cond-mat.mtrl-sci - 材料科学
    cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DB - 数据库
    cs.DC - 分布式、并行与集群计算
    cs.DS - 数据结构与算法
    cs.GT - 计算机科学与博弈论
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.MM - 多媒体
    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
    econ.EM - 计量经济学
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    eess.SY - 系统和控制
    math.CO - 组合数学
    math.NA - 数值分析
    math.OC - 优化与控制
    math.ST - 统计理论
    q-bio.GN - 基因组学
    q-bio.QM - 定量方法
    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

    • [cond-mat.mtrl-sci]Complex Spin Hamiltonian Represented by Artificial Neural Network
    • [cs.AI]A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances
    • [cs.AI]A curated, ontology-based, large-scale knowledge graph of artificial intelligence tasks and benchmarks
    • [cs.AI]An Unsupervised Video Game Playstyle Metric via State Discretization
    • [cs.AI]Artificial intelligence for Sustainable Energy: A Contextual Topic Modeling and Content Analysis
    • [cs.AI]Benchmarking Safety Monitors for Image Classifiers with Machine Learning
    • [cs.AI]Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values
    • [cs.AI]Efficiency, Fairness, and Stability in Non-Commercial Peer-to-Peer Ridesharing
    • [cs.AI]Induction, Popper, and machine learning
    • [cs.AI]Learning to Assist Agents by Observing Them
    • [cs.AI]Trustworthy AI: From Principles to Practices
    • [cs.AI]What is understandable in Bayesian network explanations?
    • [cs.CL]A Aelf-supervised Tibetan-chinese Vocabulary Alignment Method Based On Adversarial Learning
    • [cs.CL]A Case Study to Reveal if an Area of Interest has a Trend in Ongoing Tweets Using Word and Sentence Embeddings
    • [cs.CL]A Comparative Study of Sentiment Analysis Using NLP and Different Machine Learning Techniques on US Airline Twitter Data
    • [cs.CL]A Novel Metric for Evaluating Semantics Preservation
    • [cs.CL]Adversarial Examples Generation for Reducing Implicit Gender Bias in Pre-trained Models
    • [cs.CL]Aspect Sentiment Quad Prediction as Paraphrase Generation
    • [cs.CL]Clustering and Network Analysis for the Embedding Spaces of Sentences and Sub-Sentences
    • [cs.CL]DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models
    • [cs.CL]Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics
    • [cs.CL]Improving Zero-shot Multilingual Neural Machine Translation for Low-Resource Languages
    • [cs.CL]Investigating Robustness of Dialog Models to Popular Figurative Language Constructs
    • [cs.CL]Is There More Pattern in Knowledge Graph? Exploring Proximity Pattern for Knowledge Graph Embedding
    • [cs.CL]JuriBERT: A Masked-Language Model Adaptation for French Legal Text
    • [cs.CL]LawSum: A weakly supervised approach for Indian Legal Document Summarization
    • [cs.CL]Leveraging Information Bottleneck for Scientific Document Summarization
    • [cs.CL]LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
    • [cs.CL]Mapping Language to Programs using Multiple Reward Components with Inverse Reinforcement Learning
    • [cs.CL]Minimizing LR(1) State Machines is NP-Hard
    • [cs.CL]Multi-Document Keyphrase Extraction: A Literature Review and the First Dataset
    • [cs.CL]Perhaps PTLMs Should Go to School — A Task to Assess Open Book and Closed Book QA
    • [cs.CL]Probing Language Models for Understanding of Temporal Expressions
    • [cs.CL]Project Debater APIs: Decomposing the AI Grand Challenge
    • [cs.CL]Protagonists’ Tagger in Literary Domain — New Datasets and a Method for Person Entity Linkage
    • [cs.CL]SPaR.txt, a cheap Shallow Parsing approach for Regulatory texts
    • [cs.CL]Sentiment and structure in word co-occurrence networks on Twitter
    • [cs.CL]Simplify Your Law: Using Information Theory to Deduplicate Legal Documents
    • [cs.CL]Structured abbreviation expansion in context
    • [cs.CL]Subtractive mountain clustering algorithm applied to a chatbot to assist elderly people in medication intake
    • [cs.CL]Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark
    • [cs.CL]TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts
    • [cs.CL]The state-of-the-art in text-based automatic personality prediction
    • [cs.CL]TopiOCQA: Open-domain Conversational Question Answeringwith Topic Switching
    • [cs.CL]Towards Theme Detection in Personal Finance Questions
    • [cs.CL]Towards Understanding Persuasion in Computational Argumentation
    • [cs.CL]Unified Likelihood Ratio Estimation for High- to Zero-frequency N-grams
    • [cs.CR]A New Approach for Image Authentication Framework for Media Forensics Purpose
    • [cs.CR]AsymML: An Asymmetric Decomposition Framework for Privacy-Preserving DNN Training and Inference
    • [cs.CR]Automating Privilege Escalation with Deep Reinforcement Learning
    • [cs.CR]One-Bit Matrix Completion with Differential Privacy
    • [cs.CR]SecFL: Confidential Federated Learning using TEEs
    • [cs.CR]Towards General-purpose Infrastructure for Protecting Scientific Data Under Study
    • [cs.CR]Virtual Private Mobile Network with Multiple Gateways for B5G Location Privacy
    • [cs.CV]3d sequential image mosaicing for underwater navigation and mapping
    • [cs.CV]A Robust Scheme for 3D Point Cloud Copy Detection
    • [cs.CV]A free lunch from ViT: Adaptive Attention Multi-scale Fusion Transformer for Fine-grained Visual Recognition
    • [cs.CV]A new weakly supervised approach for ALS point cloud semantic segmentation
    • [cs.CV]Accurate Cup-to-Disc Ratio Measurement with Tight Bounding Box Supervision in Fundus Photography
    • [cs.CV]Adding Quaternion Representations to Attention Networks for Classification
    • [cs.CV]Algorithm Fairness in AI for Medicine and Healthcare
    • [cs.CV]An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset
    • [cs.CV]Anatomical Landmarks Localization for 3D Foot Point Clouds
    • [cs.CV]Anti-aliasing Deep Image Classifiers using Novel Depth Adaptive Blurring and Activation Function
    • [cs.CV]Asking questions on handwritten document collections
    • [cs.CV]Automated Aerial Animal Detection When Spatial Resolution Conditions Are Varied
    • [cs.CV]Automated Seed Quality Testing System using GAN & Active Learning
    • [cs.CV]BPFNet: A Unified Framework for Bimodal Palmprint Alignment and Fusion
    • [cs.CV]Balanced Masked and Standard Face Recognition
    • [cs.CV]BdSL36: A Dataset for Bangladeshi Sign Letters Recognition
    • [cs.CV]Bounding Box Tightness Prior for Weakly Supervised Image Segmentation
    • [cs.CV]CertainNet: Sampling-free Uncertainty Estimation for Object Detection
    • [cs.CV]Classification of Viral Pneumonia X-ray Images with the Aucmedi Framework
    • [cs.CV]Context-Aware Unsupervised Clustering for Person Search
    • [cs.CV]Counterfactual Samples Synthesizing and Training for Robust Visual Question Answering
    • [cs.CV]DARDet: A Dense Anchor-free Rotated Object Detector in Aerial Images
    • [cs.CV]Domain-Specific Bias Filtering for Single Labeled Domain Generalization
    • [cs.CV]Effectiveness of Optimization Algorithms in Deep Image Classification
    • [cs.CV]Enhance Images as You Like with Unpaired Learning
    • [cs.CV]Explainable Event Recognition
    • [cs.CV]FICGAN: Facial Identity Controllable GAN for De-identification
    • [cs.CV]Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation
    • [cs.CV]Fingerprint Matching using the Onion Peeling Approach and Turning Function
    • [cs.CV]GenCo: Generative Co-training on Data-Limited Image Generation
    • [cs.CV]Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild
    • [cs.CV]Implicit and Explicit Attention for Zero-Shot Learning
    • [cs.CV]Inductive Biased Estimation: Learning Generalizations for Identity Transfer
    • [cs.CV]InfiniteForm: A synthetic, minimal bias dataset for fitness applications
    • [cs.CV]Keypoint Communities
    • [cs.CV]Learning Online Visual Invariances for Novel Objects via Super-vised and Self-Supervised Training
    • [cs.CV]Learning Structural Representations for Recipe Generation and Food Retrieval
    • [cs.CV]Light Field Saliency Detection with Dual Local Graph Learning andReciprocative Guidance
    • [cs.CV]Max and Coincidence Neurons in Neural Networks
    • [cs.CV]Optimizing Neural Network for Computer Vision task in Edge Device
    • [cs.CV]PCAM: Product of Cross-Attention Matrices for Rigid Registration of Point Clouds
    • [cs.CV]RoomStructNet: Learning to Rank Non-Cuboidal Room Layouts From Single View
    • [cs.CV]SPEC: Seeing People in the Wild with an Estimated Camera
    • [cs.CV]Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection
    • [cs.CV]Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancement
    • [cs.CV]Spatial Ensemble: a Novel Model Smoothing Mechanism for Student-Teacher Framework
    • [cs.CV]Spatio-Temporal Video Representation Learning for AI Based Video Playback Style Prediction
    • [cs.CV]Translating Images into Maps
    • [cs.CV]Universal Adversarial Spoofing Attacks against Face Recognition
    • [cs.CV]Universal Face Restoration With Memorized Modulation
    • [cs.CV]Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundary
    • [cs.CV]Weakly Supervised Attention-based Models Using Activation Maps for Citrus Mite and Insect Pest Classification
    • [cs.CY]Anonymer Tanz als dekolonialisierende Praxis. Ein embodied Research Versuch
    • [cs.CY]Examining Similar and Ideologically Correlated Imagery in Online Political Communication
    • [cs.CY]Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models
    • [cs.CY]Making Things Explainable vs Explaining: Requirements and Challenges under the GDPR
    • [cs.DB]Dr.Aid: Supporting Data-governance Rule Compliance for Decentralized Collaboration in an Automated Way
    • [cs.DB]Tao: A Learning Framework for Adaptive Nearest Neighbor Search using Static Features Only
    • [cs.DC]A New Acceleration Paradigm for Discrete CosineTransform and Other Fourier-Related Transforms
    • [cs.DC]Be Aware of Your Leaders
    • [cs.DC]Controlling Resource Allocation using Blockchain-Based Delegation
    • [cs.DC]Distributed 今日学术视野(2021.10.6) - 图1-Coloring Plays Hide-and-Seek
    • [cs.DC]Lower Bounds for Induced Cycle Detection in Distributed Computing
    • [cs.DC]Multi-Feasibility Variable Selection
    • [cs.DC]Repttack: Exploiting Cloud Schedulers to Guide Co-Location Attacks
    • [cs.DC]Spindle: Techniques for Optimizing Atomic Multicast on RDMA
    • [cs.DC]TACC: A Full-stack Cloud Computing Infrastructure for Machine Learning Tasks
    • [cs.DS]Clique percolation method: memory efficient almost exact communities
    • [cs.DS]Random Subgraph Detection Using Queries
    • [cs.GT]Inducing Equilibria via Incentives: Simultaneous Design-and-Play Finds Global Optima
    • [cs.GT]Information Elicitation Meets Clustering
    • [cs.HC]Analysis of the Correlation between smartphone usage changes during the COVID-19 pandemic and usage preferences on apps
    • [cs.HC]Generating User-Centred Explanations via Illocutionary Question Answering: From Philosophy to Interfaces
    • [cs.HC]How mass surveillance can crowd out installations of COVID-19 contact tracing apps
    • [cs.IR]A Proposed Conceptual Framework for a Representational Approach to Information Retrieval
    • [cs.IR]Deep Neural Matching Models for Graph Retrieval
    • [cs.IR]Encoder Adaptation of Dense Passage Retrieval for Open-Domain Question Answering
    • [cs.IR]Multiversal Simulacra: Understanding Hypotheticals and Possible Worlds Through Simulation
    • [cs.IR]Person Entity Profiling Framework: Identifying, Integrating and Visualizing Online Freely Available Entity-Related Information
    • [cs.IR]Relation Analysis between Hotel Review Rating Scores and Sentiment Analysis of Reviews by Chinese Tourists Visiting Japan
    • [cs.IR]Unsupervised paradigm for information extraction from transcripts using BERT
    • [cs.IT]A Class of Nonbinary Symmetric Information Bottleneck Problems
    • [cs.IT]A Minimal Intervention Definition of Reverse Engineering a Neural Circuit
    • [cs.IT]A Modified Q-Learning Algorithm for Rate-Profiling of Polarization Adjusted Convolutional (PAC) Codes
    • [cs.IT]A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications
    • [cs.IT]A Unified 3D Beam Training and Tracking Procedure for Terahertz Communication
    • [cs.IT]Age of Changed Information: Content-Aware Status Updating in the Internet of Things
    • [cs.IT]Binary code optimization
    • [cs.IT]Clustering with Respect to the Information Distance
    • [cs.IT]Communication Models for Reconfigurable Intelligent Surfaces: From Surface Electromagnetics to Wireless Networks Optimization
    • [cs.IT]Complete b-symbol weight distribution of some irreducible cyclic codes
    • [cs.IT]Graph Compression with Application to Model Selection
    • [cs.IT]Lifetime Maximization for UAV-Enabled IoT Networks with Cognitive NOMA Transmissions
    • [cs.IT]New families of quantum stabilizer codes from Hermitian self-orthogonal algebraic geometry codes
    • [cs.IT]Optimal Resource Allocation and Beamforming for Two-User MISO WPCNs for a Non-linear Circuit-Based EH Model
    • [cs.IT]Sequences of linear codes where the rate times distance grows rapidly
    • [cs.IT]Skew cyclic codes over 今日学术视野(2021.10.6) - 图2 with derivation
    • [cs.IT]Spiked Covariance Estimation from Modulo-Reduced Measurements
    • [cs.LG]A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning
    • [cs.LG]A Theoretical Overview of Neural Contraction Metrics for Learning-based Control with Guaranteed Stability
    • [cs.LG]ACDC: Online Unsupervised Cross-Domain Adaptation
    • [cs.LG]AI Back-End as a Service for Learning Switching of Mobile Apps between the Fog and the Cloud
    • [cs.LG]ALBU: An approximate Loopy Belief message passing algorithm for LDA to improve performance on small data sets
    • [cs.LG]An AO-ADMM approach to constraining PARAFAC2 on all modes
    • [cs.LG]An Analysis of Super-Net Heuristics in Weight-Sharing NAS
    • [cs.LG]An Empirical Investigation of Learning from Biased Toxicity Labels
    • [cs.LG]Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
    • [cs.LG]BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning
    • [cs.LG]Batch size-invariance for policy optimization
    • [cs.LG]Behaviour-conditioned policies for cooperative reinforcement learning tasks
    • [cs.LG]Beyond Topics: Discovering Latent Healthcare Objectives from Event Sequences
    • [cs.LG]Boost Neural Networks by Checkpoints
    • [cs.LG]Classifying COVID-19 Spike Sequences from Geographic Location Using Deep Learning
    • [cs.LG]Consider the Alternatives: Navigating Fairness-Accuracy Tradeoffs via Disqualification
    • [cs.LG]Consistency Regularization Can Improve Robustness to Label Noise
    • [cs.LG]Contraction Theory for Nonlinear Stability Analysis and Learning-based Control: A Tutorial Overview
    • [cs.LG]Cycle-Consistent World Models for Domain Independent Latent Imagination
    • [cs.LG]Deep Fraud Detection on Non-attributed Graph
    • [cs.LG]Deep Learning for Principal-Agent Mean Field Games
    • [cs.LG]Deep Learning for Rain Fade Prediction in Satellite Communications
    • [cs.LG]DenDrift: A Drift-Aware Algorithm for Host Profiling
    • [cs.LG]DiffNet: Neural Field Solutions of Parametric Partial Differential Equations
    • [cs.LG]Differentiable Spline Approximations
    • [cs.LG]Distributed Learning Approaches for Automated Chest X-Ray Diagnosis
    • [cs.LG]Enhancing Model Robustness and Fairness with Causality: A Regularization Approach
    • [cs.LG]FairFed: Enabling Group Fairness in Federated Learning
    • [cs.LG]Fairness and underspecification in acoustic scene classification: The case for disaggregated evaluations
    • [cs.LG]Fast Line Search for Multi-Task Learning
    • [cs.LG]Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification
    • [cs.LG]Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning
    • [cs.LG]Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information
    • [cs.LG]GROWN: GRow Only When Necessary for Continual Learning
    • [cs.LG]Git: Clustering Based on Graph of Intensity Topology
    • [cs.LG]Graph Pointer Neural Networks
    • [cs.LG]Human-Centered AI for Data Science: A Systematic Approach
    • [cs.LG]HyperTeNet: Hypergraph and Transformer-based Neural Network for Personalized List Continuation
    • [cs.LG]Identifiability in Exact Multilayer Sparse Matrix Factorization
    • [cs.LG]Identifiability in Exact Two-Layer Sparse Matrix Factorization
    • [cs.LG]Incremental Class Learning using Variational Autoencoders with Similarity Learning
    • [cs.LG]Inference-InfoGAN: Inference Independence via Embedding Orthogonal Basis Expansion
    • [cs.LG]Information-Theoretic Generalization Bounds for Iterative Semi-Supervised Learning
    • [cs.LG]Information-theoretic generalization bounds for black-box learning algorithms
    • [cs.LG]Kalman Bayesian Neural Networks for Closed-form Online Learning
    • [cs.LG]Large Batch Experience Replay
    • [cs.LG]Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
    • [cs.LG]Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization
    • [cs.LG]Learning Networked Linear Dynamical Systems under Non-white Excitation from a Single Trajectory
    • [cs.LG]Learning through atypical ‘’phase transitions’’ in overparameterized neural networks
    • [cs.LG]ML4C: Seeing Causality Through Latent Vicinity
    • [cs.LG]Multi-Agent Path Planning Using Deep Reinforcement Learning
    • [cs.LG]On the complexity of the optimal transport problem with graph-structured cost
    • [cs.LG]Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations
    • [cs.LG]Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams
    • [cs.LG]ProTo: Program-Guided Transformer for Program-Guided Tasks
    • [cs.LG]Progressive Transmission and Inference of Deep Learning Models
    • [cs.LG]RAP-Net: Region Attention Predictive Network for Precipitation Nowcasting
    • [cs.LG]Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids
    • [cs.LG]Robust and Decomposable Average Precision for Image Retrieval
    • [cs.LG]Scheduling Optimization Techniques for Neural Network Training
    • [cs.LG]Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning
    • [cs.LG]Simple Recurrent Neural Networks is all we need for clinical events predictions using EHR data
    • [cs.LG]Simple Recurrent Neural Networks is all we need for clinical events predictions using EHR data
    • [cs.LG]Skill Induction and Planning with Latent Language
    • [cs.LG]Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients
    • [cs.LG]Stochastic Anderson Mixing for Nonconvex Stochastic Optimization
    • [cs.LG]SurvTRACE: Transformers for Survival Analysis with Competing Events
    • [cs.LG]TinyFedTL: Federated Transfer Learning on Tiny Devices
    • [cs.LG]Traffic Flow Forecasting with Maintenance Downtime via Multi-Channel Attention-Based Spatio-Temporal Graph Convolutional Networks
    • [cs.LG]Transfer Learning Approaches for Knowledge Discovery in Grid-based Geo-Spatiotemporal Data
    • [cs.LG]Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
    • [cs.LG]Unraveling the graph structure of tabular datasets through Bayesian and spectral analysis
    • [cs.LG]xFAIR: Better Fairness via Model-based Rebalancing of Protected Attributes
    • [cs.MM]Graph Representation Learning for Spatial Image Steganalysis
    • [cs.NE]Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks
    • [cs.NE]Implementation of Parallel Simplified Swarm Optimization in CUDA
    • [cs.NE]Recurrent circuits as multi-path ensembles for modeling responses of early visual cortical neurons
    • [cs.NI]Optimized Graph Based Routing Algorithm for the Angara Interconnect
    • [cs.NI]Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding
    • [cs.NI]Scaling Graph-based Deep Learning models to larger networks
    • [cs.RO]A Deep Learning Approach To Dead-Reckoning Navigation For Autonomous Underwater Vehicles With Limited Sensor Payloads
    • [cs.RO]AB-Mapper: Attention and BicNet Based Multi-agent Path Finding for Dynamic Crowded Environment
    • [cs.RO]AI based Algorithms of Path Planning, Navigation and Control for Mobile Ground Robots and UAVs
    • [cs.RO]Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm
    • [cs.RO]ComOpT: Combination and Optimization for Testing Autonomous Driving Systems
    • [cs.RO]Direct LiDAR Odometry: Fast Localization with Dense Point Clouds
    • [cs.RO]Discovering Synergies for Robot Manipulation with Multi-Task Reinforcement Learning
    • [cs.RO]Enhancing Voluntary Motion with Modular, Backdrivable, Powered Hip and Knee Orthoses
    • [cs.RO]Evolved neuromorphic radar-based altitude controller for an autonomous open-source blimp
    • [cs.RO]Expanding the Design Space for Electrically-Driven Soft Robots through Handed Shearing Auxetics
    • [cs.RO]Fast Uncertainty Quantification for Active Graph SLAM
    • [cs.RO]Geometric Atlas of the Middle Ear and Paranasal Sinuses for Robotic Applications
    • [cs.RO]Geometry-based Graph Pruning for Lifelong SLAM
    • [cs.RO]How To Not Drive: Learning Driving Constraints from Demonstration
    • [cs.RO]Hybrid Event Shaping to Stabilize Periodic Hybrid Orbits
    • [cs.RO]Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning
    • [cs.RO]Mixed Observable RRT: Multi-Agent Mission-Planning in Partially Observable Environments
    • [cs.RO]Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning
    • [cs.RO]Multi-lane Cruising Using Hierarchical Planning and Reinforcement Learning
    • [cs.RO]OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation
    • [cs.RO]Online Incremental Non-Gaussian Inference for SLAM Using Normalizing Flows
    • [cs.RO]Optimal Placement of Roadside Infrastructure Sensors towards Safer Autonomous Vehicle Deployments
    • [cs.RO]Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers
    • [cs.RO]ReDUCE: Reformulation of Mixed Integer Programs using Data from Unsupervised Clusters for Learning Efficient Strategies
    • [cs.RO]SHARP: Shielding-Aware Robust Planning for Safe and Efficient Human-Robot Interaction
    • [cs.RO]Safe Control with Neural Network Dynamic Models
    • [cs.RO]Sensitivity Study of Fiducial-Aided Navigation of Unmanned Aerial Vehicles
    • [cs.RO]Stanford Pupper: A Low-Cost Agile Quadruped Robot for Benchmarking and Education
    • [cs.RO]Stress Testing Autonomous Racing Overtake Maneuvers with RRT
    • [cs.RO]Towards Time-Optimal Tunnel-Following for Quadrotors
    • [cs.RO]Vision-aided Dynamic Quadrupedal Locomotion on Discrete Terrain using Motion Libraries
    • [cs.SD]Building a Noisy Audio Dataset to Evaluate Machine Learning Approaches for Automatic Speech Recognition Systems
    • [cs.SD]On the Interplay Between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis
    • [cs.SD]PL-EESR: Perceptual Loss Based END-TO-END Robust Speaker Representation Extraction
    • [cs.SE]Identifying non-natural language artifacts in bug reports
    • [cs.SI]A Survey of COVID-19 Misinformation: Datasets, Detection Techniques and Open Issues
    • [cs.SI]An Efficient Procedure for Mining Egocentric Temporal Motifs
    • [cs.SI]Application of Social Network Analysis in Evaluating Risk and network resilience of Closed-Loop-Supply-Chain
    • [cs.SI]Do Facial Trait Correlates with Roll Call Voting in Parliament? Using fWHR to Study Performance in Politics
    • [cs.SI]The Cognitive Science of Extremist Ideologies Online
    • [econ.EM]Probabilistic Prediction for Binary Treatment Choice: with focus on personalized medicine
    • [eess.AS]AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks
    • [eess.AS]Decoupling Speaker-Independent Emotions for Voice Conversion Via Source-Filter Networks
    • [eess.AS]End-to-End Complex-Valued Multidilated Convolutional Neural Network for Joint Acoustic Echo Cancellation and Noise Suppression
    • [eess.AS]Multi-task Voice-Activated Framework using Self-supervised Learning
    • [eess.IV]Adaptive Unfolding Total Variation Network for Low-Light Image Enhancement
    • [eess.IV]Artificial Intelligence For Breast Cancer Detection: Trends & Directions
    • [eess.IV]Assessing glaucoma in retinal fundus photographs using Deep Feature Consistent Variational Autoencoders
    • [eess.IV]Attention module improves both performance and interpretability of 4D fMRI decoding neural network
    • [eess.IV]Blindness (Diabetic Retinopathy) Severity Scale Detection
    • [eess.IV]Deep Kernel Representation for Image Reconstruction in PET
    • [eess.IV]Disarranged Zone Learning (DZL): An unsupervised and dynamic automatic stenosis recognition methodology based on coronary angiography
    • [eess.IV]EAR-U-Net: EfficientNet and attention-based residual U-Net for automatic liver segmentation in CT
    • [eess.IV]Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT scans
    • [eess.IV]Light-weight Deformable Registration using Adversarial Learning with Distilling Knowledge
    • [eess.IV]Multi-view SA-LA Net: A framework for simultaneous segmentation of RV on multi-view cardiac MR Images
    • [eess.IV]Synthetic Velocity Mapping Cardiac MRI Coupled with Automated Left Ventricle Segmentation
    • [eess.IV]Welsch Based Multiview Disparity Estimation
    • [eess.SP]A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters
    • [eess.SP]Cloud-Cluster Architecture for Detection in Intermittently Connected Sensor Networks
    • [eess.SP]Economics of Semantic Communication System in Wireless Powered Internet of Things
    • [eess.SP]Quickest Change Detection with Non-stationary and Composite Post-change Distribution
    • [eess.SY]Data-Driven Detection and Identification of IoT-Enabled Load-Altering Attacks in Power Grids
    • [eess.SY]Efficient Modeling of Morphing Wing Flight Using Neural Networks and Cubature Rules
    • [eess.SY]Exploration of AI-Oriented Power System Transient Stability Simulations
    • [eess.SY]Implementation of MPPT Technique of Solar Module with Supervised Machine Learning
    • [eess.SY]Model Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges
    • [eess.SY]Terminal Adaptive Guidance for Autonomous Hypersonic Strike Weapons via Reinforcement Learning
    • [math.CO]Local Orthogonality Dimension
    • [math.NA]Reconstructing group wavelet transform from feature maps with a reproducing kernel iteration
    • [math.OC]A Markov process approach to untangling intention versus execution in tennis
    • [math.OC]Maximum-Entropy Multi-Agent Dynamic Games: Forward and Inverse Solutions
    • [math.ST]Hierarchical Causal Analysis of Natural Languages on a Chain Event Graph
    • [math.ST]Some Statistic and Information-theoretic Results On Arithmetic Average Fusion
    • [math.ST]Volatility prediction comparison via robust volatility proxies: An empirical deviation perspective
    • [q-bio.GN]A mixture model for determining SARS-Cov-2 variant composition in pooled samples
    • [q-bio.GN]A systematic evaluation of methods for cell phenotype classification using single-cell RNA sequencing data
    • [q-bio.QM]3D-Transformer: Molecular Representation with Transformer in 3D Space
    • [q-bio.QM]Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
    • [q-bio.QM]Motif-based Graph Self-Supervised Learning forMolecular Property Prediction
    • [q-bio.QM]Pharmacoprint — a combination of pharmacophore fingerprint and artificial intelligence as a tool for computer-aided drug design
    • [quant-ph]Maximum-Likelihood Quantum State Tomography by Cover’s Method with Non-Asymptotic Analysis
    • [quant-ph]Quantum Max-Flow Min-Cut theorem
    • [quant-ph]Variational learning of quantum ground states on spiking neuromorphic hardware
    • [stat.AP]Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS
    • [stat.AP]The Impacts of Mobility on Covid-19 Dynamics: Using Soft and Hard Data
    • [stat.ME]A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint
    • [stat.ME]A causal fused lasso for interpretable heterogeneous treatment effects estimation
    • [stat.ME]A general framework for identification of permissible variable subsets in structured model selection
    • [stat.ME]A non-parametric Bayesian approach for adjusting partial compliance in sequential decision making
    • [stat.ME]Bayesian Model-Averaged Meta-Analysis in Medicine
    • [stat.ME]COFFEE: COVID-19 Forecasts using Fast Evaluations and Estimation
    • [stat.ME]Data Integration in Causal Inference
    • [stat.ME]Functional outlier detection for density-valued data with application to robustify distribution to distribution regression
    • [stat.ME]Graph-based multiple change-point detection
    • [stat.ME]Multi-linear Tensor Autoregressive Models
    • [stat.ME]Online Control of the False Discovery Rate under “Decision Deadlines”
    • [stat.ME]Online multiple testing with super-uniformity reward
    • [stat.ME]Vector or Matrix Factor Model? A Strong Rule Helps!
    • [stat.ML]Active Learning for Contextual Search with Binary Feedbacks
    • [stat.ML]Causality and Generalizability: Identifiability and Learning Methods
    • [stat.ML]Clustering a Mixture of Gaussians with Unknown Covariance
    • [stat.ML]DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization
    • [stat.ML]Factored couplings in multi-marginal optimal transport via difference of convex programming
    • [stat.ML]Generalized Kernel Thinning
    • [stat.ML]Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs
    • [stat.ML]Implicit Riemannian Concave Potential Maps
    • [stat.ML]Marginally calibrated response distributions for end-to-end learning in autonomous driving
    • [stat.ML]Row-clustering of a Point Process-valued Matrix
    • [stat.ML]Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
    • [stat.ML]Treeging

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

    • [cond-mat.mtrl-sci]Complex Spin Hamiltonian Represented by Artificial Neural Network
    Hongyu Yu, Changsong Xu, Feng Lou, L. Bellaiche, Zhenpeng Hu, Xingao Gong, Hongjun Xiang
    http://arxiv.org/abs/2110.00724v1

    • [cs.AI]A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances
    Dieqiao Feng, Carla P. Gomes, Bart Selman
    http://arxiv.org/abs/2110.00898v1

    • [cs.AI]A curated, ontology-based, large-scale knowledge graph of artificial intelligence tasks and benchmarks
    Kathrin Blagec, Simon Ott, Adriano Barbosa da Silva, Matthias Samwald
    http://arxiv.org/abs/2110.01434v1

    • [cs.AI]An Unsupervised Video Game Playstyle Metric via State Discretization
    Chiu-Chou Lin, Wei-Chen Chiu, I-Chen Wu
    http://arxiv.org/abs/2110.00950v1

    • [cs.AI]Artificial intelligence for Sustainable Energy: A Contextual Topic Modeling and Content Analysis
    Tahereh Saheb, Mohammad Dehghani
    http://arxiv.org/abs/2110.00828v1

    • [cs.AI]Benchmarking Safety Monitors for Image Classifiers with Machine Learning
    Raul Sena Ferreira, Jean Arlat, Jeremie Guiochet, Hélène Waeselynck
    http://arxiv.org/abs/2110.01232v1

    • [cs.AI]Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values
    Alexandre Heuillet, Fabien Couthouis, Natalia Díaz-Rodríguez
    http://arxiv.org/abs/2110.01307v1

    • [cs.AI]Efficiency, Fairness, and Stability in Non-Commercial Peer-to-Peer Ridesharing
    Hoon Oh, Yanhan Tang, Zong Zhang, Alexandre Jacquillat, Fei Fang
    http://arxiv.org/abs/2110.01152v1

    • [cs.AI]Induction, Popper, and machine learning
    Bruce Nielson, Daniel C. Elton
    http://arxiv.org/abs/2110.00840v1

    • [cs.AI]Learning to Assist Agents by Observing Them
    Antti Keurulainen, Isak Westerlund, Samuel Kaski, Alexander Ilin
    http://arxiv.org/abs/2110.01311v1

    • [cs.AI]Trustworthy AI: From Principles to Practices
    Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, Jiquan Pei, Jinfeng Yi, Bowen Zhou
    http://arxiv.org/abs/2110.01167v1

    • [cs.AI]What is understandable in Bayesian network explanations?
    Raphaela Butz, Renée Schulz, Arjen Hommersom, Marko van Eekelen
    http://arxiv.org/abs/2110.01322v1

    • [cs.CL]A Aelf-supervised Tibetan-chinese Vocabulary Alignment Method Based On Adversarial Learning
    Enshuai Hou, Jie zhu
    http://arxiv.org/abs/2110.01258v1

    • [cs.CL]A Case Study to Reveal if an Area of Interest has a Trend in Ongoing Tweets Using Word and Sentence Embeddings
    İsmail Aslan, Yücel Topçu
    http://arxiv.org/abs/2110.00866v1

    • [cs.CL]A Comparative Study of Sentiment Analysis Using NLP and Different Machine Learning Techniques on US Airline Twitter Data
    Md. Taufiqul Haque Khan Tusar, Md. Touhidul Islam
    http://arxiv.org/abs/2110.00859v1

    • [cs.CL]A Novel Metric for Evaluating Semantics Preservation
    Letian Peng, Zuchao Li, Hai Zhao
    http://arxiv.org/abs/2110.01176v1

    • [cs.CL]Adversarial Examples Generation for Reducing Implicit Gender Bias in Pre-trained Models
    Wenqian Ye, Fei Xu, Yaojia Huang, Cassie Huang, Ji A
    http://arxiv.org/abs/2110.01094v1

    • [cs.CL]Aspect Sentiment Quad Prediction as Paraphrase Generation
    Wenxuan Zhang, Yang Deng, Xin Li, Yifei Yuan, Lidong Bing, Wai Lam
    http://arxiv.org/abs/2110.00796v1

    • [cs.CL]Clustering and Network Analysis for the Embedding Spaces of Sentences and Sub-Sentences
    Yuan An, Alexander Kalinowski, Jane Greenberg
    http://arxiv.org/abs/2110.00697v1

    • [cs.CL]DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models
    Gregor Betz, Kyle Richardson
    http://arxiv.org/abs/2110.01509v1

    • [cs.CL]Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics
    Prajjwal Bhargava, Aleksandr Drozd, Anna Rogers
    http://arxiv.org/abs/2110.01518v1

    • [cs.CL]Improving Zero-shot Multilingual Neural Machine Translation for Low-Resource Languages
    Chenyang Li, Gongxu Luo
    http://arxiv.org/abs/2110.00712v1

    • [cs.CL]Investigating Robustness of Dialog Models to Popular Figurative Language Constructs
    Harsh Jhamtani, Varun Gangal, Eduard Hovy, Taylor Berg-Kirkpatrick
    http://arxiv.org/abs/2110.00687v1

    • [cs.CL]Is There More Pattern in Knowledge Graph? Exploring Proximity Pattern for Knowledge Graph Embedding
    Ren Li, Yanan Cao, Qiannan Zhu, Xiaoxue Li, Fang Fang
    http://arxiv.org/abs/2110.00720v1

    • [cs.CL]JuriBERT: A Masked-Language Model Adaptation for French Legal Text
    Stella Douka, Hadi Abdine, Michalis Vazirgiannis, Rajaa El Hamdani, David Restrepo Amariles
    http://arxiv.org/abs/2110.01485v1

    • [cs.CL]LawSum: A weakly supervised approach for Indian Legal Document Summarization
    Vedant Parikh, Vidit Mathur, Parth Metha, Nimita Mittal, Prasenjit Majumder
    http://arxiv.org/abs/2110.01188v1

    • [cs.CL]Leveraging Information Bottleneck for Scientific Document Summarization
    Jiaxin Ju, Ming Liu, Huan Yee Koh, Yuan Jin, Lan Du, Shirui Pan
    http://arxiv.org/abs/2110.01280v1

    • [cs.CL]LexGLUE: A Benchmark Dataset for Legal Language Understanding in English
    Ilias Chalkidis, Abhik Jana, Dirk Hartung, Michael Bommarito, Ion Androutsopoulos, Daniel Martin Katz, Nikolaos Aletras
    http://arxiv.org/abs/2110.00976v1

    • [cs.CL]Mapping Language to Programs using Multiple Reward Components with Inverse Reinforcement Learning
    Sayan Ghosh, Shashank Srivastava
    http://arxiv.org/abs/2110.00842v1

    • [cs.CL]Minimizing LR(1) State Machines is NP-Hard
    Wuu Yang
    http://arxiv.org/abs/2110.00776v1

    • [cs.CL]Multi-Document Keyphrase Extraction: A Literature Review and the First Dataset
    Ori Shapira, Ramakanth Pasunuru, Ido Dagan, Yael Amsterdamer
    http://arxiv.org/abs/2110.01073v1

    • [cs.CL]Perhaps PTLMs Should Go to School — A Task to Assess Open Book and Closed Book QA
    Manuel R. Ciosici, Joe Cecil, Alex Hedges, Dong-Ho Lee, Marjorie Freedman, Ralph Weischedel
    http://arxiv.org/abs/2110.01552v1

    • [cs.CL]Probing Language Models for Understanding of Temporal Expressions
    Shivin Thukral, Kunal Kukreja, Christian Kavouras
    http://arxiv.org/abs/2110.01113v1

    • [cs.CL]Project Debater APIs: Decomposing the AI Grand Challenge
    Roy Bar-Haim, Yoav Kantor, Elad Venezian, Yoav Katz, Noam Slonim
    http://arxiv.org/abs/2110.01029v1

    • [cs.CL]Protagonists’ Tagger in Literary Domain — New Datasets and a Method for Person Entity Linkage
    Weronika Łajewska, Anna Wróblewska
    http://arxiv.org/abs/2110.01349v1

    • [cs.CL]SPaR.txt, a cheap Shallow Parsing approach for Regulatory texts
    Ruben Kruiper, Ioannis Konstas, Alasdair Gray, Farhad Sadeghineko, Richard Watson, Bimal Kumar
    http://arxiv.org/abs/2110.01295v1

    • [cs.CL]Sentiment and structure in word co-occurrence networks on Twitter
    Mikaela Irene Fudolig, Thayer Alshaabi, Michael V. Arnold, Christopher M. Danforth, Peter Sheridan Dodds
    http://arxiv.org/abs/2110.00587v1

    • [cs.CL]Simplify Your Law: Using Information Theory to Deduplicate Legal Documents
    Corinna Coupette, Jyotsna Singh, Holger Spamann
    http://arxiv.org/abs/2110.00735v1

    • [cs.CL]Structured abbreviation expansion in context
    Kyle Gorman, Christo Kirov, Brian Roark, Richard Sproat
    http://arxiv.org/abs/2110.01140v1

    • [cs.CL]Subtractive mountain clustering algorithm applied to a chatbot to assist elderly people in medication intake
    Neuza Clar, Paulo A. Salgado, T-P Azevedo Perdicoúlis
    http://arxiv.org/abs/2110.00933v1

    • [cs.CL]Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark
    Joel Niklaus, Ilias Chalkidis, Matthias Stürmer
    http://arxiv.org/abs/2110.00806v1

    • [cs.CL]TLDR9+: A Large Scale Resource for Extreme Summarization of Social Media Posts
    Sajad Sotudeh, Hanieh Deilamsalehi, Franck Dernoncourt, Nazli Goharian
    http://arxiv.org/abs/2110.01159v1

    • [cs.CL]The state-of-the-art in text-based automatic personality prediction
    Ali-Reza Feizi-Derakhshi, Mohammad-Reza Feizi-Derakhshi, Majid Ramezani, Narjes Nikzad-Khasmakhi, Meysam Asgari-Chenaghlu, Taymaz Akan, Mehrdad Ranjbar-Khadivi, Elnaz Zafarni-Moattar, Zoleikha Jahanbakhsh-Naghadeh
    http://arxiv.org/abs/2110.01186v1

    • [cs.CL]TopiOCQA: Open-domain Conversational Question Answeringwith Topic Switching
    Vaibhav Adlakha, Shehzaad Dhuliawala, Kaheer Suleman, Harm de Vries, Siva Reddy
    http://arxiv.org/abs/2110.00768v1

    • [cs.CL]Towards Theme Detection in Personal Finance Questions
    John Xi Qiu, Adam Faulkner, Aysu Ezen Can
    http://arxiv.org/abs/2110.01550v1

    • [cs.CL]Towards Understanding Persuasion in Computational Argumentation
    Esin Durmus
    http://arxiv.org/abs/2110.01078v1

    • [cs.CL]Unified Likelihood Ratio Estimation for High- to Zero-frequency N-grams
    Masato Kikuchi, Kento Kawakami, Kazuho Watanabe, Mitsuo Yoshida, Kyoji Umemura
    http://arxiv.org/abs/2110.00946v1

    • [cs.CR]A New Approach for Image Authentication Framework for Media Forensics Purpose
    Ahmad M Nagm, Khaled Y Youssef, Mohammad I Youssef
    http://arxiv.org/abs/2110.01065v1

    • [cs.CR]AsymML: An Asymmetric Decomposition Framework for Privacy-Preserving DNN Training and Inference
    Yue Niu, Ramy E. Ali, Salman Avestimehr
    http://arxiv.org/abs/2110.01229v1

    • [cs.CR]Automating Privilege Escalation with Deep Reinforcement Learning
    Kalle Kujanpää, Willie Victor, Alexander Ilin
    http://arxiv.org/abs/2110.01362v1

    • [cs.CR]One-Bit Matrix Completion with Differential Privacy
    Zhengpin Li, Zheng Wei, Xiaojun Mao, Jian Wang
    http://arxiv.org/abs/2110.00719v1

    • [cs.CR]SecFL: Confidential Federated Learning using TEEs
    Do Le Quoc, Christof Fetzer
    http://arxiv.org/abs/2110.00981v1

    • [cs.CR]Towards General-purpose Infrastructure for Protecting Scientific Data Under Study
    Andrew Trask, Kritika Prakash
    http://arxiv.org/abs/2110.01315v1

    • [cs.CR]Virtual Private Mobile Network with Multiple Gateways for B5G Location Privacy
    Stefano Tomasin, Javier German Luzon Hidalgo
    http://arxiv.org/abs/2110.01195v1

    • [cs.CV]3d sequential image mosaicing for underwater navigation and mapping
    E. Nocerino, F. Menna, B. Chemisky, P. Drap
    http://arxiv.org/abs/2110.01382v1

    • [cs.CV]A Robust Scheme for 3D Point Cloud Copy Detection
    Jiaqi Yang, Xuequan Lu, Wenzhi Chen
    http://arxiv.org/abs/2110.00972v1

    • [cs.CV]A free lunch from ViT: Adaptive Attention Multi-scale Fusion Transformer for Fine-grained Visual Recognition
    Yuan Zhang, Jian Cao, Ling Zhang, Xiangcheng Liu, Zhiyi Wang, Feng Ling, Weiqian Chen
    http://arxiv.org/abs/2110.01240v1

    • [cs.CV]A new weakly supervised approach for ALS point cloud semantic segmentation
    Puzuo Wang, Wei Yao
    http://arxiv.org/abs/2110.01462v1

    • [cs.CV]Accurate Cup-to-Disc Ratio Measurement with Tight Bounding Box Supervision in Fundus Photography
    Juan Wang, Bin Xia
    http://arxiv.org/abs/2110.00943v1

    • [cs.CV]Adding Quaternion Representations to Attention Networks for Classification
    Nazmul Shahadat, Anthony S. Maida
    http://arxiv.org/abs/2110.01185v1

    • [cs.CV]Algorithm Fairness in AI for Medicine and Healthcare
    Richard J. Chen, Tiffany Y. Chen, Jana Lipkova, Judy J. Wang, Drew F. K. Williamson, Ming Y. Lu, Sharifa Sahai, Faisal Mahmood
    http://arxiv.org/abs/2110.00603v1

    • [cs.CV]An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset
    Wanyu Bian, Yunmei Chen, Xiaojing Ye, Qingchao Zhang
    http://arxiv.org/abs/2110.00715v1

    • [cs.CV]Anatomical Landmarks Localization for 3D Foot Point Clouds
    Sheldon Fung, Xuequan Lu, Mantas Mykolaitis, Gediminas Kostkevicius, Domantas Ozerenskis
    http://arxiv.org/abs/2110.00937v1

    • [cs.CV]Anti-aliasing Deep Image Classifiers using Novel Depth Adaptive Blurring and Activation Function
    Md Tahmid Hossain, Shyh Wei Teng, Ferdous Sohel, Guojun Lu
    http://arxiv.org/abs/2110.00899v1

    • [cs.CV]Asking questions on handwritten document collections
    Minesh Mathew, Lluis Gomez, Dimosthenis Karatzas, CV Jawahar
    http://arxiv.org/abs/2110.00711v1

    • [cs.CV]Automated Aerial Animal Detection When Spatial Resolution Conditions Are Varied
    Jasper Brown, Yongliang Qiao, Cameron Clark, Sabrina Lomax, Khalid Rafique, Salah Sukkarieh
    http://arxiv.org/abs/2110.01329v1

    • [cs.CV]Automated Seed Quality Testing System using GAN & Active Learning
    Sandeep Nagar, Prateek Pani, Raj Nair, Girish Varma
    http://arxiv.org/abs/2110.00777v1

    • [cs.CV]BPFNet: A Unified Framework for Bimodal Palmprint Alignment and Fusion
    Zhaoqun Li, Xu Liang, Dandan Fan, Jinxing Li, David Zhang
    http://arxiv.org/abs/2110.01179v1

    • [cs.CV]Balanced Masked and Standard Face Recognition
    Delong Qi, Kangli Hu, Weijun Tan, Qi Yao, Jingfeng Liu
    http://arxiv.org/abs/2110.01521v1

    • [cs.CV]BdSL36: A Dataset for Bangladeshi Sign Letters Recognition
    Oishee Bintey Hoque, Mohammad Imrul Jubair, Al-Farabi Akash, Saiful Islam
    http://arxiv.org/abs/2110.00869v1

    • [cs.CV]Bounding Box Tightness Prior for Weakly Supervised Image Segmentation
    Juan Wang, Bin Xia
    http://arxiv.org/abs/2110.00934v1

    • [cs.CV]CertainNet: Sampling-free Uncertainty Estimation for Object Detection
    Stefano Gasperini, Jan Haug, Mohammad-Ali Nikouei Mahani, Alvaro Marcos-Ramiro, Nassir Navab, Benjamin Busam, Federico Tombari
    http://arxiv.org/abs/2110.01604v1

    • [cs.CV]Classification of Viral Pneumonia X-ray Images with the Aucmedi Framework
    Pia Schneider, Dominik Müller, Frank Kramer
    http://arxiv.org/abs/2110.01017v1

    • [cs.CV]Context-Aware Unsupervised Clustering for Person Search
    Byeong-Ju Han, Kuhyeun Ko, Jae-Young Sim
    http://arxiv.org/abs/2110.01341v1

    • [cs.CV]Counterfactual Samples Synthesizing and Training for Robust Visual Question Answering
    Long Chen, Yuhang Zheng, Yulei Niu, Hanwang Zhang, Jun Xiao
    http://arxiv.org/abs/2110.01013v1

    • [cs.CV]DARDet: A Dense Anchor-free Rotated Object Detector in Aerial Images
    Feng Zhang, Xueying Wang, Shilin Zhou, Yingqian Wang
    http://arxiv.org/abs/2110.01025v1

    • [cs.CV]Domain-Specific Bias Filtering for Single Labeled Domain Generalization
    Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin
    http://arxiv.org/abs/2110.00726v1

    • [cs.CV]Effectiveness of Optimization Algorithms in Deep Image Classification
    Zhaoyang Zhu, Haozhe Sun, Chi Zhang
    http://arxiv.org/abs/2110.01598v1

    • [cs.CV]Enhance Images as You Like with Unpaired Learning
    Xiaopeng Sun, Muxingzi Li, Tianyu He, Lubin Fan
    http://arxiv.org/abs/2110.01161v1

    • [cs.CV]Explainable Event Recognition
    Imran Khan, Kashif Ahmad, Namra Gul, Talhat Khan, Nasir Ahmad, Ala-Al-Fuqaha
    http://arxiv.org/abs/2110.00755v1

    • [cs.CV]FICGAN: Facial Identity Controllable GAN for De-identification
    Yonghyun Jeong, Jooyoung Choi, Sungwon Kim, Youngmin Ro, Tae-Hyun Oh, Doyeon Kim, Heonseok Ha, Sungroh Yoon
    http://arxiv.org/abs/2110.00740v1

    • [cs.CV]Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation
    Dan Yao, Stephen McLaughlin, Yoann Altmann
    http://arxiv.org/abs/2110.01585v1

    • [cs.CV]Fingerprint Matching using the Onion Peeling Approach and Turning Function
    Nazanin Padkan, B. Sadeghi Bigham, Mohammad Reza Faraji
    http://arxiv.org/abs/2110.00958v1

    • [cs.CV]GenCo: Generative Co-training on Data-Limited Image Generation
    Kaiwen Cui, Jiaxing Huang, Zhipeng Luo, Gongjie Zhang, Fangneng Zhan, Shijian Lu
    http://arxiv.org/abs/2110.01254v1

    • [cs.CV]Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild
    Akash Sengupta, Ignas Budvytis, Roberto Cipolla
    http://arxiv.org/abs/2110.00990v1

    • [cs.CV]Implicit and Explicit Attention for Zero-Shot Learning
    Faisal Alamri, Anjan Dutta
    http://arxiv.org/abs/2110.00860v1

    • [cs.CV]Inductive Biased Estimation: Learning Generalizations for Identity Transfer
    Gege Gao, Huaibo Huang, Chaoyou Fu, Ran He
    http://arxiv.org/abs/2110.01571v1

    • [cs.CV]InfiniteForm: A synthetic, minimal bias dataset for fitness applications
    Andrew Weitz, Lina Colucci, Sidney Primas, Brinnae Bent
    http://arxiv.org/abs/2110.01330v1

    • [cs.CV]Keypoint Communities
    Duncan Zauss, Sven Kreiss, Alexandre Alahi
    http://arxiv.org/abs/2110.00988v1

    • [cs.CV]Learning Online Visual Invariances for Novel Objects via Super-vised and Self-Supervised Training
    Valerio Biscione, Jeffrey S. Bowers
    http://arxiv.org/abs/2110.01476v1

    • [cs.CV]Learning Structural Representations for Recipe Generation and Food Retrieval
    Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao
    http://arxiv.org/abs/2110.01209v1

    • [cs.CV]Light Field Saliency Detection with Dual Local Graph Learning andReciprocative Guidance
    Nian Liu, Wangbo Zhao, Dingwen Zhang, Junwei Han, Ling Shao
    http://arxiv.org/abs/2110.00698v1

    • [cs.CV]Max and Coincidence Neurons in Neural Networks
    Albert Lee, Kang L. Wang
    http://arxiv.org/abs/2110.01218v1

    • [cs.CV]Optimizing Neural Network for Computer Vision task in Edge Device
    Ranjith M S, S Parameshwara, Pavan Yadav A, Shriganesh Hegde
    http://arxiv.org/abs/2110.00791v1

    • [cs.CV]PCAM: Product of Cross-Attention Matrices for Rigid Registration of Point Clouds
    Anh-Quan Cao, Gilles Puy, Alexandre Boulch, Renaud Marlet
    http://arxiv.org/abs/2110.01269v1

    • [cs.CV]RoomStructNet: Learning to Rank Non-Cuboidal Room Layouts From Single View
    Xi Zhang, Chun-Kai Wang, Kenan Deng, Tomas Yago-Vicente, Himanshu Arora
    http://arxiv.org/abs/2110.00644v1

    • [cs.CV]SPEC: Seeing People in the Wild with an Estimated Camera
    Muhammed Kocabas, Chun-Hao P. Huang, Joachim Tesch, Lea Müller, Otmar Hilliges, Michael J. Black
    http://arxiv.org/abs/2110.00620v1

    • [cs.CV]Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection
    Farzaneh Rezaeianaran, Rakshith Shetty, Rahaf Aljundi, Daniel Olmeda Reino, Shanshan Zhang, Bernt Schiele
    http://arxiv.org/abs/2110.01428v1

    • [cs.CV]Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancement
    Shen Zheng, Gaurav Gupta
    http://arxiv.org/abs/2110.00970v1

    • [cs.CV]Spatial Ensemble: a Novel Model Smoothing Mechanism for Student-Teacher Framework
    Tengteng Huang, Yifan Sun, Xun Wang, Haotian Yao, Chi Zhang
    http://arxiv.org/abs/2110.01253v1

    • [cs.CV]Spatio-Temporal Video Representation Learning for AI Based Video Playback Style Prediction
    Rishubh Parihar, Gaurav Ramola, Ranajit Saha, Ravi Kini, Aniket Rege, Sudha Velusamy
    http://arxiv.org/abs/2110.01015v1

    • [cs.CV]Translating Images into Maps
    Avishkar Saha, Oscar Mendez Maldonado, Chris Russell, Richard Bowden
    http://arxiv.org/abs/2110.00966v1

    • [cs.CV]Universal Adversarial Spoofing Attacks against Face Recognition
    Takuma Amada, Seng Pei Liew, Kazuya Kakizaki, Toshinori Araki
    http://arxiv.org/abs/2110.00708v1

    • [cs.CV]Universal Face Restoration With Memorized Modulation
    Jia Li, Huaibo Huang, Xiaofei Jia, Ran He
    http://arxiv.org/abs/2110.01033v1

    • [cs.CV]Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundary
    Siyuan Zhou, Li Niu, Jianlou Si, Chen Qian, Liqing Zhang
    http://arxiv.org/abs/2110.01519v1

    • [cs.CV]Weakly Supervised Attention-based Models Using Activation Maps for Citrus Mite and Insect Pest Classification
    Edson Bollis, Helena Maia, Helio Pedrini, Sandra Avila
    http://arxiv.org/abs/2110.00881v1

    • [cs.CY]Anonymer Tanz als dekolonialisierende Praxis. Ein embodied Research Versuch
    Paula Helm
    http://arxiv.org/abs/2110.01089v1

    • [cs.CY]Examining Similar and Ideologically Correlated Imagery in Online Political Communication
    Amogh Joshi, Cody Buntain
    http://arxiv.org/abs/2110.01183v1

    • [cs.CY]Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models
    Robert Wolfe, Aylin Caliskan
    http://arxiv.org/abs/2110.00672v1

    • [cs.CY]Making Things Explainable vs Explaining: Requirements and Challenges under the GDPR
    Francesco Sovrano, Fabio Vitali, Monica Palmirani
    http://arxiv.org/abs/2110.00758v1

    • [cs.DB]Dr.Aid: Supporting Data-governance Rule Compliance for Decentralized Collaboration in an Automated Way
    Rui Zhao, Malcolm Atkinson, Petros Papapanagiotou, Federica Magnoni, Jacques Fleuriot
    http://arxiv.org/abs/2110.01056v1

    • [cs.DB]Tao: A Learning Framework for Adaptive Nearest Neighbor Search using Static Features Only
    Kaixiang Yang, Hongya Wang, Bo Xu, Wei Wang, Yingyuan Xiao, Ming Du, Junfeng Zhou
    http://arxiv.org/abs/2110.00696v1

    • [cs.DC]A New Acceleration Paradigm for Discrete CosineTransform and Other Fourier-Related Transforms
    Zixuan Jiang, Jiaqi Gu, David Z. Pan
    http://arxiv.org/abs/2110.01172v1

    • [cs.DC]Be Aware of Your Leaders
    Shir Cohen, Rati Gelashvili, Lefteris Kokoris Kogias, Zekun Li, Dahlia Malkhi, Alberto Sonnino, Alexander Spiegelman
    http://arxiv.org/abs/2110.00960v1

    • [cs.DC]Controlling Resource Allocation using Blockchain-Based Delegation
    Shantanu Pal, Ambrose Hill, Tahiry Rabehaja, Michael Hitchens
    http://arxiv.org/abs/2110.01162v1

    • [cs.DC]Distributed 今日学术视野(2021.10.6) - 图3-Coloring Plays Hide-and-Seek
    Alkida Balliu, Sebastian Brandt, Fabian Kuhn, Dennis Olivetti
    http://arxiv.org/abs/2110.00643v1

    • [cs.DC]Lower Bounds for Induced Cycle Detection in Distributed Computing
    François Le Gall, Masayuki Miyamoto
    http://arxiv.org/abs/2110.00741v1

    • [cs.DC]Multi-Feasibility Variable Selection
    Ali Fathi, Mohammad Rashid, Shayan Ranjbarzadeh, Mojtaba Tefagh
    http://arxiv.org/abs/2110.00819v1

    • [cs.DC]Repttack: Exploiting Cloud Schedulers to Guide Co-Location Attacks
    Chongzhou Fang, Han Wang, Najmeh Nazari, Behnam Omidi, Avesta Sasan, Khaled N. Khasawneh, Setareh Rafatirad, Houman Homayoun
    http://arxiv.org/abs/2110.00846v1

    • [cs.DC]Spindle: Techniques for Optimizing Atomic Multicast on RDMA
    Sagar Jha, Lorenzo Rosa, Ken Birman
    http://arxiv.org/abs/2110.00886v1

    • [cs.DC]TACC: A Full-stack Cloud Computing Infrastructure for Machine Learning Tasks
    Kaiqiang Xu, Xinchen Wan, Hao Wang, Zhenghang Ren, Xudong Liao, Decang Sun, Chaoliang Zeng, Kai Chen
    http://arxiv.org/abs/2110.01556v1

    • [cs.DS]Clique percolation method: memory efficient almost exact communities
    Alexis Baudin, Maximilien Danisch, Sergey Kirgizov, Clémence Magnien, Marwan Ghanem
    http://arxiv.org/abs/2110.01213v1

    • [cs.DS]Random Subgraph Detection Using Queries
    Wasim Huleihel, Arya Mazumdar, Soumyabrata Pal
    http://arxiv.org/abs/2110.00744v1

    • [cs.GT]Inducing Equilibria via Incentives: Simultaneous Design-and-Play Finds Global Optima
    Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Marco Nie, Zhaoran Wang
    http://arxiv.org/abs/2110.01212v1

    • [cs.GT]Information Elicitation Meets Clustering
    Yuqing Kong
    http://arxiv.org/abs/2110.00952v1

    • [cs.HC]Analysis of the Correlation between smartphone usage changes during the COVID-19 pandemic and usage preferences on apps
    Yuxuan Yang, Maiko Shigeno
    http://arxiv.org/abs/2110.01331v1

    • [cs.HC]Generating User-Centred Explanations via Illocutionary Question Answering: From Philosophy to Interfaces
    Francesco Sovrano, Fabio Vitali
    http://arxiv.org/abs/2110.00762v1

    • [cs.HC]How mass surveillance can crowd out installations of COVID-19 contact tracing apps
    Eran Toch, Oshrat Ayalon
    http://arxiv.org/abs/2110.01567v1

    • [cs.IR]A Proposed Conceptual Framework for a Representational Approach to Information Retrieval
    Jimmy Lin
    http://arxiv.org/abs/2110.01529v1

    • [cs.IR]Deep Neural Matching Models for Graph Retrieval
    Chitrank Gupta, Yash Jain
    http://arxiv.org/abs/2110.00925v1

    • [cs.IR]Encoder Adaptation of Dense Passage Retrieval for Open-Domain Question Answering
    Minghan Li, Jimmy Lin
    http://arxiv.org/abs/2110.01599v1

    • [cs.IR]Multiversal Simulacra: Understanding Hypotheticals and Possible Worlds Through Simulation
    Michael D. Ekstrand
    http://arxiv.org/abs/2110.00811v1

    • [cs.IR]Person Entity Profiling Framework: Identifying, Integrating and Visualizing Online Freely Available Entity-Related Information
    Saeed Amal, Einat Minkov, Tsvi Kuflik
    http://arxiv.org/abs/2110.00759v1

    • [cs.IR]Relation Analysis between Hotel Review Rating Scores and Sentiment Analysis of Reviews by Chinese Tourists Visiting Japan
    Elisa Claire Alemán Carreón, Hirofumi Nonaka, Toru Hiraoka
    http://arxiv.org/abs/2110.00821v1

    • [cs.IR]Unsupervised paradigm for information extraction from transcripts using BERT
    Aravind Chandramouli, Siddharth Shukla, Neeti Nair, Shiven Purohit, Shubham Pandey, Murali Krishna
    http://arxiv.org/abs/2110.00949v1

    • [cs.IT]A Class of Nonbinary Symmetric Information Bottleneck Problems
    Michael Dikshtein, Shlomo Shamai
    http://arxiv.org/abs/2110.00985v1

    • [cs.IT]A Minimal Intervention Definition of Reverse Engineering a Neural Circuit
    Keerthana Gurushankar, Pulkit Grover
    http://arxiv.org/abs/2110.00889v1

    • [cs.IT]A Modified Q-Learning Algorithm for Rate-Profiling of Polarization Adjusted Convolutional (PAC) Codes
    Samir Kumar Mishra, Digvijay Katyal, Sarvesha Anegundi Ganapathi
    http://arxiv.org/abs/2110.01563v1

    • [cs.IT]A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications
    Beixiong Zheng, Changsheng You, Weidong Mei, Rui Zhang
    http://arxiv.org/abs/2110.01292v1

    • [cs.IT]A Unified 3D Beam Training and Tracking Procedure for Terahertz Communication
    Boyu Ning, Zhi Chen, Zhongbao Tian, Chong Han, Shaoqian Li
    http://arxiv.org/abs/2110.01066v1

    • [cs.IT]Age of Changed Information: Content-Aware Status Updating in the Internet of Things
    Xijun Wang, Wenrui Lin, Chao Xu, Xinghua Sun, Xiang Chen
    http://arxiv.org/abs/2110.00817v1

    • [cs.IT]Binary code optimization
    Parviz Gharehbagheri, Sayeed Hamid Haji Sayeed Javadi, Parvaneh Asghari, Naser Gharehbagheri
    http://arxiv.org/abs/2110.00917v1

    • [cs.IT]Clustering with Respect to the Information Distance
    Andrei Romashchenko
    http://arxiv.org/abs/2110.01346v1

    • [cs.IT]Communication Models for Reconfigurable Intelligent Surfaces: From Surface Electromagnetics to Wireless Networks Optimization
    Marco Di Renzo, Fadil H. Danufane, Sergei Tretyakov
    http://arxiv.org/abs/2110.00833v1

    • [cs.IT]Complete b-symbol weight distribution of some irreducible cyclic codes
    Hongwei Zhu, Minjia Shi, Ferruh Ozbudak
    http://arxiv.org/abs/2110.00805v1

    • [cs.IT]Graph Compression with Application to Model Selection
    Mojtaba Abolfazli, Anders Host-Madsen, June Zhang, Andras Bratincsak
    http://arxiv.org/abs/2110.00701v1

    • [cs.IT]Lifetime Maximization for UAV-Enabled IoT Networks with Cognitive NOMA Transmissions
    Na Tang
    http://arxiv.org/abs/2110.01133v1

    • [cs.IT]New families of quantum stabilizer codes from Hermitian self-orthogonal algebraic geometry codes
    Lin Sok
    http://arxiv.org/abs/2110.00769v1

    • [cs.IT]Optimal Resource Allocation and Beamforming for Two-User MISO WPCNs for a Non-linear Circuit-Based EH Model
    Nikita Shanin, Moritz Garkisch, Amelie Hagelauer, Robert Schober, Laura Cottatellucci
    http://arxiv.org/abs/2110.01453v1

    • [cs.IT]Sequences of linear codes where the rate times distance grows rapidly
    Faezeh Alizadeh, S. P. Glasby, Cheryl E. Praeger
    http://arxiv.org/abs/2110.01277v1

    • [cs.IT]Skew cyclic codes over 今日学术视野(2021.10.6) - 图4 with derivation
    Djoko Suprijanto, Hopein Christofen Tang
    http://arxiv.org/abs/2110.01580v1

    • [cs.IT]Spiked Covariance Estimation from Modulo-Reduced Measurements
    Elad Romanov, Or Ordentlich
    http://arxiv.org/abs/2110.01150v1

    • [cs.LG]A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning
    Iris A. M. Huijben, Wouter Kool, Max B. Paulus, Ruud J. G. van Sloun
    http://arxiv.org/abs/2110.01515v1

    • [cs.LG]A Theoretical Overview of Neural Contraction Metrics for Learning-based Control with Guaranteed Stability
    Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques Slotine, Chuchu Fan
    http://arxiv.org/abs/2110.00693v1

    • [cs.LG]ACDC: Online Unsupervised Cross-Domain Adaptation
    Marcus de Carvalho, Mahardhika Pratama, Jie Zhang, Edward Yapp
    http://arxiv.org/abs/2110.01326v1

    • [cs.LG]AI Back-End as a Service for Learning Switching of Mobile Apps between the Fog and the Cloud
    Dionysis Athanasopoulos, Dewei Liu
    http://arxiv.org/abs/2110.00836v1

    • [cs.LG]ALBU: An approximate Loopy Belief message passing algorithm for LDA to improve performance on small data sets
    Rebecca M. C. Taylor, Johan A. du Preez
    http://arxiv.org/abs/2110.00635v1

    • [cs.LG]An AO-ADMM approach to constraining PARAFAC2 on all modes
    Marie Roald, Carla Schenker, Rasmus Bro, Jeremy E. Cohen, Evrim Acar
    http://arxiv.org/abs/2110.01278v1

    • [cs.LG]An Analysis of Super-Net Heuristics in Weight-Sharing NAS
    Kaicheng Yu, René Ranftl, Mathieu Salzmann
    http://arxiv.org/abs/2110.01154v1

    • [cs.LG]An Empirical Investigation of Learning from Biased Toxicity Labels
    Neel Nanda, Jonathan Uesato, Sven Gowal
    http://arxiv.org/abs/2110.01577v1

    • [cs.LG]Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits
    Chuanhao Li, Hongning Wang
    http://arxiv.org/abs/2110.01463v1

    • [cs.LG]BRAC+: Improved Behavior Regularized Actor Critic for Offline Reinforcement Learning
    Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K Prasanna
    http://arxiv.org/abs/2110.00894v1

    • [cs.LG]Batch size-invariance for policy optimization
    Jacob Hilton, Karl Cobbe, John Schulman
    http://arxiv.org/abs/2110.00641v1

    • [cs.LG]Behaviour-conditioned policies for cooperative reinforcement learning tasks
    Antti Keurulainen, Isak Westerlund, Ariel Kwiatkowski, Samuel Kaski, Alexander Ilin
    http://arxiv.org/abs/2110.01266v1

    • [cs.LG]Beyond Topics: Discovering Latent Healthcare Objectives from Event Sequences
    Adrian Caruana, Madhushi Bandara, Daniel Catchpoole, Paul J Kennedy
    http://arxiv.org/abs/2110.01160v1

    • [cs.LG]Boost Neural Networks by Checkpoints
    Feng Wang, Guoyizhe Wei, Qiao Liu, Jinxiang Ou, Xian Wei, Hairong Lv
    http://arxiv.org/abs/2110.00959v1

    • [cs.LG]Classifying COVID-19 Spike Sequences from Geographic Location Using Deep Learning
    Sarwan Ali, Babatunde Bello, Murray Patterson
    http://arxiv.org/abs/2110.00809v1

    • [cs.LG]Consider the Alternatives: Navigating Fairness-Accuracy Tradeoffs via Disqualification
    Guy N. Rothblum, Gal Yona
    http://arxiv.org/abs/2110.00813v1

    • [cs.LG]Consistency Regularization Can Improve Robustness to Label Noise
    Erik Englesson, Hossein Azizpour
    http://arxiv.org/abs/2110.01242v1

    • [cs.LG]Contraction Theory for Nonlinear Stability Analysis and Learning-based Control: A Tutorial Overview
    Hiroyasu Tsukamoto, Soon-Jo Chung, Jean-Jacques Slotine
    http://arxiv.org/abs/2110.00675v1

    • [cs.LG]Cycle-Consistent World Models for Domain Independent Latent Imagination
    Sidney Bender, Tim Joseph, Marius Zoellner
    http://arxiv.org/abs/2110.00808v1

    • [cs.LG]Deep Fraud Detection on Non-attributed Graph
    Chen Wang, Yingtong Dou, Min Chen, Jia Chen, Zhiwei Liu, Philip S. Yu
    http://arxiv.org/abs/2110.01171v1

    • [cs.LG]Deep Learning for Principal-Agent Mean Field Games
    Steven Campbell, Yichao Chen, Arvind Shrivats, Sebastian Jaimungal
    http://arxiv.org/abs/2110.01127v1

    • [cs.LG]Deep Learning for Rain Fade Prediction in Satellite Communications
    Aidin Ferdowsi, David Whitefield
    http://arxiv.org/abs/2110.00695v1

    • [cs.LG]DenDrift: A Drift-Aware Algorithm for Host Profiling
    Ali Sedaghatbaf, Sima Sinaei, Perttu Ranta-aho, Marko Koskinen
    http://arxiv.org/abs/2110.01221v1

    • [cs.LG]DiffNet: Neural Field Solutions of Parametric Partial Differential Equations
    Biswajit Khara, Aditya Balu, Ameya Joshi, Soumik Sarkar, Chinmay Hegde, Adarsh Krishnamurthy, Baskar Ganapathysubramanian
    http://arxiv.org/abs/2110.01601v1

    • [cs.LG]Differentiable Spline Approximations
    Minsu Cho, Aditya Balu, Ameya Joshi, Anjana Deva Prasad, Biswajit Khara, Soumik Sarkar, Baskar Ganapathysubramanian, Adarsh Krishnamurthy, Chinmay Hegde
    http://arxiv.org/abs/2110.01532v1

    • [cs.LG]Distributed Learning Approaches for Automated Chest X-Ray Diagnosis
    Edoardo Giacomello, Michele Cataldo, Daniele Loiacono, Pier Luca Lanzi
    http://arxiv.org/abs/2110.01474v1

    • [cs.LG]Enhancing Model Robustness and Fairness with Causality: A Regularization Approach
    Zhao Wang, Kai Shu, Aron Culotta
    http://arxiv.org/abs/2110.00911v1

    • [cs.LG]FairFed: Enabling Group Fairness in Federated Learning
    Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Salman Avestimehr
    http://arxiv.org/abs/2110.00857v1

    • [cs.LG]Fairness and underspecification in acoustic scene classification: The case for disaggregated evaluations
    Andreas Triantafyllopoulos, Manuel Milling, Konstantinos Drossos, Björn W. Schuller
    http://arxiv.org/abs/2110.01506v1

    • [cs.LG]Fast Line Search for Multi-Task Learning
    Andrey Filatov, Daniil Merkulov
    http://arxiv.org/abs/2110.00874v1

    • [cs.LG]Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification
    Jiong Zhang, Wei-cheng Chang, Hsiang-fu Yu, Inderjit S. Dhillon
    http://arxiv.org/abs/2110.00685v1

    • [cs.LG]Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning
    Tong Zhang
    http://arxiv.org/abs/2110.00871v1

    • [cs.LG]Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information
    Yang Zhang, Ashkan Khakzar, Yawei Li, Azade Farshad, Seong Tae Kim, Nassir Navab
    http://arxiv.org/abs/2110.01471v1

    • [cs.LG]GROWN: GRow Only When Necessary for Continual Learning
    Li Yang, Sen Lin, Junshan Zhang, Deliang Fan
    http://arxiv.org/abs/2110.00908v1

    • [cs.LG]Git: Clustering Based on Graph of Intensity Topology
    Zhangyang Gao, Haitao Lin, Cheng Tan, Lirong Wu, Stan. Z Li
    http://arxiv.org/abs/2110.01274v1

    • [cs.LG]Graph Pointer Neural Networks
    Tianmeng Yang, Yujing Wang, Zhihan Yue, Yaming Yang, Yunhai Tong, Jing Bai
    http://arxiv.org/abs/2110.00973v1

    • [cs.LG]Human-Centered AI for Data Science: A Systematic Approach
    Dakuo Wang, Xiaojuan Ma, April Yi Wang
    http://arxiv.org/abs/2110.01108v1

    • [cs.LG]HyperTeNet: Hypergraph and Transformer-based Neural Network for Personalized List Continuation
    Vijaikumar M, Deepesh Hada, Shirish Shevade
    http://arxiv.org/abs/2110.01467v1

    • [cs.LG]Identifiability in Exact Multilayer Sparse Matrix Factorization
    Léon Zheng, Rémi Gribonval, Elisa Riccietti
    http://arxiv.org/abs/2110.01230v1

    • [cs.LG]Identifiability in Exact Two-Layer Sparse Matrix Factorization
    Léon Zheng, Rémi Gribonval, Elisa Riccietti
    http://arxiv.org/abs/2110.01235v1

    • [cs.LG]Incremental Class Learning using Variational Autoencoders with Similarity Learning
    Jiahao Huo, Terence L. van Zyl
    http://arxiv.org/abs/2110.01303v1

    • [cs.LG]Inference-InfoGAN: Inference Independence via Embedding Orthogonal Basis Expansion
    Hongxiang Jiang, Jihao Yin, Xiaoyan Luo, Fuxiang Wang
    http://arxiv.org/abs/2110.00788v1

    • [cs.LG]Information-Theoretic Generalization Bounds for Iterative Semi-Supervised Learning
    Haiyun He, Hanshu Yan, Vincent Y. F. Tan
    http://arxiv.org/abs/2110.00926v1

    • [cs.LG]Information-theoretic generalization bounds for black-box learning algorithms
    Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan
    http://arxiv.org/abs/2110.01584v1

    • [cs.LG]Kalman Bayesian Neural Networks for Closed-form Online Learning
    Philipp Wagner, Xinyang Wu, Marco F. Huber
    http://arxiv.org/abs/2110.00944v1

    • [cs.LG]Large Batch Experience Replay
    Thibault Lahire, Matthieu Geist, Emmanuel Rachelson
    http://arxiv.org/abs/2110.01528v1

    • [cs.LG]Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
    Anastasios N. Angelopoulos, Stephen Bates, Emmanuel J. Candès, Michael I. Jordan, Lihua Lei
    http://arxiv.org/abs/2110.01052v1

    • [cs.LG]Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization
    Junkun Yuan, Xu Ma, Kun Kuang, Ruoxuan Xiong, Mingming Gong, Lanfen Lin
    http://arxiv.org/abs/2110.01438v1

    • [cs.LG]Learning Networked Linear Dynamical Systems under Non-white Excitation from a Single Trajectory
    Harish Doddi, Deepjyoti Deka, Saurav Talukdar, Murti Salapaka
    http://arxiv.org/abs/2110.00852v1

    • [cs.LG]Learning through atypical ‘’phase transitions’’ in overparameterized neural networks
    Carlo Baldassi, Clarissa Lauditi, Enrico M. Malatesta, Rosalba Pacelli, Gabriele Perugini, Riccardo Zecchina
    http://arxiv.org/abs/2110.00683v1

    • [cs.LG]ML4C: Seeing Causality Through Latent Vicinity
    Haoyue Dai, Rui Ding, Yuanyuan Jiang, Shi Han, Dongmei Zhang
    http://arxiv.org/abs/2110.00637v1

    • [cs.LG]Multi-Agent Path Planning Using Deep Reinforcement Learning
    Mert Çetinkaya
    http://arxiv.org/abs/2110.01460v1

    • [cs.LG]On the complexity of the optimal transport problem with graph-structured cost
    Jiaojiao Fan, Isabel Haasler, Johan Karlsson, Yongxin Chen
    http://arxiv.org/abs/2110.00627v1

    • [cs.LG]Parallel Actors and Learners: A Framework for Generating Scalable RL Implementations
    Chi Zhang, Sanmukh Rao Kuppannagari, Viktor K Prasanna
    http://arxiv.org/abs/2110.01101v1

    • [cs.LG]Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams
    Erdem Bıyık, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh
    http://arxiv.org/abs/2110.00751v1

    • [cs.LG]ProTo: Program-Guided Transformer for Program-Guided Tasks
    Zelin Zhao, Karan Samel, Binghong Chen, Le Song
    http://arxiv.org/abs/2110.00804v1

    • [cs.LG]Progressive Transmission and Inference of Deep Learning Models
    Youngsoo Lee, Sangdoo Yun, Yeonghun Kim, Sunghee Choi
    http://arxiv.org/abs/2110.00916v1

    • [cs.LG]RAP-Net: Region Attention Predictive Network for Precipitation Nowcasting
    Chuyao Luo, ZhengZhang, Rui Ye, Xutao Li, Yunming Ye
    http://arxiv.org/abs/2110.01035v1

    • [cs.LG]Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids
    Shanny Lin, Shaohui Liu, Hao Zhu
    http://arxiv.org/abs/2110.01490v1

    • [cs.LG]Robust and Decomposable Average Precision for Image Retrieval
    Elias Ramzi, Nicolas Thome, Clément Rambour, Nicolas Audebert, Xavier Bitot
    http://arxiv.org/abs/2110.01445v1

    • [cs.LG]Scheduling Optimization Techniques for Neural Network Training
    Hyungjun Oh, Hyungjun Oh, HyeongJu Kim, Jiwon Seo
    http://arxiv.org/abs/2110.00929v1

    • [cs.LG]Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning
    Elie Aljalbout, Maximilian Ulmer, Rudolph Triebel
    http://arxiv.org/abs/2110.00784v1

    • [cs.LG]Simple Recurrent Neural Networks is all we need for clinical events predictions using EHR data
    Laila Rasmy, Jie Zhu, Zhiheng Li, Xin Hao, Hong Thoai Tran, Yujia Zhou, Firat Tiryaki, Yang Xiang, Hua Xu, Degui Zhi
    http://arxiv.org/abs/2110.0099
    c06
    8v1
    c06
    8v1)

    • [cs.LG]Simple Recurrent Neural Networks is all we need for clinical events predictions using EHR data
    Laila Rasmy, Jie Zhu, Zhiheng Li, Xin Hao, Hong Thoai Tran, Yujia Zhou, Firat Tiryaki, Yang Xiang, Hua Xu, Degui Zhi
    http://arxiv.org/abs/2110.00998v1

    • [cs.LG]Skill Induction and Planning with Latent Language
    Pratyusha Sharma, Antonio Torralba, Jacob Andreas
    http://arxiv.org/abs/2110.01517v1

    • [cs.LG]Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients
    Lingjiao Chen, Leshang Chen, Hongyi Wang, Susan Davidson, Edgar Dobriban
    http://arxiv.org/abs/2110.01595v1

    • [cs.LG]Stochastic Anderson Mixing for Nonconvex Stochastic Optimization
    Fuchao Wei, Chenglong Bao, Yang Liu
    http://arxiv.org/abs/2110.01543v1

    • [cs.LG]SurvTRACE: Transformers for Survival Analysis with Competing Events
    Zifeng Wang, Jimeng Sun
    http://arxiv.org/abs/2110.00855v1

    • [cs.LG]TinyFedTL: Federated Transfer Learning on Tiny Devices
    Kavya Kopparapu, Eric Lin
    http://arxiv.org/abs/2110.01107v1

    • [cs.LG]Traffic Flow Forecasting with Maintenance Downtime via Multi-Channel Attention-Based Spatio-Temporal Graph Convolutional Networks
    Yuanjie Lu, Parastoo Kamranfar, David Lattanzi, Amarda Shehu
    http://arxiv.org/abs/2110.01535v1

    • [cs.LG]Transfer Learning Approaches for Knowledge Discovery in Grid-based Geo-Spatiotemporal Data
    Aishwarya Sarkar, Jien Zhang, Chaoqun Lu, Ali Jannesari
    http://arxiv.org/abs/2110.00841v1

    • [cs.LG]Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
    Gaon An, Seungyong Moon, Jang-Hyun Kim, Hyun Oh Song
    http://arxiv.org/abs/2110.01548v1

    • [cs.LG]Unraveling the graph structure of tabular datasets through Bayesian and spectral analysis
    Bruno Messias F. de Resende, Eric K. Tokuda, Luciano da Fontoura Costa
    http://arxiv.org/abs/2110.01421v1

    • [cs.LG]xFAIR: Better Fairness via Model-based Rebalancing of Protected Attributes
    Kewen Peng, Joymallya Chakraborty, Tim Menzies
    http://arxiv.org/abs/2110.01109v1

    • [cs.MM]Graph Representation Learning for Spatial Image Steganalysis
    Qiyun Liu, Hanzhou Wu
    http://arxiv.org/abs/2110.00957v1

    • [cs.NE]Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks
    Mufeng Tang, Yibo Yang, Yali Amit
    http://arxiv.org/abs/2109.15089v2

    • [cs.NE]Implementation of Parallel Simplified Swarm Optimization in CUDA
    Wei-Chang Yeh, Zhenyao Liu, Shi-Yi Tan, Shang-Ke Huang
    http://arxiv.org/abs/2110.01470v1

    • [cs.NE]Recurrent circuits as multi-path ensembles for modeling responses of early visual cortical neurons
    Yimeng Zhang, Harold Rockwell, Ge Huang, Stephen Tsou, Yuanyuan Wei, Tai Sing Lee
    http://arxiv.org/abs/2110.00825v1

    • [cs.NI]Optimized Graph Based Routing Algorithm for the Angara Interconnect
    Anatoly Mukosey, Alexander Semenov, Alexander Tretiakov
    http://arxiv.org/abs/2110.00851v1

    • [cs.NI]Reinforcement Learning for Admission Control in Wireless Virtual Network Embedding
    Haitham Afifi, Fabian Sauer, Holger Karl
    http://arxiv.org/abs/2110.01262v1

    • [cs.NI]Scaling Graph-based Deep Learning models to larger networks
    Miquel Ferriol-Galmés, José Suárez-Varela, Krzysztof Rusek, Pere Barlet-Ros, Albert Cabellos-Aparicio
    http://arxiv.org/abs/2110.01261v1

    • [cs.RO]A Deep Learning Approach To Dead-Reckoning Navigation For Autonomous Underwater Vehicles With Limited Sensor Payloads
    Ivar Bjørgo Saksvik, Alex Alcocer, Vahid Hassani
    http://arxiv.org/abs/2110.00661v1

    • [cs.RO]AB-Mapper: Attention and BicNet Based Multi-agent Path Finding for Dynamic Crowded Environment
    Huifeng Guan, Yuan Gao, Min Zhao, Yong Yang, Fuqin Deng, Tin Lun Lam
    http://arxiv.org/abs/2110.00760v1

    • [cs.RO]AI based Algorithms of Path Planning, Navigation and Control for Mobile Ground Robots and UAVs
    Jian Zhang
    http://arxiv.org/abs/2110.00910v1

    • [cs.RO]Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm
    Kanata Suzuki, Taro Sunagawa, Tomotake Sasaki, Takashi Katoh
    http://arxiv.org/abs/2110.00947v1

    • [cs.RO]ComOpT: Combination and Optimization for Testing Autonomous Driving Systems
    Changwen Li, Chih-Hong Cheng, Tiantian Sun, Yuhang Chen, Rongjie Yan
    http://arxiv.org/abs/2110.00761v1

    • [cs.RO]Direct LiDAR Odometry: Fast Localization with Dense Point Clouds
    Kenny Chen, Brett T. Lopez, Ali-akbar Agha-mohammadi, Ankur Mehta
    http://arxiv.org/abs/2110.00605v1

    • [cs.RO]Discovering Synergies for Robot Manipulation with Multi-Task Reinforcement Learning
    Zhanpeng He, Matei Ciocarlie
    http://arxiv.org/abs/2110.01530v1

    • [cs.RO]Enhancing Voluntary Motion with Modular, Backdrivable, Powered Hip and Knee Orthoses
    Christopher Nesler, Gray Thomas, Nikhil Divekar, Elliott J. Rouse, Robert D. Gregg
    http://arxiv.org/abs/2110.01562v1

    • [cs.RO]Evolved neuromorphic radar-based altitude controller for an autonomous open-source blimp
    Marina González-Álvarez, Julien Dupeyroux, Federico Corradi, Guido de Croon
    http://arxiv.org/abs/2110.00646v1

    • [cs.RO]Expanding the Design Space for Electrically-Driven Soft Robots through Handed Shearing Auxetics
    Ian Good, Tosh Brown-Moore, Aditya Patil, Daniel Revier, Jeffrey Ian Lipton
    http://arxiv.org/abs/2110.00669v1

    • [cs.RO]Fast Uncertainty Quantification for Active Graph SLAM
    Julio A. Placed, José A. Castellanos
    http://arxiv.org/abs/2110.01289v1

    • [cs.RO]Geometric Atlas of the Middle Ear and Paranasal Sinuses for Robotic Applications
    Guillaume Michel, Durgesh Salunkhe, Philippe Bordure, Damien Chablat
    http://arxiv.org/abs/2110.01246v1

    • [cs.RO]Geometry-based Graph Pruning for Lifelong SLAM
    Gerhard Kurz, Matthias Holoch, Peter Biber
    http://arxiv.org/abs/2110.01286v1

    • [cs.RO]How To Not Drive: Learning Driving Constraints from Demonstration
    Kasra Rezaee, Peyman Yadmellat
    http://arxiv.org/abs/2110.00645v1

    • [cs.RO]Hybrid Event Shaping to Stabilize Periodic Hybrid Orbits
    James Zhu, Nathan J. Kong, George Council, Aaron M. Jonhson
    http://arxiv.org/abs/2110.01123v1

    • [cs.RO]Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning
    Danny Driess, Jung-Su Ha, Marc Toussaint, Russ Tedrake
    http://arxiv.org/abs/2110.00792v1

    • [cs.RO]Mixed Observable RRT: Multi-Agent Mission-Planning in Partially Observable Environments
    Kasper Johansson, Ugo Rosolia, Wyatt Ubellacker, Andrew Singletary, Aaron D. Ames
    http://arxiv.org/abs/2110.01002v1

    • [cs.RO]Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning
    Kasra Rezaee, Peyman Yadmellat, Simon Chamorro
    http://arxiv.org/abs/2110.00640v1

    • [cs.RO]Multi-lane Cruising Using Hierarchical Planning and Reinforcement Learning
    Kasra Rezaee, Peyman Yadmellat, Masoud S. Nosrati, Elmira Amirloo Abolfathi, Mohammed Elmahgiubi, Jun Luo
    http://arxiv.org/abs/2110.00650v1

    • [cs.RO]OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation
    Josiah Wong, Viktor Makoviychuk, Anima Anandkumar, Yuke Zhu
    http://arxiv.org/abs/2110.00704v1

    • [cs.RO]Online Incremental Non-Gaussian Inference for SLAM Using Normalizing Flows
    Qiangqiang Huang, Can Pu, Kasra Khosoussi, David M. Rosen, Dehann Fourie, Jonathan P. How, John J. Leonard
    http://arxiv.org/abs/2110.00876v1

    • [cs.RO]Optimal Placement of Roadside Infrastructure Sensors towards Safer Autonomous Vehicle Deployments
    Roshan Vijay, Jim Cherian, Rachid Riah, Niels de Boer, Apratim Choudhury
    http://arxiv.org/abs/2110.01251v1

    • [cs.RO]Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers
    Kilian Kleeberger, Jonathan Schnitzler, Muhammad Usman Khalid, Richard Bormann, Werner Kraus, Marco F. Huber
    http://arxiv.org/abs/2110.00992v1

    • [cs.RO]ReDUCE: Reformulation of Mixed Integer Programs using Data from Unsupervised Clusters for Learning Efficient Strategies
    Xuan Lin, Gabriel I. Fernandez, Dennis W. Hong
    http://arxiv.org/abs/2110.00666v1

    • [cs.RO]SHARP: Shielding-Aware Robust Planning for Safe and Efficient Human-Robot Interaction
    Haimin Hu, Kensuke Nakamura, Jaime F. Fisac
    http://arxiv.org/abs/2110.00843v1

    • [cs.RO]Safe Control with Neural Network Dynamic Models
    Tianhao Wei, Changliu Liu
    http://arxiv.org/abs/2110.01110v1

    • [cs.RO]Sensitivity Study of Fiducial-Aided Navigation of Unmanned Aerial Vehicles
    Amanda J. Strate, Randall Christensen
    http://arxiv.org/abs/2110.01596v1

    • [cs.RO]Stanford Pupper: A Low-Cost Agile Quadruped Robot for Benchmarking and Education
    Nathan Kau, Stuart Bowers
    http://arxiv.org/abs/2110.00736v1

    • [cs.RO]Stress Testing Autonomous Racing Overtake Maneuvers with RRT
    Stanley Bak, Johannes Betz, Abhinav Chawla, Hongrui Zheng, Rahul Mangharam
    http://arxiv.org/abs/2110.01095v1

    • [cs.RO]Towards Time-Optimal Tunnel-Following for Quadrotors
    Jon Arrizabalaga, Markus Ryll
    http://arxiv.org/abs/2110.01351v1

    • [cs.RO]Vision-aided Dynamic Quadrupedal Locomotion on Discrete Terrain using Motion Libraries
    Ayush Agrawal, Shuxiao Chen, Akshara Rai, Koushil Sreenath
    http://arxiv.org/abs/2110.00891v1

    • [cs.SD]Building a Noisy Audio Dataset to Evaluate Machine Learning Approaches for Automatic Speech Recognition Systems
    Julio Cesar Duarte, Sérgio Colcher
    http://arxiv.org/abs/2110.01425v1

    • [cs.SD]On the Interplay Between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis
    Cheng-I Jeff Lai, Erica Cooper, Yang Zhang, Shiyu Chang, Kaizhi Qian, Yi-Lun Liao, Yung-Sung Chuang, Alexander H. Liu, Junichi Yamagishi, David Cox, James Glass
    http://arxiv.org/abs/2110.01147v1

    • [cs.SD]PL-EESR: Perceptual Loss Based END-TO-END Robust Speaker Representation Extraction
    Yi Ma, Kong Aik Lee, Ville Hautamaki, Haizhou Li
    http://arxiv.org/abs/2110.00940v1

    • [cs.SE]Identifying non-natural language artifacts in bug reports
    Thomas Hirsch, Birgit Hofer
    http://arxiv.org/abs/2110.01336v1

    • [cs.SI]A Survey of COVID-19 Misinformation: Datasets, Detection Techniques and Open Issues
    A. R. Sana Ullah, Anupam Das, Anik Das, Muhammad Ashad Kabir, Kai Shu
    http://arxiv.org/abs/2110.00737v1

    • [cs.SI]An Efficient Procedure for Mining Egocentric Temporal Motifs
    Antonio Longa, Giulia Cencetti, Bruno Lepri, Andrea Passerini
    http://arxiv.org/abs/2110.01391v1

    • [cs.SI]Application of Social Network Analysis in Evaluating Risk and network resilience of Closed-Loop-Supply-Chain
    Sara Akbar Ghanadian, Saeed Ghanbartehrani
    http://arxiv.org/abs/2110.00652v1

    • [cs.SI]Do Facial Trait Correlates with Roll Call Voting in Parliament? Using fWHR to Study Performance in Politics
    Rahul Goel, Tymofii Brik, Rajesh Sharma
    http://arxiv.org/abs/2110.00780v1

    • [cs.SI]The Cognitive Science of Extremist Ideologies Online
    Chloe Perry, Simon DeDeo
    http://arxiv.org/abs/2110.00626v1

    • [econ.EM]Probabilistic Prediction for Binary Treatment Choice: with focus on personalized medicine
    Charles F. Manski
    http://arxiv.org/abs/2110.00864v1

    • [eess.AS]AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks
    Jee-weon Jung, Hee-Soo Heo, Hemlata Tak, Hye-jin Shim, Joon Son Chung, Bong-Jin Lee, Ha-Jin Yu, Nicholas Evans
    http://arxiv.org/abs/2110.01200v1

    • [eess.AS]Decoupling Speaker-Independent Emotions for Voice Conversion Via Source-Filter Networks
    Zhaojie Luo, Shoufeng Lin, Rui Liu, Jun Baba, Yuichiro Yoshikawa, Ishiguro Hiroshi
    http://arxiv.org/abs/2110.01164v1

    • [eess.AS]End-to-End Complex-Valued Multidilated Convolutional Neural Network for Joint Acoustic Echo Cancellation and Noise Suppression
    Karn N. Watcharasupat, Thi Ngoc Tho Nguyen, Woon-Seng Gan, Shengkui Zhao, Bin Ma
    http://arxiv.org/abs/2110.00745v1

    • [eess.AS]Multi-task Voice-Activated Framework using Self-supervised Learning
    Shehzeen Hussain, Van Nguyen, Shuhua Zhang, Erik Visser
    http://arxiv.org/abs/2110.01077v1

    • [eess.IV]Adaptive Unfolding Total Variation Network for Low-Light Image Enhancement
    Chuanjun Zheng, Daming Shi, Wentian Shi
    http://arxiv.org/abs/2110.00984v1

    • [eess.IV]Artificial Intelligence For Breast Cancer Detection: Trends & Directions
    Shahid Munir Shah, Rizwan Ahmed Khan, Sheeraz Arif, Unaiza Sajid
    http://arxiv.org/abs/2110.00942v1

    • [eess.IV]Assessing glaucoma in retinal fundus photographs using Deep Feature Consistent Variational Autoencoders
    Sayan Mandal, Alessandro A. Jammal, Felipe A. Medeiros
    http://arxiv.org/abs/2110.01534v1

    • [eess.IV]Attention module improves both performance and interpretability of 4D fMRI decoding neural network
    Zhoufan Jiang, Yanming Wang, ChenWei Shi, Yueyang Wu, Rongjie Hu, Shishuo Chen, Sheng Hu, Xiaoxiao Wang, Bensheng Qiu
    http://arxiv.org/abs/2110.00920v1

    • [eess.IV]Blindness (Diabetic Retinopathy) Severity Scale Detection
    Ramya Bygari, Rachita Naik, Uday Kumar P
    http://arxiv.org/abs/2110.01333v1

    • [eess.IV]Deep Kernel Representation for Image Reconstruction in PET
    Siqi Li, Guobao Wang
    http://arxiv.org/abs/2110.01174v1

    • [eess.IV]Disarranged Zone Learning (DZL): An unsupervised and dynamic automatic stenosis recognition methodology based on coronary angiography
    Yanan Dai, Pengxiong Zhu, Bangde Xue, Yun Ling, Xibao Shi, Liang Geng, Qi Zhang, Jun Liu
    http://arxiv.org/abs/2110.00896v1

    • [eess.IV]EAR-U-Net: EfficientNet and attention-based residual U-Net for automatic liver segmentation in CT
    Jinke Wang, Xiangyang Zhang, Peiqing Lv, Lubiao Zhou, Haiying Wang
    http://arxiv.org/abs/2110.01014v1

    • [eess.IV]Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT scans
    Michelle Xiao-Lin Foo, Seong Tae Kim, Magdalini Paschali, Leili Goli, Egon Burian, Marcus Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler
    http://arxiv.org/abs/2110.00948v1

    • [eess.IV]Light-weight Deformable Registration using Adversarial Learning with Distilling Knowledge
    Minh Q. Tran, Tuong Do, Huy Tran, Erman Tjiputra, Quang D. Tran, Anh Nguyen
    http://arxiv.org/abs/2110.01293v1

    • [eess.IV]Multi-view SA-LA Net: A framework for simultaneous segmentation of RV on multi-view cardiac MR Images
    Sana Jabbar, Syed Talha Bukhari, Hassan Mohy-ud-Din
    http://arxiv.org/abs/2110.00682v1

    • [eess.IV]Synthetic Velocity Mapping Cardiac MRI Coupled with Automated Left Ventricle Segmentation
    Xiaodan Xing, Yinzhe Wu, David Firmin, Peter Gatehouse, Guang Yang
    http://arxiv.org/abs/2110.01304v1

    • [eess.IV]Welsch Based Multiview Disparity Estimation
    James L. Gray, Aous T. Naman, David S. Taubman
    http://arxiv.org/abs/2110.00803v1

    • [eess.SP]A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters
    Victor M. Tenorio, Samuel Rey, Fernando Gama, Santiago Segarra, Antonio G. Marques
    http://arxiv.org/abs/2110.00844v1

    • [eess.SP]Cloud-Cluster Architecture for Detection in Intermittently Connected Sensor Networks
    Michal Yemini, Stephanie Gil, Andrea J. Goldsmith
    http://arxiv.org/abs/2110.01119v1

    • [eess.SP]Economics of Semantic Communication System in Wireless Powered Internet of Things
    Zi Qin Liew, Yanyu Cheng, Wei Yang Bryan Lim, Dusit Niyato, Chunyan Miao, Sumei Sun
    http://arxiv.org/abs/2110.01423v1

    • [eess.SP]Quickest Change Detection with Non-stationary and Composite Post-change Distribution
    Yuchen Liang, Venugopal V. Veeravalli
    http://arxiv.org/abs/2110.01581v1

    • [eess.SY]Data-Driven Detection and Identification of IoT-Enabled Load-Altering Attacks in Power Grids
    Subhash Lakshminarayana, Saurav Sthapit, Carsten Maple
    http://arxiv.org/abs/2110.00667v1

    • [eess.SY]Efficient Modeling of Morphing Wing Flight Using Neural Networks and Cubature Rules
    Paul Ghanem, Yunus Bicer, Deniz Erdogmus, Alireza Ramezani
    http://arxiv.org/abs/2110.01057v1

    • [eess.SY]Exploration of AI-Oriented Power System Transient Stability Simulations
    Tannan Xiao, Ying Chen, Jianquan Wang, Shaowei Huang, Weilin Tong, Tirui He
    http://arxiv.org/abs/2110.00931v1

    • [eess.SY]Implementation of MPPT Technique of Solar Module with Supervised Machine Learning
    Ruhi Sharmin, Sayeed Shafayet Chowdhury, Farihal Abedin, Kazi Mujibur Rahman
    http://arxiv.org/abs/2110.00728v1

    • [eess.SY]Model Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges
    Cosimo Della Santina, Christian Duriez, Daniela Rus
    http://arxiv.org/abs/2110.01358v1

    • [eess.SY]Terminal Adaptive Guidance for Autonomous Hypersonic Strike Weapons via Reinforcement Learning
    Brian Gaudet, Roberto Furfaro
    http://arxiv.org/abs/2110.00634v1

    • [math.CO]Local Orthogonality Dimension
    Inon Attias, Ishay Haviv
    http://arxiv.org/abs/2110.00718v1

    • [math.NA]Reconstructing group wavelet transform from feature maps with a reproducing kernel iteration
    Davide Barbieri
    http://arxiv.org/abs/2110.00600v1

    • [math.OC]A Markov process approach to untangling intention versus execution in tennis
    Timothy C. Y. Chan, Douglas S. Fearing, Craig Fernandes, Stephanie Kovalchik
    http://arxiv.org/abs/2110.01527v1

    • [math.OC]Maximum-Entropy Multi-Agent Dynamic Games: Forward and Inverse Solutions
    Negar Mehr, Mingyu Wang, Mac Schwager
    http://arxiv.org/abs/2110.01027v1

    • [math.ST]Hierarchical Causal Analysis of Natural Languages on a Chain Event Graph
    Xuewen Yu, Jim Q. Smith
    http://arxiv.org/abs/2110.01129v1

    • [math.ST]Some Statistic and Information-theoretic Results On Arithmetic Average Fusion
    Tiancheng Li
    http://arxiv.org/abs/2110.01440v1

    • [math.ST]Volatility prediction comparison via robust volatility proxies: An empirical deviation perspective
    Weichen Wang, Ran An, Ziwei Zhu
    http://arxiv.org/abs/2110.01189v1

    • [q-bio.GN]A mixture model for determining SARS-Cov-2 variant composition in pooled samples
    Renan Valieris, Rodrigo Drummond, Alexandre Defelicibus, Emannuel Dias-Neto, Rafael A. Rosales, Israel Tojal da Silva
    http://arxiv.org/abs/2110.01117v1

    • [q-bio.GN]A systematic evaluation of methods for cell phenotype classification using single-cell RNA sequencing data
    Xiaowen Cao, Li Xing, Elham Majd, Hua He, Junhua Gu, Xuekui Zhang
    http://arxiv.org/abs/2110.00681v1

    • [q-bio.QM]3D-Transformer: Molecular Representation with Transformer in 3D Space
    Fang Wu, Qiang Zhang, Dragomir Radev, Jiyu Cui, Wen Zhang, Huabin Xing, Ningyu Zhang, Huajun Chen
    http://arxiv.org/abs/2110.01191v1

    • [q-bio.QM]Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
    Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang
    http://arxiv.org/abs/2110.01219v1

    • [q-bio.QM]Motif-based Graph Self-Supervised Learning forMolecular Property Prediction
    Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee
    http://arxiv.org/abs/2110.00987v1

    • [q-bio.QM]Pharmacoprint — a combination of pharmacophore fingerprint and artificial intelligence as a tool for computer-aided drug design
    Dawid Warszycki, Łukasz Struski, Marek Śmieja, Rafał Kafel, Rafał Kurczab
    http://arxiv.org/abs/2110.01339v1

    • [quant-ph]Maximum-Likelihood Quantum State Tomography by Cover’s Method with Non-Asymptotic Analysis
    Chien-Ming Lin, Hao-Chung Cheng, Yen-Huan Li
    http://arxiv.org/abs/2110.00747v1

    • [quant-ph]Quantum Max-Flow Min-Cut theorem
    Nengkun Yu
    http://arxiv.org/abs/2110.00905v1

    • [quant-ph]Variational learning of quantum ground states on spiking neuromorphic hardware
    Robert Klassert, Andreas Baumbach, Mihai A. Petrovici, Martin Gärttner
    http://arxiv.org/abs/2109.15169v2

    • [stat.AP]Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS
    Amanda F. Mejia, Vincent Koppelmans, Laura Jelsone-Swain, Sanjay Kalra, Robert C. Welsh
    http://arxiv.org/abs/2110.01510v1

    • [stat.AP]The Impacts of Mobility on Covid-19 Dynamics: Using Soft and Hard Data
    Leonardo Martins, Marcelo C. Medeiros
    http://arxiv.org/abs/2110.00597v1

    • [stat.ME]A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint
    Rui Pan, Yingqiu Zhu, Baishan Guo, Xuening Zhu, Hansheng Wang
    http://arxiv.org/abs/2110.00936v1

    • [stat.ME]A causal fused lasso for interpretable heterogeneous treatment effects estimation
    Oscar Hernan Madrid Padilla, Peng Ding, Yanzhen Chen, Gabriel Ruiz
    http://arxiv.org/abs/2110.00901v1

    • [stat.ME]A general framework for identification of permissible variable subsets in structured model selection
    Guanbo Wang, Mireille E. Schnitzer, Tom Chen, Rui Wang, Robert W. Platt
    http://arxiv.org/abs/2110.01031v1

    • [stat.ME]A non-parametric Bayesian approach for adjusting partial compliance in sequential decision making
    Indrabati Bhattacharya, Brent A. Johnson, William Artman, Andrew Wilson, Kevin G. Lynch, James R. McKay, Ashkan Ertefaie
    http://arxiv.org/abs/2110.00659v1

    • [stat.ME]Bayesian Model-Averaged Meta-Analysis in Medicine
    František Bartoš, Quentin F. Gronau, Bram Timmers, Willem M. Otte, Alexander Ly, Eric-Jan Wagenmakers
    http://arxiv.org/abs/2110.01076v1

    • [stat.ME]COFFEE: COVID-19 Forecasts using Fast Evaluations and Estimation
    Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus
    http://arxiv.org/abs/2110.01546v1

    • [stat.ME]Data Integration in Causal Inference
    Xu Shi, Ziyang Pan, Wang Miao
    http://arxiv.org/abs/2110.01106v1

    • [stat.ME]Functional outlier detection for density-valued data with application to robustify distribution to distribution regression
    Xinyi Lei, Zhicheng Chen, Hui Li
    http://arxiv.org/abs/2110.00707v1

    • [stat.ME]Graph-based multiple change-point detection
    Yuxuan Zhang, Hao Chen
    http://arxiv.org/abs/2110.01170v1

    • [stat.ME]Multi-linear Tensor Autoregressive Models
    Zebang Li, Han Xiao
    http://arxiv.org/abs/2110.00928v1

    • [stat.ME]Online Control of the False Discovery Rate under “Decision Deadlines”
    Aaron Fisher
    http://arxiv.org/abs/2110.01583v1

    • [stat.ME]Online multiple testing with super-uniformity reward
    Sebastian Döhler, Iqraa Meah, Etienne Roquain
    http://arxiv.org/abs/2110.01255v1

    • [stat.ME]Vector or Matrix Factor Model? A Strong Rule Helps!
    Yong He, Xin-bing Kong, Lorenzo Trapani, Long Yu
    http://arxiv.org/abs/2110.01008v1

    • [stat.ML]Active Learning for Contextual Search with Binary Feedbacks
    Chen, Xi, Liu, Quanquan, Wang, Yining
    http://arxiv.org/abs/2110.01072v1

    • [stat.ML]Causality and Generalizability: Identifiability and Learning Methods
    Martin Emil Jakobsen
    http://arxiv.org/abs/2110.01430v1

    • [stat.ML]Clustering a Mixture of Gaussians with Unknown Covariance
    Damek Davis, Mateo Diaz, Kaizheng Wang
    http://arxiv.org/abs/2110.01602v1

    • [stat.ML]DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization
    Boyue Li, Zhize Li, Yuejie Chi
    http://arxiv.org/abs/2110.01165v1

    • [stat.ML]Factored couplings in multi-marginal optimal transport via difference of convex programming
    Quang Huy Tran, Hicham Janati, Ievgen Redko, Rémi Flamary, Nicolas Courty
    http://arxiv.org/abs/2110.00629v1

    • [stat.ML]Generalized Kernel Thinning
    Raaz Dwivedi, Lester Mackey
    http://arxiv.org/abs/2110.01593v1

    • [stat.ML]Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs
    Ximing Wu
    http://arxiv.org/abs/2110.00921v1

    • [stat.ML]Implicit Riemannian Concave Potential Maps
    Danilo J. Rezende, Sébastien Racanière
    http://arxiv.org/abs/2110.01288v1

    • [stat.ML]Marginally calibrated response distributions for end-to-end learning in autonomous driving
    Clara Hoffmann, Nadja Klein
    http://arxiv.org/abs/2110.01050v1

    • [stat.ML]Row-clustering of a Point Process-valued Matrix
    Lihao Yin, Ganggang Xu, Huiyan Sang, Yongtao Guan
    http://arxiv.org/abs/2110.01207v1

    • [stat.ML]Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
    Yan Sun, Wenjun Xiong, Faming Liang
    http://arxiv.org/abs/2110.00653v1

    • [stat.ML]Treeging
    Gregory L. Watson, Michael Jerrett, Colleen E. Reid, Donatello Telesca
    http://arxiv.org/abs/2110.01053v1