiv.org/abs/2110.09168v1

    • [cs.CV]Don’t Judge Me by My Face : An Indirect Adversarial Approach to Remove Sensitive Information From Multimodal Neural Representation in Asynchronous Job Video Interviews
    Léo Hemamou, Arthur Guillon, Jean-Claude Martin, Chloé Clavel
    http://arxiv.org/abs/2110.09424v1

    • [cs.CV]Dynamic Slimmable Denoising Network
    Zutao Jiang, Changlin Li, Xiaojun Chang, Jihua Zhu, Yi Yang
    http://arxiv.org/abs/2110.08940v1

    • [cs.CV]Explore before Moving: A Feasible Path Estimation and Memory Recalling Framework for Embodied Navigation
    Yang Wu, Shirui Feng, Guanbin Li, Liang Lin
    http://arxiv.org/abs/2110.08571v1

    • [cs.CV]Exploring Novel Pooling Strategies for Edge Preserved Feature Maps in Convolutional Neural Networks
    Adithya Sineesh, Mahesh Raveendranatha Panicker
    http://arxiv.org/abs/2110.08842v1

    • [cs.CV]FAST3D: Flow-Aware Self-Training for 3D Object Detectors
    Christian Fruhwirth-Reisinger, Michael Opitz, Horst Possegger, Horst Bischof
    http://arxiv.org/abs/2110.09355v1

    • [cs.CV]FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation
    Fuqin Deng, Hua Feng, Mingjian Liang, Hongmin Wang, Yong Yang, Yuan Gao, Junfeng Chen, Junjie Hu, Xiyue Guo, Tin Lun Lam
    http://arxiv.org/abs/2110.08988v1

    • [cs.CV]Face Verification with Challenging Imposters and Diversified Demographics
    Adrian Popescu, Liviu-Daniel Ştefan, Jérôme Deshayes-Chossart, Bogdan Ionescu
    http://arxiv.org/abs/2110.08667v1

    • [cs.CV]FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces
    Ricard Durall, Jireh Jam, Dominik Strassel, Moi Hoon Yap, Janis Keuper
    http://arxiv.org/abs/2110.09425v1

    • [cs.CV]Fast tree skeleton extraction using voxel thinning based on tree point cloud
    Jingqian Sun, Pei Wang, Ronghao Li, Mei Zhou
    http://arxiv.org/abs/2110.09028v1

    • [cs.CV]Finding Strong Gravitational Lenses Through Self-Attention
    Hareesh Thuruthipilly, Adam Zadrozny, Agnieszka Pollo
    http://arxiv.org/abs/2110.09202v1

    • [cs.CV]Fully-Connected Tensor Network Decomposition for Robust Tensor Completion Problem
    Yun-Yang Liu, Xi-Le Zhao, Guang-Jing Song, Yu-Bang Zheng, Ting-Zhu Huang
    http://arxiv.org/abs/2110.08754v1

    • [cs.CV]Graph Convolution Neural Network For Weakly Supervised Abnormality Localization In Long Capsule Endoscopy Videos
    Sodiq Adewole, Philip Fernandes, James Jablonski, Andrew Copland, Michael Porter, Sana Syed, Donald Brown
    http://arxiv.org/abs/2110.09110v1

    • [cs.CV]Grayscale Based Algorithm for Remote Sensing with Deep Learning
    Sai Ganesh CS, Aouthithiye Barathwaj SR Y, R. Azhagumurugan, R. Swethaa S
    http://arxiv.org/abs/2110.08493v1

    • [cs.CV]HRFormer: High-Resolution Transformer for Dense Prediction
    Yuhui Yuan, Rao Fu, Lang Huang, Weihong Lin, Chao Zhang, Xilin Chen, Jingdong Wang
    http://arxiv.org/abs/2110.09408v1

    • [cs.CV]Hybrid Mutimodal Fusion for Dimensional Emotion Recognition
    Ziyu Ma, Fuyan Ma, Bin Sun, Shutao Li
    http://arxiv.org/abs/2110.08495v1

    • [cs.CV]Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation
    Yinghuan Shi, Jian Zhang, Tong Ling, Jiwen Lu, Yefeng Zheng, Qian Yu, Lei Qi, Yang Gao
    http://arxiv.org/abs/2110.08762v1

    • [cs.CV]InfAnFace: Bridging the infant-adult domain gap in facial landmark estimation in the wild
    M. Wan, S. Zhu, P. Gulati, L. Luan, X. Huang, R. Schwartz-Mette, M. Hayes, E. Zimmerman, S. Ostadabbas
    http://arxiv.org/abs/2110.08935v1

    • [cs.CV]Intelligent Video Editing: Incorporating Modern Talking Face Generation Algorithms in a Video Editor
    Anchit Gupta, Faizan Farooq Khan, Rudrabha Mukhopadhyay, Vinay P. Namboodiri, C. V. Jawahar
    http://arxiv.org/abs/2110.08580v1

    • [cs.CV]Joint 3D Human Shape Recovery from A Single Imag with Bilayer-Graph
    Xin Yu, Jeroen van Baar, Siheng Chen
    http://arxiv.org/abs/2110.08472v1

    • [cs.CV]Learning multiplane images from single views with self-supervision
    Gustavo Sutter P. Carvalho, Diogo C. Luvizon, Antonio Joia, Andre G. C. Pacheco, Otavio A. B. Penatti
    http://arxiv.org/abs/2110.09380v1

    • [cs.CV]Leveraging MoCap Data for Human Mesh Recovery
    Fabien Baradel, Thibault Groueix, Philippe Weinzaepfel, Romain Brégier, Yannis Kalantidis, Grégory Rogez
    http://arxiv.org/abs/2110.09243v1

    • [cs.CV]Localization with Sampling-Argmax
    Jiefeng Li, Tong Chen, Ruiqi Shi, Yujing Lou, Yong-Lu Li, Cewu Lu
    http://arxiv.org/abs/2110.08825v1

    • [cs.CV]LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
    Junjue Wang, Zhuo zheng, Ailong Ma, Xiaoyan Lu, Yanfei Zhong
    http://arxiv.org/abs/2110.08733v1

    • [cs.CV]MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation
    Xinshuo Weng, Boris Ivanovic, Marco Pavone
    http://arxiv.org/abs/2110.09481v1

    • [cs.CV]MeronymNet: A Hierarchical Approach for Unified and Controllable Multi-Category Object Generation
    Rishabh Baghel, Abhishek Trivedi, Tejas Ravichandran, Ravi Kiran Sarvadevabhatla
    http://arxiv.org/abs/2110.08818v1

    • [cs.CV]Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes
    Sara Hahner, Jochen Garcle
    http://arxiv.org/abs/2110.09401v1

    • [cs.CV]Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks
    Peihao Zhu, Rameen Abdal, John Femiani, Peter Wonka
    http://arxiv.org/abs/2110.08398v1

    • [cs.CV]Multi-View Stereo Network with attention thin volume
    Zihang Wan
    http://arxiv.org/abs/2110.08556v1

    • [cs.CV]NYU-VPR: Long-Term Visual Place Recognition Benchmark with View Direction and Data Anonymization Influences
    Diwei Sheng, Yuxiang Chai, Xinru Li, Chen Feng, Jianzhe Lin, Claudio Silva, John-Ross Rizzo
    http://arxiv.org/abs/2110.09004v1

    • [cs.CV]Natural Image Reconstruction from fMRI using Deep Learning: A Survey
    Zarina Rakhimberdina, Quentin Jodelet, Xin Liu, Tsuyoshi Murata
    http://arxiv.org/abs/2110.09006v1

    • [cs.CV]Network Augmentation for Tiny Deep Learning
    Han Cai, Chuang Gan, Ji Lin, Song Han
    http://arxiv.org/abs/2110.08890v1

    • [cs.CV]Neural Network Pruning Through Constrained Reinforcement Learning
    Shehryar Malik, Muhammad Umair Haider, Omer Iqbal, Murtaza Taj
    http://arxiv.org/abs/2110.08558v1

    • [cs.CV]NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric Mapping
    Stefan Lionar, Lukas Schmid, Cesar Cadena, Roland Siegwart, Andrei Cramariuc
    http://arxiv.org/abs/2110.09415v1

    • [cs.CV]No RL, No Simulation: Learning to Navigate without Navigating
    Meera Hahn, Devendra Chaplot, Shubham Tulsiani, Mustafa Mukadam, James M. Rehg, Abhinav Gupta
    http://arxiv.org/abs/2110.09470v1

    • [cs.CV]Nonlinear Transform Induced Tensor Nuclear Norm for Tensor Completion
    Ben-Zheng Li, Xi-Le Zhao, Teng-Yu Ji, Xiong-Jun Zhang, Ting-Zhu Huang
    http://arxiv.org/abs/2110.08774v1

    • [cs.CV]On the Effect of Selfie Beautification Filters on Face Detection and Recognition
    Pontus Hedman, Vasilios Skepetzis, Kevin Hernandez-Diaz, Josef Bigun, Fernando Alonso-Fernandez
    http://arxiv.org/abs/2110.08934v1

    • [cs.CV]Online Continual Learning Via Candidates Voting
    Jiangpeng He, Fengqing Zhu
    http://arxiv.org/abs/2110.08855v1

    • [cs.CV]Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning
    Uche Osahor, Nasser M. Nasrabadi
    http://arxiv.org/abs/2110.09374v1

    • [cs.CV]Patch-Based Deep Autoencoder for Point Cloud Geometry Compression
    Kang You, Pan Gao
    http://arxiv.org/abs/2110.09109v1

    • [cs.CV]PixelPyramids: Exact Inference Models from Lossless Image Pyramids
    Shweta Mahajan, Stefan Roth
    http://arxiv.org/abs/2110.08787v1

    • [cs.CV]Predicting Rebar Endpoints using Sin Exponential Regression Model
    Jong-Chan Park, Hye-Youn Lim, Dae-Seong Kang
    http://arxiv.org/abs/2110.08955v1

    • [cs.CV]Pseudo-label refinement using superpixels for semi-supervised brain tumour segmentation
    Bethany H. Thompson, Gaetano Di Caterina, Jeremy P. Voisey
    http://arxiv.org/abs/2110.08589v1

    • [cs.CV]Revealing Disocclusions in Temporal View Synthesis through Infilling Vector Prediction
    Vijayalakshmi Kanchana, Nagabhushan Somraj, Suraj Yadwad, Rajiv Soundararajan
    http://arxiv.org/abs/2110.08805v1

    • [cs.CV]Robust Pedestrian Attribute Recognition Using Group Sparsity for Occlusion Videos
    Geonu Lee, Kimin Yun, Jungchan Cho
    http://arxiv.org/abs/2110.08708v1

    • [cs.CV]SIN:Superpixel Interpolation Network
    Qing Yuan, Songfeng Lu, Yan Huang, Wuxin Sha
    http://arxiv.org/abs/2110.08702v1

    • [cs.CV]Self-Supervised Monocular DepthEstimation with Internal Feature Fusion
    Hang Zhou, David Greenwood, Sarah Taylor
    http://arxiv.org/abs/2110.09482v1

    • [cs.CV]Siamese Transformer Pyramid Networks for Real-Time UAV Tracking
    Daitao Xing, Nikolaos Evangeliou, Athanasios Tsoukalas, Anthony Tzes
    http://arxiv.org/abs/2110.08822v1

    • [cs.CV]StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis
    Jiatao Gu, Lingjie Liu, Peng Wang, Christian Theobalt
    http://arxiv.org/abs/2110.08985v1

    • [cs.CV]Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks
    Yikai Wang, Yi Yang, Fuchun Sun, Anbang Yao
    http://arxiv.org/abs/2110.09195v1

    • [cs.CV]SynCoLFinGer: Synthetic Contactless Fingerprint Generator
    Jannis Priesnitz, Christian Rathgeb, Nicolas Buchmann, Christoph Busch
    http://arxiv.org/abs/2110.09144v1

    • [cs.CV]TEAM-Net: Multi-modal Learning for Video Action Recognition with Partial Decoding
    Zhengwei Wang, Qi She, Aljosa Smolic
    http://arxiv.org/abs/2110.08814v1

    • [cs.CV]TLDR: Twin Learning for Dimensionality Reduction
    Yannis Kalantidis, Carlos Lassance, Jon Almazan, Diane Larlus
    http://arxiv.org/abs/2110.09455v1

    • [cs.CV]Taming Visually Guided Sound Generation
    Vladimir Iashin, Esa Rahtu
    http://arxiv.org/abs/2110.08791v1

    • [cs.CV]Temporally stable video segmentation without video annotations
    Aharon Azulay, Tavi Halperin, Orestis Vantzos, Nadav Bornstein, Ofir Bibi
    http://arxiv.org/abs/2110.08893v1

    • [cs.CV]TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models
    Soumick Chatterjee, Arnab Das, Chirag Mandal, Budhaditya Mukhopadhyay, Manish Vipinraj, Aniruddh Shukla, Rajatha Nagaraja Rao, Chompunuch Sarasaen, Oliver Speck, Andreas Nürnberger
    http://arxiv.org/abs/2110.08429v1

    • [cs.CV]Towards Language-guided Visual Recognition via Dynamic Convolutions
    Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Xinghao Ding, Yongjian Wu, Feiyue Huang, Yue Gao, Rongrong Ji
    http://arxiv.org/abs/2110.08797v1

    • [cs.CV]Uncertainty-Aware Semi-Supervised Few Shot Segmentation
    Soopil Kim, Philip Chikontwe, Sang Hyun Park
    http://arxiv.org/abs/2110.08954v1

    • [cs.CV]Understanding Dimensional Collapse in Contrastive Self-supervised Learning
    Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
    http://arxiv.org/abs/2110.09348v1

    • [cs.CV]Unsupervised Finetuning
    Suichan Li, Dongdong Chen, Yinpeng Chen, Lu Yuan, Lei Zhang, Qi Chu, Bin Liu, Nenghai Yu
    http://arxiv.org/abs/2110.09510v1

    • [cs.CV]Unsupervised Image Fusion Using Deep Image Priors
    Xudong Ma, Alin Achim, Paul Hill
    http://arxiv.org/abs/2110.09490v1

    • [cs.CV]Unsupervised Shot Boundary Detection for Temporal Segmentation of Long Capsule Endoscopy Videos
    Sodiq Adewole, Philip Fernandes, James Jablonski, Andrew Copland, Michael Porter, Sana Syed, Donald Brown
    http://arxiv.org/abs/2110.09067v1

    • [cs.CV]Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analytics
    Wenhan Yang, Haofeng Huang, Yueyu Hu, Ling-Yu Duan, Jiaying Liu
    http://arxiv.org/abs/2110.09241v1

    • [cs.CV]Visual-aware Attention Dual-stream Decoder for Video Captioning
    Zhixin Sun, Xian Zhong, Shuqin Chen, Lin Li, Luo Zhong
    http://arxiv.org/abs/2110.08578v1

    • [cs.CV]VoteHMR: Occlusion-Aware Voting Network for Robust 3D Human Mesh Recovery from Partial Point Clouds
    Guanze Liu, Yu Rong, Lu Sheng
    http://arxiv.org/abs/2110.08729v1

    • [cs.CY]Carbon Neutrality in Data Center
    Zhiwei Cao, Xin Zhou, Han Hu, Zhi Wang, Yonggang Wen
    http://arxiv.org/abs/2110.09284v1

    • [cs.CY]Ctrl-Shift: How Privacy Sentiment Changed from 2019 to 2021
    Angelica Goetzen, Samuel Dooley, Elissa M. Redmiles
    http://arxiv.org/abs/2110.09437v1

    • [cs.CY]Directional forces in the evolution of grammar
    Shimpei Okuda, Michio Hosaka, Kazutoshi Sasahara
    http://arxiv.org/abs/2110.08567v1

    • [cs.CY]Explainable Student Performance Prediction With Personalized Attention for Explaining Why A Student Fails
    Kun Niu, Xipeng Cao, Yicong Yu
    http://arxiv.org/abs/2110.08268v1

    • [cs.CY]How to Effectively Identify and Communicate Person-Targeting Media Bias in Daily News Consumption?
    Felix Hamborg, Timo Spinde, Kim Heinser, Karsten Donnay, Bela Gipp
    http://arxiv.org/abs/2110.09151v1

    • [cs.CY]Modelling Behaviour Change using Cognitive Agent Simulations
    Catriona M. Kennedy
    http://arxiv.org/abs/2110.08645v1

    • [cs.CY]Newsalyze: Effective Communication of Person-Targeting Biases in News Articles
    Felix Hamborg, Kim Heinser, Anastasia Zhukova, Karsten Donnay, Bela Gipp
    http://arxiv.org/abs/2110.09158v1

    • [cs.CY]Ride Sharing & Data Privacy: An Analysis of the State of Practice
    Carsten Hesselmann, Jan Gertheiss, Jörg P. Müller
    http://arxiv.org/abs/2110.09188v1

    • [cs.DC]Adaptive and Fair Transformation for Recoverable Mutual Exclusion
    Sahil Dhoked, Neeraj Mittal
    http://arxiv.org/abs/2110.08308v1

    • [cs.DC]Hydra: A System for Large Multi-Model Deep Learning
    Kabir Nagrecha, Arun Kumar
    http://arxiv.org/abs/2110.08633v1

    • [cs.DC]Self-stabilizing Byzantine- and Intrusion-tolerant Consensus
    Romaric Duvignau, Michel Raynal, Elad Michael Schiller
    http://arxiv.org/abs/2110.08592v1

    • [cs.DL]Deep forecasting of translational impact in medical research
    Amy PK Nelson, Robert J Gray, James K Ruffle, Henry C Watkins, Daniel Herron, Nick Sorros, Danil Mikhailov, M. Jorge Cardoso, Sebastien Ourselin, Nick McNally, Bryan Williams, Geraint E. Rees, Parashkev Nachev
    http://arxiv.org/abs/2110.08904v1

    • [cs.DL]Return migration of German-affiliated researchers: Analyzing departure and return by gender, cohort, and discipline using Scopus bibliometric data 1996-2020
    Xinyi Zhao, Samin Aref, Emilio Zagheni, Guy Stecklov
    http://arxiv.org/abs/2110.08340v1

    • [cs.DL]Statistics in everyone’s backyard: an impact study via citation network analysis
    Lijia Wang, Xin Tong, Y. X. Rachel Wang
    http://arxiv.org/abs/2110.08605v1

    • [cs.DS]Dimensionality Reduction for Wasserstein Barycenter
    Zachary Izzo, Sandeep Silwal, Samson Zhou
    http://arxiv.org/abs/2110.08991v1

    • [cs.DS]Terminal Embeddings in Sublinear Time
    Yeshwanth Cherapanamjeri, Jelani Nelson
    http://arxiv.org/abs/2110.08691v1

    • [cs.FL]What can we learn from universal Turing machines?
    Maurice Margenstern
    http://arxiv.org/abs/2110.08511v1

    • [cs.HC]Comparing Deep Neural Nets with UMAP Tour
    Mingwei Li, Carlos Scheidegger
    http://arxiv.org/abs/2110.09431v1

    • [cs.HC]MAAD: A Model and Dataset for “Attended Awareness” in Driving
    Deepak Gopinath, Guy Rosman, Simon Stent, Katsuya Terahata, Luke Fletcher, Brenna Argall, John Leonard
    http://arxiv.org/abs/2110.08610v1

    • [cs.IR]Context-aware Reranking with Utility Maximization for Recommendation
    Yunjia Xi, Weiwen Liu, Xinyi Dai, Ruiming Tang, Weinan Zhang, Qing Liu, Xiuqiang He, Yong Yu
    http://arxiv.org/abs/2110.09059v1

    • [cs.IR]Demographic Biases of Crowd Workers in Key Opinion Leaders Finding
    Hossein A. Rahmani, Jie Yang
    http://arxiv.org/abs/2110.09248v1

    • [cs.IR]Learning to Learn a Cold-start Sequential Recommender
    Xiaowen Huang, Jitao Sang, Jian Yu, Changsheng Xu
    http://arxiv.org/abs/2110.09083v1

    • [cs.IR]Low-Precision Quantization for Efficient Nearest Neighbor Search
    Anthony Ko, Iman Keivanloo, Vihan Lakshman, Eric Schkufza
    http://arxiv.org/abs/2110.08919v1

    • [cs.IR]Prioritization of COVID-19-related literature via unsupervised keyphrase extraction and document representation learning
    Blaž Škrlj, Marko Jukič, Nika Eržen, Senja Pollak, Nada Lavrač
    http://arxiv.org/abs/2110.08874v1

    • [cs.IR]Revisiting Popularity and Demographic Biases in Recommender Evaluation and Effectiveness
    Nicola Neophytou, Bhaskar Mitra, Catherine Stinson
    http://arxiv.org/abs/2110.08353v1

    • [cs.IR]Towards More Accountable Search Engines: Online Evaluation of Representation Bias
    Aldo Lipani, Florina Piroi, Emine Yilmaz
    http://arxiv.org/abs/2110.08835v1

    • [cs.IT]A Framework of Mahalanobis-Distance Metric with Supervised Learning for Clustering Multipath Components in MIMO Channel Analysis
    Yi Chen, Chong Han, Jia He, Guangjian Wang
    http://arxiv.org/abs/2110.08768v1

    • [cs.IT]A Primer on the Statistical Relation between Wireless Ultra-Reliability and Location Estimation
    Tobias Kallehauge, Pablo Ramírez-Espinosa, Kimmo Kansanen, Henk Wymeersch, Petar Popovski
    http://arxiv.org/abs/2110.09215v1

    • [cs.IT]A Q-Learning-based Approach for Distributed Beam Scheduling in mmWave Networks
    Xiang Zhang, Shamik Sarkar, Arupjyoti Bhuyan, Sneha Kumar Kasera, Mingyue Ji
    http://arxiv.org/abs/2110.08704v1

    • [cs.IT]Affine Hermitian Grassmann Codes
    Fernando Piñero González, Doel Rivera Laboy
    http://arxiv.org/abs/2110.08964v1

    • [cs.IT]Capacity Region Bounds for the K user Dispersive Nonlinear Optical WDM Channel with Peak Power Constraints
    Viswanathan Ramachandran, Gabriele Liga, Astrid Barreiro, Alex Alvarado
    http://arxiv.org/abs/2110.09405v1

    • [cs.IT]Coverage Probability of Double-IRS Assisted Communication Systems
    Anastasios Papazafeiropoulos, Pandelis Kourtessis, Symeon Chatzinotas, John M. Senior
    http://arxiv.org/abs/2110.08317v1

    • [cs.IT]DNA Codes over the Ring 今日学术视野(2021.10.20) - 图3
    Adel Alahmadi, Krishna Gopal Benerjee, Sourav Deb, Manish K Gupta
    http://arxiv.org/abs/2110.09089v1

    • [cs.IT]Deep Learning-Based Power Control for Uplink Cell-Free Massive MIMO Systems
    Yongshun Zhang, Jiayi Zhang, Yu Jin, Stefano Buzzi, Bo Ai
    http://arxiv.org/abs/2110.09001v1

    • [cs.IT]Deep Reinforcement Learning for Practical Phase Shift Optimization in RIS-aided MISO URLLC Systems
    Ramin Hashemi, Samad Ali, Nurul Huda Mahmood, Matti Latva-aho
    http://arxiv.org/abs/2110.08513v1

    • [cs.IT]Joint Spatial Division and Coaxial Multiplexing for Downlink Multi-User OAM Wireless Backhaul
    Wen-Xuan Long, Rui Chen, Marco Moretti, Jian Xiong, Jiandong Li
    http://arxiv.org/abs/2110.09123v1

    • [cs.IT]Location Information Assisted Beamforming Design for Reconfigurable Intelligent Surface Aided Communication Systems
    Zhe Xing, Rui Wang, Xiaojun Yuan, Jun Wu
    http://arxiv.org/abs/2110.08980v1

    • [cs.IT]Multifractal of mass function
    Chenhui Qiang, Yong Deng
    http://arxiv.org/abs/2110.08716v1

    • [cs.IT]Novel Secret-Key-Assisted Schemes for Secure MISOME-OFDM Systems
    Mohamed Marzban, Ahmed El Shafie, Naofal Al-Dhahir
    http://arxiv.org/abs/2110.08707v1

    • [cs.IT]Reconfigurable Intelligent Surface-Enhanced OFDM Communications via Delay Adjustable Metasurface
    Jiancheng An, Chao Xu, Derrick Wing Kwan Ng, Chau Yuen, Lu Gan, Lajos Hanzo
    http://arxiv.org/abs/2110.09291v1

    • [cs.IT]Spectral Efficiency of OTFS Based Orthogonal Multiple Access with Rectangular Pulses
    Venkatesh Khammammetti, Saif Khan Mohammed
    http://arxiv.org/abs/2110.08746v1

    • [cs.IT]System Outage Probability and Diversity Analysis of SWIPT Enabled Two-Way DF Relaying under Hardware Impairments
    Guangyue Lu, Zhipeng Liu, Yinghui Ye, Xiaoli Chu
    http://arxiv.org/abs/2110.08865v1

    • [cs.IT]The search of Type I codes
    Carolin Hannusch, Roland S. Major
    http://arxiv.org/abs/2110.09244v1

    • [cs.LG]A Dimensionality Reduction Approach for Convolutional Neural Networks
    Laura Meneghetti, Nicola Demo, Gianluigi Rozza
    http://arxiv.org/abs/2110.09163v1

    • [cs.LG]A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization
    Donghao Ying, Yuhao Ding, Javad Lavaei
    http://arxiv.org/abs/2110.08923v1

    • [cs.LG]A Heterogeneous Graph Based Framework for Multimodal Neuroimaging Fusion Learning
    Gen Shi, Yifan Zhu, Wenjin Liu, Xuesong Li
    http://arxiv.org/abs/2110.08465v1

    • [cs.LG]A Riemannian Mean Field Formulation for Two-layer Neural Networks with Batch Normalization
    Chao Ma, Lexing Ying
    http://arxiv.org/abs/2110.08725v1

    • [cs.LG]Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
    Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen
    http://arxiv.org/abs/2110.08450v1

    • [cs.LG]Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications
    Bang Wu, Xiangwen Yang, Shirui Pan, Xingliang Yuan
    http://arxiv.org/abs/2110.08760v1

    • [cs.LG]An LSTM-based Plagiarism Detection via Attention Mechanism and a Population-based Approach for Pre-Training Parameters with imbalanced Classes
    Seyed Vahid Moravvej, Seyed Jalaleddin Mousavirad, Mahshid Helali Moghadam, Mehrdad Saadatmand
    http://arxiv.org/abs/2110.08771v1

    • [cs.LG]Beltrami Flow and Neural Diffusion on Graphs
    Benjamin Paul Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M Bronstein
    http://arxiv.org/abs/2110.09443v1

    • [cs.LG]Black-box Adversarial Attacks on Network-wide Multi-step Traffic State Prediction Models
    Bibek Poudel, Weizi Li
    http://arxiv.org/abs/2110.08712v1

    • [cs.LG]Capsule Graph Neural Networks with EM Routing
    Yu Lei, Jing Zhang
    http://arxiv.org/abs/2110.09039v1

    • [cs.LG]Centroid Approximation for Bootstrap
    Mao Ye, Qiang Liu
    http://arxiv.org/abs/2110.08720v1

    • [cs.LG]Classical-to-Quantum Transfer Learning for Spoken Command Recognition Based on Quantum Neural Networks
    Jun Qi, Javier Tejedor
    http://arxiv.org/abs/2110.08689v1

    • [cs.LG]Compositional Attention: Disentangling Search and Retrieval
    Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
    http://arxiv.org/abs/2110.09419v1

    • [cs.LG]Correlation-based Discovery of Disease Patterns for Syndromic Surveillance
    Michael Rapp, M
    b60
    oritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
    http://arxiv.org/abs/2110.09208v1

    • [cs.LG]DFW-PP: Dynamic Feature Weighting based Popularity Prediction for Social Media Content
    Viswanatha Reddy G, Chaitanya B S N V, Prathyush P, Sumanth M, Mrinalini C, Dileep Kumar P, Snehasis Mukherjee
    http://arxiv.org/abs/2110.08510v1

    • [cs.LG]DPNAS: Neural Architecture Search for Deep Learningwith Differential Privacy
    Anda Cheng, Jiaxing Wang, Xi Sheryl Zhang, Qiang Chen, Peisong Wang, Jian Cheng
    http://arxiv.org/abs/2110.08557v1

    • [cs.LG]Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization
    Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong
    http://arxiv.org/abs/2110.08896v1

    • [cs.LG]Data Driven and Visualization based Strategization for University Rank Improvement using Decision Trees
    Nishi Doshi, Samhitha Gundam, Bhaskar Chaudhury
    http://arxiv.org/abs/2110.09050v1

    • [cs.LG]Deep Active Learning by Leveraging Training Dynamics
    Haonan Wang, Wei Huang, Andrew Margenot, Hanghang Tong, Jingrui He
    http://arxiv.org/abs/2110.08611v1

    • [cs.LG]Deep Learning and Spectral Embedding for Graph Partitioning
    Alice Gatti, Zhixiong Hu, Tess Smidt, Esmond G. Ng, Pieter Ghysels
    http://arxiv.org/abs/2110.08614v1

    • [cs.LG]Demystifying How Self-Supervised Features Improve Training from Noisy Labels
    Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu
    http://arxiv.org/abs/2110.09022v1

    • [cs.LG]Developing a novel fair-loan-predictor through a mul
    f9b
    ti-sensitive debiasing pipeline: DualFair
    Arashdeep Singh, Jashandeep Singh, Ariba Khan, Amar Gupta
    http://arxiv.org/abs/2110.08944v1

    • [cs.LG]Discovering and Achieving Goals via World Models
    Russell Mendonca, Oleh Rybkin, Kostas Daniilidis, Danijar Hafner, Deepak Pathak
    http://arxiv.org/abs/2110.09514v1

    • [cs.LG]Dynamic Graph Echo State Networks
    Domenico Tortorella, Alessio Micheli
    http://arxiv.org/abs/2110.08565v1

    • [cs.LG]Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient
    Shanchao Yang, Kaili Ma, Baoxiang Wang, Hongyuan Zha
    http://arxiv.org/abs/2110.09035v1

    • [cs.LG]EmbRace: Accelerating Sparse Communication for Distributed Training of NLP Neural Networks
    Shengwei Li, Zhiquan Lai, Dongsheng Li, Xiangyu Ye, Yabo Duan
    http://arxiv.org/abs/2110.09132v1

    • [cs.LG]Equivariant Discrete Normalizing Flows
    Avishek Joey Bose, Ivan Kobyzev
    http://arxiv.org/abs/2110.08649v1

    • [cs.LG]Explaining generalization in deep learning: progress and fundamental limits
    Vaishnavh Nagarajan
    http://arxiv.org/abs/2110.08922v1

    • [cs.LG]Exploiting Domain-Specific Features to Enhance Domain Generalization
    Manh-Ha Bui, Toan Tran, Anh Tuan Tran, Dinh Phung
    http://arxiv.org/abs/2110.09410v1

    • [cs.LG]Exploring Deep Neural Networks on Edge TPU
    Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Brano Kusy, Raja Jurdak, Marius Portmann
    http://arxiv.org/abs/2110.08826v1

    • [cs.LG]Fair Tree Learning
    António Pereira Barata, Cor J. Veenman
    http://arxiv.org/abs/2110.09295v1

    • [cs.LG]FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
    Yan Shen, Jian Du, Hao Zhang, Benyu Zhang, Zhanghexuan Ji, Mingchen Gao
    http://arxiv.org/abs/2110.08477v1

    • [cs.LG]Finding Everything within Random Binary Networks
    Kartik Sreenivasan, Shashank Rajput, Jy-yong Sohn, Dimitris Papailiopoulos
    http://arxiv.org/abs/2110.08996v1

    • [cs.LG]Goal Agnostic Planning using Maximum Likelihood Paths in Hypergraph World Models
    Christopher Robinson
    http://arxiv.org/abs/2110.09442v1

    • [cs.LG]GradSign: Model Performance Inference with Theoretical Insights
    Zhihao Zhang, Zhihao Jia
    http://arxiv.org/abs/2110.08616v1

    • [cs.LG]Graph Partner Neural Networks for Semi-Supervised Learning on Graphs
    Langzhang Liang, Cuiyun Gao, Shiyi Chen, Shishi Duan, Yu pan, Junjin Zheng, Lei Wang, Zenglin Xu
    http://arxiv.org/abs/2110.09182v1

    • [cs.LG]Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation
    Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah
    http://arxiv.org/abs/2110.08727v1

    • [cs.LG]Green Simulation Assisted Policy Gradient to Accelerate Stochastic Process Control
    Hua Zheng, Wei Xie, M. Ben Feng
    http://arxiv.org/abs/2110.08902v1

    • [cs.LG]Growing Representation Learning
    Ryan King, Bobak Mortazavi
    http://arxiv.org/abs/2110.08857v1

    • [cs.LG]Hand Gesture Recognition Using Temporal Convolutions and Attention Mechanism
    Elahe Rahimian, Soheil Zabihi, Amir Asif, Dario Farina, S. Farokh Atashzar, Arash Mohammadi
    http://arxiv.org/abs/2110.08717v1

    • [cs.LG]Improving Robustness using Generated Data
    Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy Mann
    http://arxiv.org/abs/2110.09468v1

    • [cs.LG]Intrusion-Free Graph Mixup
    Hongyu Guo, Yongyi Mao
    http://arxiv.org/abs/2110.09344v1

    • [cs.LG]Learning Optimal Conformal Classifiers
    David Stutz, Krishnamurthy, Dvijotham, Ali Taylan Cemgil, Arnaud Doucet
    http://arxiv.org/abs/2110.09192v1

    • [cs.LG]Learning Prototype-oriented Set Representations for Meta-Learning
    Dandan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou, Hongyuan Zha
    http://arxiv.org/abs/2110.09140v1

    • [cs.LG]Learning in High Dimension Always Amounts to Extrapolation
    Randall Balestriero, Jerome Pesenti, Yann LeCun
    http://arxiv.org/abs/2110.09485v1

    • [cs.LG]Learning velocity model for complex media with deep convolutional neural networks
    A. Stankevich, I. Nechepurenko, A. Shevchenko, L. Gremyachikh, A. Ustyuzhanin, A. Vasyukov
    http://arxiv.org/abs/2110.08626v1

    • [cs.LG]Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning
    Yuchen Xiao, Xueguang Lyu, Christopher Amato
    http://arxiv.org/abs/2110.08642v1

    • [cs.LG]Low-rank Matrix Recovery With Unknown Correspondence
    Zhiwei Tang, Tsung-Hui Chang, Xiaojing Ye, Hongyuan Zha
    http://arxiv.org/abs/2110.07959v2

    • [cs.LG]MDP Abstraction with Successor Features
    Dongge Han, Michael Wooldridge, Sebastian Tschiatschek
    http://arxiv.org/abs/2110.09196v1

    • [cs.LG]MEMO: Test Time Robustness via Adaptation and Augmentation
    Marvin Zhang, Sergey Levine, Chelsea Finn
    http://arxiv.org/abs/2110.09506v1

    • [cs.LG]MG-GCN: Scalable Multi-GPU GCN Training Framework
    Muhammed Fatih Balın, Kaan Sancak, Ümit V. Çatalyürek
    http://arxiv.org/abs/2110.08688v1

    • [cs.LG]Mapping illegal waste dumping sites with neural-network classification of satellite imagery
    Devesa, Maria Roberta, Vazquez Brust, H. Antonio
    http://arxiv.org/abs/2110.08599v1

    • [cs.LG]Natural Attribute-based Shift Detection
    Jeonghoon Park, Jimin Hong, Radhika Dua, Daehoon Gwak, Yixuan Li, Jaegul Choo, Edward Choi
    http://arxiv.org/abs/2110.09276v1

    • [cs.LG]NeuralArTS: Structuring Neural Architecture Search with Type Theory
    Robert Wu, Nayan Saxena, Rohan Jain
    http://arxiv.org/abs/2110.08710v1

    • [cs.LG]Noise-Resilient Ensemble Learning using Evidence Accumulation Clustering
    Gaëlle Candel, David Naccache
    http://arxiv.org/abs/2110.09212v1

    • [cs.LG]Noise-robust Clustering
    Rahmat Adesunkanmi, Ratnesh Kumar
    http://arxiv.org/abs/2110.08871v1

    • [cs.LG]On Predictive Explanation of Data Anomalies
    Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
    http://arxiv.org/abs/2110.09467v1

    • [cs.LG]On the Pareto Frontier of Regret Minimization and Best Arm Identification in Stochastic Bandits
    Zixin Zhong, Wang Chi Cheung, Vincent Y. F. Tan
    http://arxiv.org/abs/2110.08627v1

    • [cs.LG]On the Statistical Analysis of Complex Tree-shaped 3D Objects
    Guan Wang, Hamid Laga, Anuj Srivastava
    http://arxiv.org/abs/2110.08693v1

    • [cs.LG]On-board Fault Diagnosis of a Laboratory Mini SR-30 Gas Turbine Engine
    Richa Singh
    http://arxiv.org/abs/2110.08820v1

    • [cs.LG]Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits
    Reda Ouhamma, Rémy Degenne, Pierre Gaillard, Vianney Perchet
    http://arxiv.org/abs/2110.09133v1

    • [cs.LG]Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs
    Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
    http://arxiv.org/abs/2110.08440v1

    • [cs.LG]Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs
    Han Zhong, Zhuoran Yang, Zhaoran Wang Csaba Szepesvári
    http://arxiv.org/abs/2110.08984v1

    • [cs.LG]Physics-guided Deep Markov Models for Learning Nonlinear Dynamical Systems with Uncertainty
    Wei Liu, Zhilu Lai, Kiran Bacsa, Eleni Chatzi
    http://arxiv.org/abs/2110.08607v1

    • [cs.LG]Poisoning Attacks on Fair Machine Learning
    Minh-Hao Van, Wei Du, Xintao Wu, A
    27b
    idong Lu
    http://arxiv.org/abs/2110.08932v1

    • [cs.LG]Protecting Anonymous Speech: A Generative Adversarial Network Methodology for Removing Stylistic Indicators in Text
    Rishi Balakrishnan, Stephen Sloan, Anil Aswani
    http://arxiv.org/abs/2110.09495v1

    • [cs.LG]Provable Hierarchy-Based Meta-Reinforcement Learning
    Kurtland Chua, Qi Lei, Jason D. Lee
    http://arxiv.org/abs/2110.09507v1

    • [cs.LG]Provable RL with Exogenous Distractors via Multistep Inverse Dynamics
    Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford
    http://arxiv.org/abs/2110.08847v1

    • [cs.LG]Real-time Mortality Prediction Using MIMIC-IV ICU Data Via Boosted Nonparametric Hazards
    Zhale Nowroozilarki, Arash Pakbin, James Royalty, Donald K. K. Lee, Bobak J. Mortazavi
    http://arxiv.org/abs/2110.08949v1

    • [cs.LG]Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models
    Leena Chennuru Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar
    http://arxiv.org/abs/2110.09476v1

    • [cs.LG]S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based Networks
    Shiyu Liu, Chong Min John Tan, Mehul Motani
    http://arxiv.org/abs/2110.08764v1

    • [cs.LG]SPAP: Simultaneous Demand Prediction and Planning for Electric Vehicle Chargers in a New City
    Yizong Wang, Dong Zhao, Yajie Ren, Desheng Zhang, Huadong Ma
    http://arxiv.org/abs/2110.09452v1

    • [cs.LG]Self-Supervised Learning for Binary Networks by Joint Classifier Training
    Dahyun Kim, Jonghyun Choi
    http://arxiv.org/abs/2110.08851v1

    • [cs.LG]Self-Supervised Representation Learning: Introduction, Advances and Challenges
    Linus Ericsson, Henry Gouk, Chen Change Loy, Timothy M. Hospedales
    http://arxiv.org/abs/2110.09327v1

    • [cs.LG]Semi-asynchronous Hierarchical Federated Learning for Cooperative Intelligent Transportation Systems
    Qimei Chen, Zehua You, Hao Jiang
    http://arxiv.org/abs/2110.09073v1

    • [cs.LG]Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection
    Koby Bibas, Meir Feder, Tal Hassner
    http://arxiv.org/abs/2110.09246v1

    • [cs.LG]Speeding-Up Back-Propagation in DNN: Approximate Outer Product with Memory
    Eduin E. Hernandez, Stefano Rini, Tolga M. Duman
    http://arxiv.org/abs/2110.09164v1

    • [cs.LG]Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning
    Yuqing Hu, Vincent Gripon, Stéphane Pateux
    http://arxiv.org/abs/2110.09446v1

    • [cs.LG]State-Space Constraints Improve the Generalization of the Differentiable Neural Computer in some Algorithmic Tasks
    Patrick Ofner, Roman Kern
    http://arxiv.org/abs/2110.09138v1

    • [cs.LG]Streaming Decision Trees and Forests
    Haoyin Xu, Jayanta Dey, Sambit Panda, Joshua T. Vogelstein
    http://arxiv.org/abs/2110.08483v1

    • [cs.LG]Tackling the Imbalance for GNNs
    Rui Wang, Weixuan Xiong, Qinghu Hou, Ou Wu
    http://arxiv.org/abs/2110.08690v1

    • [cs.LG]Temporal Knowledge Graph Reasoning Triggered by Memories
    Mengnan Zhao, Lihe Zhang, Yuqiu Kong, Baocai Yin
    http://arxiv.org/abs/2110.08765v1

    • [cs.LG]Topologically Regularized Data Embeddings
    Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys
    http://arxiv.org/abs/2110.09193v1

    • [cs.LG]Towards Better Long-range Time Series Forecasting using Generative Adversarial Networks
    Shiyu Liu, Mehul Motani
    http://arxiv.org/abs/2110.08770v1

    • [cs.LG]Towards Federated Bayesian Network Structure Learning with Continuous Optimization
    Ignavier Ng, Kun Zhang
    http://arxiv.org/abs/2110.09356v1

    • [cs.LG]Towards General Deep Leakage in Federated Learning
    Jiahui Geng, Yongli Mou, Feifei Li, Qing Li, Oya Beyan, Stefan Decker, Chunming Rong
    http://arxiv.org/abs/2110.09074v1

    • [cs.LG]Towards Instance-Optimal Offline Reinforcement Learning with Pessimism
    Ming Yin, Yu-Xiang Wang
    http://arxiv.org/abs/2110.08695v1

    • [cs.LG]Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization
    Tao Sun, Huaming Ling, Zuoqiang Shi, Dongsheng Li, Bao Wang
    http://arxiv.org/abs/2110.09057v1

    • [cs.LG]Transformer with a Mixture of Gaussian Keys
    Tam Nguyen, Tan M. Nguyen, Dung Le, Khuong Nguyen, Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
    http://arxiv.org/abs/2110.08678v1

    • [cs.LG]Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions
    Batuhan Bardak, Mehmet Tan
    http://arxiv.org/abs/2110.08918v1

    • [cs.LG]Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry
    Patrick Hemmer, Niklas Kühl, Jakob Schöffer
    http://arxiv.org/abs/2110.09023v1

    • [cs.LG]When Are Linear Stochastic Bandits Attackable?
    Huazheng Wang, Haifeng Xu, Hongning Wang
    http://arxiv.org/abs/2110.09008v1

    • [cs.LG]pygrank: A Python Package for Graph Node Ranking
    Emmanouil Krasanakis, Symeon Papadopoulos, Ioannis Kompatsiaris, Andreas Symeonidis
    http://arxiv.org/abs/2110.09274v1

    • [cs.LO]Learning First-Order Rules with Relational Path Contrast for Inductive Relation Reasoning
    Yudai Pan, Jun Liu, Lingling Zhang, Xin Hu, Tianzhe Zhao, Qika Lin
    http://arxiv.org/abs/2110.08810v1

    • [cs.LO]Semantics of Conjectures
    Alessio Rolfini
    http://arxiv.org/abs/2110.08920v1

    • [cs.MS]Least Squares on GPUs in Multiple Double Precision
    Jan Verschelde
    http://arxiv.org/abs/2110.08375v1

    • [cs.NE]Backpropagation with Biologically Plausible Spatio-Temporal Adjustment For Training Deep Spiking Neural Networks
    Guobin Shen, Dongcheng Zhao, Yi Zeng
    http://arxiv.org/abs/2110.08858v1

    • [cs.NE]Learning Continuous Chaotic Attractors with a Reservoir Computer
    Lindsay M. Smith, Jason Z. Kim, Zhixin Lu, Dani S. Bassett
    http://arxiv.org/abs/2110.08631v1

    • [cs.NE]Minimal Conditions for Beneficial Local Search
    Mark G Wallace
    http://arxiv.org/abs/2110.08741v1

    • [cs.NE]Result Diversification by Multi-objective Evolutionary Algorithms with Theoretical Guarantees
    Chao Qian, Dan-Xuan Liu, Zhi-Hua Zhou
    http://arxiv.org/abs/2110.09332v1

    • [cs.NI]Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing
    Pinyarash Pinyoanuntapong, Tagore Pothuneedi, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, Pu Wang
    http://arxiv.org/abs/2110.08952v1

    • [cs.RO]A New Approach to Complex Dynamic Geofencing for Unmanned Aerial Vehicles
    Vihangi Vagal, Konstantinos Markantonakis, Carlton Shepherd
    http://arxiv.org/abs/2110.09453v1

    • [cs.RO]A Tactile-enabled Grasping Method for Robotic Fruit Harvesting
    Hongyu Zhou, Xing Wang, Hanwen Kang, Chao Chen
    http://arxiv.org/abs/2110.09051v1

    • [cs.RO]A unified framework for walking and running of bipedal robots
    Mahrokh Ghoddousi Boroujeni, Elham Daneshmand, Ludovic Righetti, Majid Khadiv
    http://arxiv.org/abs/2110.09172v1

    • [cs.RO]Accurate and Robust Object-oriented SLAM with 3D Quadric Landmark Construction in Outdoor Environment
    Rui Tian, Yunzhou Zhang, Yonghui Feng, Linghao Yang, Zhenzhong Cao, Sonya Coleman, Dermot Kerr
    http://arxiv.org/abs/2110.08977v1

    • [cs.RO]CLASP: Constrained Latent Shape Projection for Refining Object Shape from Robot Contact
    Brad Saund, Dmitry Berenson
    http://arxiv.org/abs/2110.08719v1

    • [cs.RO]Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks
    Shushman Choudhury, Kiril Solovey, Mykel Kochenderfer, Marco Pavone
    http://arxiv.org/abs/2110.08802v1

    • [cs.RO]Deep Tactile Experience: Estimating Tactile Sensor Output from Depth Sensor Data
    Karankumar Patel, Soshi Iba, Nawid Jamali
    http://arxiv.org/abs/2110.08946v1

    • [cs.RO]Does human-robot trust need reciprocity?
    Joshua Zonca, Alessandra Sciutti
    http://arxiv.org/abs/org/abs/2110.09359v1

    • [cs.RO]Dynamic Compressed Sensing of Unsteady Flows with a Mobile Robot
    Sachin Shriwastav, Gregory Snyder, Zhuoyuan Song
    http://arxiv.org/abs/2110.08658v1

    • [cs.RO]Electric Vehicle Automatic Charging System Based on Vision-force Fusion
    Dashun Guo, Liang Xie, Hongxiang Yu, Yue Wang, Rong Xiong
    http://arxiv.org/abs/2110.09191v1

    • [cs.RO]Enhancing exploration algorithms for navigation with visual SLAM
    Kirill Muravyev, Andrey Bokovoy, Konstantin Yakovlev
    http://arxiv.org/abs/2110.09156v1

    • [cs.RO]Extended Version of Reactive Task Allocation and Planning of A Heterogeneous Multi-Robot System
    Ziyi Zhou, Dong Jae Lee, Yuki Yoshinaga, Dejun Guo, Ye Zhao
    http://arxiv.org/abs/2110.08436v1

    • [cs.RO]FAR Planner: Fast, Attemptable Route Planner using Dynamic Visibility Update
    Fan Yang, Chao Cao, Hongbiao Zhu, Jean Oh, Ji Zhang
    http://arxiv.org/abs/2110.09460v1

    • [cs.RO]Generative Adversarial Imitation Learning for End-to-End Autonomous Driving on Urban Environments
    Gustavo Claudio Karl Couto, Eric Aislan Antonelo
    http://arxiv.org/abs/2110.08586v1

    • [cs.RO]How Far Two UAVs Should Be subject to Communication Uncertainties
    Quan Quan, Rao Fu, Kai-Yuan
    http://arxiv.org/abs/2110.09391v1

    • [cs.RO]Keypoint-Based Bimanual Shaping of Deformable Linear Objects under Environmental Constraints using Hierarchical Action Planning
    Shengzeng Huo, Anqing Duan, Chengxi Li, Peng Zhou, Wanyu Ma, David Navarro-Alarcon
    http://arxiv.org/abs/2110.08962v1

    • [cs.RO]Learning Cloth Folding Tasks with Refined Flow Based Spatio-Temporal Graphs
    Peng Zhou, Omar Zahra, Anqing Duan, Shengzeng Huo, Zeyu Wu, David Navarro-Alarcon
    http://arxiv.org/abs/2110.08620v1

    • [cs.RO]Lifelong Topological Visual Navigation
    Rey Reza Wiyatno, Anqi Xu, Liam Paull
    http://arxiv.org/abs/2110.08488v1

    • [cs.RO]On-line Optimal Ranging Sensor Deployment for Robotic Exploration
    Luca Santoro, Davide Brunelli, Daniele Fontanelli
    http://arxiv.org/abs/2110.08853v1

    • [cs.RO]Online Motion Planning with Soft Timed Temporal Logic in Dynamic and Unknown Environment
    Zhiliang Li, Mingyu Cai, Shaoping Xiao, Zhen Kan
    http://arxiv.org/abs/2110.09007v1

    • [cs.RO]Partial Hierarchical Pose Graph Optimization for SLAM
    Alexander Korovko, Dmitry Robustov
    http://arxiv.org/abs/2110.08639v1

    • [cs.RO]Probabilistic Inference in Planning for Partially Observable Long Horizon Problems
    Alphonsus Adu-Bredu, Nikhil Devraj, Pin-Han Lin, Zhen Zeng, Odest Chadwicke Jenkins
    http://arxiv.org/abs/2110.09153v1

    • [cs.RO]Reinforcement Learning-Based Coverage Path Planning with Implicit Cellular Decomposition
    Javad Heydari, Olimpiya Saha, Viswanath Ganapathy
    http://arxiv.org/abs/2110.09018v1

    • [cs.RO]Starkit: RoboCup Humanoid KidSize 2021 Worldwide Champion Team Paper
    Egor Davydenko, Ivan Khokhlov, Vladimir Litvinenko, Ilya Ryakin, Ilya Osokin, Azer Babaev
    http://arxiv.org/abs/2110.08377v1

    • [cs.RO]TIP: Task-Informed Motion Prediction for Intelligent Systems
    Xin Huang, Guy Rosman, Ashkan Jasour, Stephen G. McGill, John J. Leonard, Brian C. Williams
    http://arxiv.org/abs/2110.08750v1

    • [cs.RO]Trajectory Optimization for Thermally-Actuated Soft Planar Robot Limbs
    Anthony Wertz, Andrew P. Sabelhaus, Carmel Majidi
    http://arxiv.org/abs/2110.09474v1

    • [cs.RO]sbp-env: A Python Package for Sampling-based Motion Planner and Samplers
    Tin Lai
    http://arxiv.org/abs/2110.08402v1

    • [cs.SD]Deep Clustering For General-Purpose Audio Representations
    Sreyan Ghosh, Sandesh V Katta, Ashish Seth, S. Umesh
    http://arxiv.org/abs/2110.08895v1

    • [cs.SD]FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech Detection
    Zhenyu Zhang, Yewei Gu, Xiaowei Yi, Xianfeng Zhao
    http://arxiv.org/abs/2110.09441v1

    • [cs.SD]Improving End-To-End Modeling for Mispronunciation Detection with Effective Augmentation Mechanisms
    Tien-Hong Lo, Yao-Ting Sung, Berlin Chen
    http://arxiv.org/abs/2110.08731v1

    • [cs.SD]LDNet: Unified Listener Dependent Modeling in MOS Prediction for Synthetic Speech
    Wen-Chin Huang, Erica Cooper, Junichi Yamagishi, Tomoki Toda
    http://arxiv.org/abs/2110.09103v1

    • [cs.SD]Real Additive Margin Softmax for Speaker Verification
    Lantian Li, Ruiqian Nai, Dong Wang
    http://arxiv.org/abs/2110.09116v1

    • [cs.SD]Towards Robust Waveform-Based Acoustic Models
    Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu
    http://arxiv.org/abs/2110.08634v1

    • [cs.SE]AugmentedCode: Examining the Effects of Natural Language Resources in Code Retrieval Models
    Mehdi Bahrami, N. C. Shrikanth, Yuji Mizobuchi, Lei Liu, Masahiro Fukuyori, Wei-Peng Chen, Kazuki Munakata
    http://arxiv.org/abs/2110.08512v1

    • [cs.SE]Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review
    Xinhai Zhang, Jianbo Tao, Kaige Tan, Martin Törngren, José Manuel Gaspar Sánchez, Muhammad Rusyadi Ramli, Xin Tao, Magnus Gyllenhammar, Franz Wotawa, Naveen Mohan, Mihai Nica, Hermann Felbinger
    http://arxiv.org/abs/2110.08664v1

    • [cs.SI]Information Operations in Turkey: Manufacturing Resilience with Free Twitter Accounts
    Maya Merhi, Sarah Rajtmajer, Dongwon Lee
    http://arxiv.org/abs/2110.08976v1

    • [cs.SI]Measuring the influence of beliefs in belief networks
    Aleksandar Tomašević
    http://arxiv.org/abs/2110.09154v1

    • [cs.SI]Robust Correlation Clustering with Asymmetric Noise
    Jimit Majmudar, Stephen Vavasis
    http://arxiv.org/abs/2110.08385v1

    • [cs.SI]Stability evaluation of the Russian sociologists online community: 2011-2018 years
    Aryuna Kim, Daria Maltseva
    http://arxiv.org/abs/2110.08756v1

    • [eess.AS]A Unified Speaker Adaptation Approach for ASR
    Yingzhu Zhao, Chongjia Ni, Cheung-Chi Leung, Shafiq Joty, Eng Siong Chng, Bin Ma
    http://arxiv.org/abs/2110.08545v1

    • [eess.AS]A Variational Bayesian Approach to Learning Latent Variables for Acoustic Knowledge Transfer
    Hu Hu, Sabato Marco Siniscalchi, Chao-Han Huck Yang, Chin-Hui Lee
    http://arxiv.org/abs/2110.08598v1

    • [eess.AS]ASR4REAL: An extended benchmark for speech models
    Morgane Riviere, Jade Copet, Gabriel Synnaeve
    http://arxiv.org/abs/2110.08583v1

    • [eess.AS]Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Features
    Wei-Han Hsu, Bo-Yu Chen, Yi-Hsuan Yang
    http://arxiv.org/abs/2110.08862v1

    • [eess.IV]A deep learning pipeline for localization, differentiation, and uncertainty estimation of liver lesions using multi-phasic and multi-sequence MRI
    Peng Wang, Yuhsuan Wu, Bolin Lai, Xiao-Yun Zhou, Le Lu, Wendi Liu, Huabang Zhou, Lingyun Huang, Jing Xiao, Adam P. Harrison, Ningyang Jia, Heping Hu
    http://arxiv.org/abs/2110.08817v1

    • [eess.IV]An Analysis and Implementation of the HDR+ Burst Denoising Method
    Antoine Monod, Julie Delon, Thomas Veit
    http://arxiv.org/abs/2110.09354v1

    • [eess.IV]Attention W-Net: Improved Skip Connections for better Representations
    Shikhar Mohan, Saumik Bhattacharya, Sayantari Ghosh
    http://arxiv.org/abs/2110.08811v1

    • [eess.IV]BAPGAN: GAN-based Bone Age Progression of Femur and Phalange X-ray Images
    Shinji Nakazawa, Changhee Han, Joe Hasei, Ryuichi Nakahara, Toshifumi Ozaki
    http://arxiv.org/abs/2110.08509v1

    • [eess.IV]Body Part Regression for CT Images
    Sarah Schuhegger
    http://arxiv.org/abs/2110.09148v1

    • [eess.IV]Bridging the gap between paired and unpaired medical image translation
    Pauliina Paavilainen, Saad Ullah Akram, Juho Kannala
    http://arxiv.org/abs/2110.08407v1

    • [eess.IV]CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans
    Shahin Heidarian, Parnian Afshar, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
    http://arxiv.org/abs/2110.08721v1

    • [eess.IV]COVID-19 Detection in Chest X-ray Images Using Swin-Transformer and Transformer in Transformer
    Juntao Jiang, Shuyi Lin
    http://arxiv.org/abs/2110.08427v1

    • [eess.IV]DBSegment: Fast and robust segmentation of deep brain structures — Evaluation of transportability across acquisition domains
    Mehri Baniasadi, Mikkel V. Petersen, Jorge Goncalves, Andreas Horn, Vanja Vlasov, Frank Hertel, Andreas Husch
    http://arxiv.org/abs/2110.09473v1

    • [eess.IV]Data Shapley Value for Handling Noisy Labels: An application in Screening COVID-19 Pneumonia from Chest CT Scans
    Nastaran Enshaei, Moezedin Javad Rafiee, Arash Mohammadi, Farnoosh Naderkhani
    http://arxiv.org/abs/2110.08726v1

    • [eess.IV]Deep Image Debanding
    Raymond Zhou, Shahrukh Athar, Zhongling Wang, Zhou Wang
    http://arxiv.org/abs/2110.08569v1

    • [eess.IV]Deep learning-based detection of intravenous contrast in computed tomography scans
    Zezhong Ye, Jack M. Qian, Ahmed Hosny, Roman Zeleznik, Deborah Plana, Jirapat Likitlersuang, Zhongyi Zhang, Raymond H. Mak, Hugo J. W. L. Aerts, Benjamin H. Kann
    http://arxiv.org/abs/2110.08424v1

    • [eess.IV]Fast Strain Estimation and Frame Selection in Ultrasound Elastography using Machine Learning
    Abdelrahman Zayed, Hassan Rivaz
    http://arxiv.org/abs/2110.08668v1

    • [eess.IV]GAN-based disentanglement learning for chest X-ray rib suppression
    Luyi Han, Yuanyuan Lyu, Cheng Peng, S. Kevin Zhou
    http://arxiv.org/abs/2110.09134v1

    • [eess.IV]Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep Learning
    Taimur Hassan, Bilal Hassan, Muhammad Usman Akram, Shahrukh Hashmi, Abdel Hakim Taguri, Naoufel Werghi
    http://arxiv.org/abs/2110.09319v1

    • [eess.IV]Locally Adaptive Structure and Texture Similarity for Image Quality Assessment
    Keyan Ding, Yi Liu, Xueyi Zou, Shiqi Wang, Kede Ma
    http://arxiv.org/abs/2110.08521v1

    • [eess.IV]Rheumatoid Arthritis: Automated Scoring of Radiographic Joint Damage
    Yan Ming Tan, Raphael Quek Hao Chong, Carol Anne Hargreaves
    http://arxiv.org/abs/2110.08812v1

    • [eess.IV]SAGAN: Adversarial Spatial-asymmetric Attention for Noisy Nona-Bayer Reconstruction
    S M A Sharif, Rizwan Ali Naqvi, Mithun Biswas
    http://arxiv.org/abs/2110.08619v1

    • [eess.IV]Salt and pepper noise removal method based on stationary Framelet transform with non-convex sparsity regularization
    Yingpin Chen, Lingzhi Wang, Huiying Huang, Jianhua Song, Chaoqun Yu, Yanping Xu
    http://arxiv.org/abs/2110.09113v1

    • [eess.IV]Self-Supervised U-Net for Segmenting Flat and Sessile Polyps
    Debayan Bhattacharya, Christian Betz, Dennis Eggert, Alexander Schlaefer
    http://arxiv.org/abs/2110.08776v1

    • [eess.SP]A MIMO Radar-based Few-Shot Learning Approach for Human-ID
    Pascal Weller, Fady Aziz, Sherif Abdulatif, Urs Schneider, Marco F. Huber
    http://arxiv.org/abs/2110.08595v1

    • [eess.SP]Unsupervised Learned Kalman Filtering
    Guy Revach, Nir Shlezinger, Timur Locher, Xiaoyong Ni, Ruud J. G. van Sloun, Yonina C. Eldar
    http://arxiv.org/abs/2110.09005v1

    • [eess.SY]Improving Robustness of Reinforcement Learning for Power System Control with Adversarial Training
    Alexander Pan, Yongkyun, Lee, Huan Zhang, Yize Chen, Yuanyuan Shi
    http://arxiv.org/abs/2110.08956v1

    • [eess.SY]MARTINI: Smart Meter Driven Estimation of HVAC Schedules and Energy Savings Based on WiFi Sensing and Clustering
    Kingsley Nweye, Zoltan Nagy
    http://arxiv.org/abs/2110.08927v1

    • [gr-qc]Gravitational wave surrogates through automated machine learning
    Damián Barsotti, Franco Cerino, Manuel Tiglio, Aarón Villanueva
    http://arxiv.org/abs/2110.08901v1

    • [math.OC]A portfolio approach to massively parallel Bayesian optimization
    Mickael Binois, Nicholson Collier, Jonathan Ozik
    http://arxiv.org/abs/2110.09334v1

    • [math.OC]A theoretical and empirical study of new adaptive algorithms with additional momentum steps and shifted updates for stochastic non-convex optimization
    Cristian Daniel Alecsa
    http://arxiv.org/abs/2110.08531v1

    • [math.OC]An actor-critic algorithm with deep double recurrent agents to solve the job shop scheduling problem
    Marta Monaci, Valerio Agasucci, Giorgio Grani
    http://arxiv.org/abs/2110.09076v1

    • [math.OC]Computing Semilinear Sparse Models for Approximately Eventually Periodic Signals
    Fredy Vides
    http://arxiv.org/abs/2110.08966v1

    • [math.OC]Fast Projection onto the Capped Simplex withApplications to Sparse Regression in Bioinformatics
    Andersen Ang, Jianzhu Ma, Nianjun Liu, Kun Huang, Yijie Wang
    http://arxiv.org/abs/2110.08471v1

    • [math.OC]Koopman Operator Theory for Nonlinear Dynamic Modeling using Dynamic Mode Decomposition
    Gregory Snyder, Zhuoyuan Song
    http://arxiv.org/abs/2110.08442v1

    • [math.OC]Nys-Curve: Nyström-Approximated Curvature for Stochastic Optimization
    Hardik Tankaria, Dinesh Singh, Makoto Yamada
    http://arxiv.org/abs/2110.08577v1

    • [math.OC]Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto Set
    Mao Ye, Qiang Liu
    http://arxiv.org/abs/2110.08713v1

    • [math.ST]Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches
    Shaogao Lv, Xin He, Junhui Wang
    http://arxiv.org/abs/2110.09042v1

    • [math.ST]Minimum 今日学术视野(2021.10.20) - 图4-norm interpolators: Precise asymptotics and multiple descent
    Yue Li, Yuting Wei
    http://arxiv.org/abs/2110.09502v1

    • [math.ST]On minimax estimation problem for stationary stochastic sequences from observations in special sets of points
    Oleksandr Masyutka, Mikhail Moklyachuk
    http://arxiv.org/abs/2110.08766v1

    • [math.ST]Regression with Missing Data, a Comparison Study of TechniquesBased on Random Forests
    Irving Gómez-Méndez, Emilien Joly
    http://arxiv.org/abs/2110.09333v1

    • [math.ST]Spectral measures of empirical autocovariance matrices of high dimensional Gaussian stationary processes
    Arup Bose, Walid Hachem
    http://arxiv.org/abs/2110.08523v1

    • [physics.ao-ph]Graph-based Local Climate Classification in Iran
    Neda Akrami, Koorush Ziarati, Soumyabrata Dev
    http://arxiv.org/abs/2110.09209v1

    • [physics.soc-ph]Directed Percolation in Random Temporal Network Models with Heterogeneities
    Arash Badie-Modiri, Abbas K. Rizi, Márton Karsai, Mikko Kivelä
    http://arxiv.org/abs/2110.07698v2

    • [physics.soc-ph]Understanding the network formation pattern for better link prediction
    Jiating Yu, Ling-Yun Wu
    http://arxiv.org/abs/2110.08850v1

    • [q-bio.PE]Estimating individual admixture from finite reference databases
    Peter Pfaffelhuber, Angelika Rohde
    http://arxiv.org/abs/2110.08348v1

    • [q-fin.CP]Sector Volatility Prediction Performance Using GARCH Models and Artificial Neural Networks
    Curtis Nybo
    http://arxiv.org/abs/2110.09489v1

    • [q-fin.TR]Understanding jumps in high frequency digital asset markets
    Danial Saef, Odett Nagy, Sergej Sizov, Wolfgang Karl Härdle
    http://arxiv.org/abs/2110.09429v1

    • [quant-ph]Quantum Error Correction with Reflexive Stabilizer Codes and Cayley Graphs
    Robert Vandermolen, Duncan Wright
    http://arxiv.org/abs/2110.08414v1

    • [stat.AP]A Bayesian Selection Model for Correcting Outcome Reporting Bias With Application to a Meta-analysis on Heart Failure Interventions
    Ray Bai, Xiaokang Liu, Lifeng Lin, Yulun Liu, Stephen E. Kimmel, Haitao Chu, Yong Chen
    http://arxiv.org/abs/2110.08849v1

    • [stat.AP]A Space-time Model for Inferring A Susceptibility Map for An Infectious Disease
    Xiaoxiao Li, Matthew Ferrari, Michael J. Tildesley, Murali Haran
    http://arxiv.org/abs/2110.09013v1

    • [stat.AP]Assessing Ecosystem State Space Models: Identifiability and Estimation
    John W. Smith, Leah R. Johnson, Robert Q. Thomas
    http://arxiv.org/abs/2110.08967v1

    • [stat.AP]Building Degradation Index with Variable Selection for Multivariate Sensory Data
    Yueyao Wang, I-Chen Lee, Yili Hong, Xinwei Deng
    http://arxiv.org/abs/2110.08882v1

    • [stat.AP]Exploitation of error correlation in a large analysis validation: GlobCurrent case study
    Richard E. Danielson, Johnny A. Johannessen, Graham D. Quartly, Marie-Hélène Rio, Bertrand Chapron, Fabrice Collard, Craig Donlon
    http://arxiv.org/abs/2110.08905v1

    • [stat.AP]Gradient boosting with extreme-value theory for wildfire prediction
    Jonathan Koh
    http://arxiv.org/abs/2110.09497v1

    • [stat.AP]Minding non-collapsibility of odds ratios when recalibrating risk prediction models
    Mohsen Sadatsafavi, Hamid Tavakoli1, Abdollah Safari
    http://arxiv.org/abs/2110.08648v1

    • [stat.AP]On completing a measurement model by symmetry
    Richard E. Danielson
    http://arxiv.org/abs/2110.08969v1

    • [stat.AP]Spatio-temporal extreme event modeling of terror insurgencies
    Lekha Patel, Lyndsay Shand, J. Derek Tucker, Gabriel Huerta
    http://arxiv.org/abs/2110.08363v1

    • [stat.ME]A Bayesian approach to multi-task learning with network lasso
    Kaito Shimamura, Shuichi Kawano
    http://arxiv.org/abs/2110.09040v1

    • [stat.ME]A Reduced-Bias Weighted least square estimation of the Extreme Value Index
    E. Ocran, R. Minkah, K. Doku-Amponsah
    http://arxiv.org/abs/2110.08570v1

    • [stat.ME]Double Robust Mass-Imputation with Matching Estimators
    Ali Furkan Kalay
    http://arxiv.org/abs/2110.09275v1

    • [stat.ME]Exact Bias Correction for Linear Adjustment of Randomized Controlled Trials
    Haoge Chang, Joel Middleton, Peter Aronow
    http://arxiv.org/abs/2110.08425v1

    • [stat.ME]JEL ratio test for independence of time to failure and cause of failure in competing risks
    Sreelakshmy N., Sreedevi E. P
    http://arxiv.org/abs/2110.08747v1

    • [stat.ME]Multi-group Gaussian Processes
    Didong Li, Andrew Jones, Sudipto Banerjee, Barbara E. Engelhardt
    http://arxiv.org/abs/2110.08411v1

    • [stat.ME]Optimal designs for experiments for scalar-on-function linear models
    Dam
    1000
    ianos Michaelides, Maria Adamou, David C. Woods, Antony M. Overstall
    http://arxiv.org/abs/2110.09115v1

    • [stat.ME]Quantile Regression by Dyadic CART
    Oscar Hernan Madrid Padilla, Sabyasachi Chatterjee
    http://arxiv.org/abs/2110.08665v1

    • [stat.ME]Sample size calculations for n-of-1 trials
    Jiabei Yang, Jon A. Steingrimsson, Christopher H. Schmid
    http://arxiv.org/abs/2110.08970v1

    • [stat.ME]Variance Reduction in Stochastic Reaction Networks using Control Variates
    Michael Backenköhler, Luca Bortolussi, Verena Wolf
    http://arxiv.org/abs/2110.09143v1

    • [stat.ML]Adversarial Attacks on Gaussian Process Bandits
    Eric Han, Jonathan Scarlett
    http://arxiv.org/abs/2110.08449v1

    • [stat.ML]Efficient Exploration in Binary and Preferential Bayesian Optimization
    Tristan Fauvel, Matthew Chalk
    http://arxiv.org/abs/2110.09361v1

    • [stat.ML]Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approach
    Yikun Zhang, Yen-Chi Chen
    http://arxiv.org/abs/2110.08505v1

    • [stat.ML]Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling
    Yinan Li, Fang Liu
    http://arxiv.org/abs/2110.08676v1

    • [stat.ML]Nuances in Margin Conditions Determine Gains in Active Learning
    Samory Kpotufe, Gan Yuan, Yunfan Zhao
    http://arxiv.org/abs/2110.08418v1

    • [stat.ML]On Model Selection Consistency of Lasso for High-Dimensional Ising Models on Tree-like Graphs
    Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima
    http://arxiv.org/abs/2110.08500v1

    • [stat.ML]Persuasion by Dimension Reduction
    Semyon Malamud, Andreas Schrimpf
    http://arxiv.org/abs/2110.08884v1

    • [stat.ML]Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning
    Rodolfo S. M. Freitas, Ágatha P. F. Lima, Cheng Chen, Fernando A. Rochinha, Daniel Mira, Xi Jiang
    http://arxiv.org/abs/2110.09360v1

    • [stat.ML]RKHS-SHAP: Shapley Values for Kernel Methods
    Siu Lun Chau, Javier Gonzalez, Dino Sejdinovic
    http://arxiv.org/abs/2110.09167v1

    • [stat.ML]Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules
    Weibin Mo, Zhengling Qi, Yufeng Liu
    http://arxiv.org/abs/2110.08936v1

    • [stat.ML]Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference
    Ryota Sugiyama, Hiroki Toda, Vo Nguyen Le Duy, Yu Inatsu, Ichiro Takeuchi
    http://arxiv.org/abs/2110.08989v1