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.DC - 分布式、并行与集群计算
    cs.GR - 计算机图形学
    cs.GT - 计算机科学与博弈论
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    cs.MM - 多媒体
    cs.NE - 神经与进化计算
    cs.PL - 编程语言
    cs.RO - 机器人学
    cs.SD - 声音处理
    cs.SE - 软件工程
    cs.SI - 社交网络与信息网络
    econ.EM - 计量经济学
    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.CT - 范畴论
    math.FA - 泛函演算
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    physics.geo-ph - 地球物理学
    physics.pop-ph - 流行物理学
    physics.soc-ph - 物理学与社会
    q-bio.BM - 生物分子
    q-bio.GN - 基因组学
    q-bio.NC - 神经元与认知
    q-bio.QM - 定量方法
    q-fin.TR - 贸易与市场微观结构
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cs.AI]Active Altruism Learning and Information Sufficiency for Autonomous Driving
    • [cs.AI]CASPR: A Commonsense Reasoning-based Conversational Socialbot
    • [cs.AI]Interactive Hierarchical Guidance using Language
    • [cs.AI]Natural Language for Human-Robot Collaboration: Problems Beyond Language Grounding
    • [cs.AI]The CaLiGraph Ontology as a Challenge for OWL Reasoners
    • [cs.AI]TiKick: Toward Playing Multi-agent Football Full Games from Single-agent Demonstrations
    • [cs.AI]Towards AI Logic for Social Reasoning
    • [cs.AI]Using Human-Guided Causal Knowledge for More Generalized Robot Task Planning
    • [cs.AI]Using Human-Guided Causal Knowledge for More Generalized Robot Task Planning
    • [cs.CL]A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution
    • [cs.CL]A Few More Examples May Be Worth Billions of Parameters
    • [cs.CL]A Framework for Rationale Extraction for Deep QA models
    • [cs.CL]A Review on Part-of-Speech Technologies
    • [cs.CL]Advances in Multi-turn Dialogue Comprehension: A Survey
    • [cs.CL]An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognition
    • [cs.CL]An Isotropy Analysis in the Multilingual BERT Embedding Space
    • [cs.CL]Bayesian Active Summarization
    • [cs.CL]Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networks
    • [cs.CL]Calibrate your listeners! Robust communication-based training for pragmatic speakers
    • [cs.CL]Cross Domain Emotion Recognition using Few Shot Knowledge Transfer
    • [cs.CL]DCT: Dynamic Compressive Transformer for Modeling Unbounded Sequence
    • [cs.CL]DMRST: A Joint Framework for Document-Level Multilingual RST Discourse Segmentation and Parsing
    • [cs.CL]Detecting Community Sensitive Norm Violations in Online Conversations
    • [cs.CL]Disentangled Sequence to Sequence Learning for Compositional Generalization
    • [cs.CL]Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence Annotation
    • [cs.CL]Document-Level Text Simplification: Dataset, Criteria and Baseline
    • [cs.CL]Dynamic Forecasting of Conversation Derailment
    • [cs.CL]Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality
    • [cs.CL]Enhance Long Text Understanding via Distilled Gist Detector from Abstractive Summarization
    • [cs.CL]Evaluating User Perception of Speech Recognition System Quality with Semantic Distance Metric
    • [cs.CL]Explainable Fact-checking through Question Answering
    • [cs.CL]Extending Multi-Text Sentence Fusion Resources via Pyramid Annotations
    • [cs.CL]Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference
    • [cs.CL]Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works
    • [cs.CL]Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors
    • [cs.CL]Have best of both worlds: two-pass hybrid and E2E cascading framework for speech recognition
    • [cs.CL]HydraSum — Disentangling Stylistic Features in Text Summarization using Multi-Decoder Models
    • [cs.CL]Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning
    • [cs.CL]Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgetting
    • [cs.CL]Improving Multi-Party Dialogue Discourse Parsing via Domain Integration
    • [cs.CL]It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpretation Data
    • [cs.CL]K-Wav2vec 2.0: Automatic Speech Recognition based on Joint Decoding of Graphemes and Syllables
    • [cs.CL]Language Models As or For Knowledge Bases
    • [cs.CL]Leveraging recent advances in Pre-Trained Language Models forEye-Tracking Prediction
    • [cs.CL]Multi-Task Learning for Situated Multi-Domain End-to-End Dialogue Systems
    • [cs.CL]Offensive Language Detection with BERT-based models, By Customizing Attention Probabilities
    • [cs.CL]On Automatic Text Extractive Summarization Based on Graph and pre-trained Language Model Attention
    • [cs.CL]On a Benefit of Mask Language Modeling: Robustness to Simplicity Bias
    • [cs.CL]On the Relation between Syntactic Divergence and Zero-Shot Performance
    • [cs.CL]PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction
    • [cs.CL]Pre-trained Language Models in Biomedical Domain: A Survey from Multiscale Perspective
    • [cs.CL]Representation of professions in entertainment media: Insights into frequency and sentiment trends through computational text analysis
    • [cs.CL]Rome was built in 1776: A Case Study on Factual Correctness in Knowledge-Grounded Response Generation
    • [cs.CL]Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks
    • [cs.CL]TEET! Tunisian Dataset for Toxic Speech Detection
    • [cs.CL]The Eval4NLP Shared Task on Explainable Quality Estimation: Overview and Results
    • [cs.CL]The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design
    • [cs.CL]Unsupervised Neural Machine Translation with Generative Language Models Only
    • [cs.CL]Using Document Similarity Methods to create Parallel Datasets for Code Translation
    • [cs.CL]Wav2vec-Switch: Contrastive Learning from Original-noisy Speech Pairs for Robust Speech Recognition
    • [cs.CL]We Need to Talk About Data: The Importance of Data Readiness in Natural Language Processing
    • [cs.CL]WeTS: A Benchmark for Translation Suggestion
    • [cs.CL]What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study
    • [cs.CL]Yuan 1.0: Large-Scale Pre-trained Language Model in Zero-Shot and Few-Shot Learning
    • [cs.CR]Adversarial Attacks in a Multi-view Setting: An Empirical Study of the Adversarial Patches Inter-view Transferability
    • [cs.CR]Blockchain for Edge of Things: Applications, Opportunities, and Challenges
    • [cs.CR]Demystifying the Transferability of Adversarial Attacks in Computer Networks
    • [cs.CV]3D Object Detection Combining Semantic and Geometric Features from Point Clouds
    • [cs.CV]6D-ViT: Category-Level 6D Object Pose Estimation via Transformer-based Instance Representation Learning
    • [cs.CV]A Closer Look at Prototype Classifier for Few-shot Image Classification
    • [cs.CV]A Feature Consistency Driven Attention Erasing Network for Fine-Grained Image Retrieval
    • [cs.CV]Adaptively Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation
    • [cs.CV]Adversarial Token Attacks on Vision Transformers
    • [cs.CV]Adversarial Training for Face Recognition Systems using Contrastive Adversarial Learning and Triplet Loss Fine-tuning
    • [cs.CV]An automated threshold Edge Drawing algorithm
    • [cs.CV]Arabic Speech Emotion Recognition Employing Wav2vec2.0 and HuBERT Based on BAVED Dataset
    • [cs.CV]Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor Classification
    • [cs.CV]BEV-Net: Assessing Social Distancing Compliance by Joint People Localization and Geometric Reasoning
    • [cs.CV]Better Pseudo-label: Joint Domain-aware Label and Dual-classifier for Semi-supervised Domain Generalization
    • [cs.CV]Beyond Accuracy: A Consolidated Tool for Visual Question Answering Benchmarking
    • [cs.CV]Beyond Road Extraction: A Dataset for Map Update using Aerial Images
    • [cs.CV]Biometric Template Protection for Neural-Network-based Face Recognition Systems: A Survey of Methods and Evaluation Techniques
    • [cs.CV]Boosting Fast Adversarial Training with Learnable Adversarial Initialization
    • [cs.CV]Bridging the Gap between Label- and Reference-based Synthesis in Multi-attribute Image-to-Image Translation
    • [cs.CV]BuildingNet: Learning to Label 3D Buildings
    • [cs.CV]CLIP-Adapter: Better Vision-Language Models with Feature Adapters
    • [cs.CV]CLIP4Caption ++: Multi-CLIP for Video Caption
    • [cs.CV]COVID-19 Face Mask Recognition with Advanced Face Cut Algorithm for Human Safety Measures
    • [cs.CV]Class-Balanced Active Learning for Image Classification
    • [cs.CV]Colour augmentation for improved semi-supervised semantic segmentation
    • [cs.CV]Compact CNN Models for On-device Ocular-based User Recognition in Mobile Devices
    • [cs.CV]Comparing Facial Expression Recognition in Humans and Machines: Using CAM, GradCAM, and Extremal Perturbation
    • [cs.CV]DANIEL: A Fast and Robust Consensus Maximization Method for Point Cloud Registration with High Outlier Ratios
    • [cs.CV]Deep Learning Based Person Re-Identification Methods: A Survey and Outlook of Recent Works
    • [cs.CV]Deep Long-Tailed Learning: A Survey
    • [cs.CV]Deep Video Anomaly Detection: Opportunities and Challenges
    • [cs.CV]Differentiable Stereopsis: Meshes from multiple views using differentiable rendering
    • [cs.CV]Digging Into Self-Supervised Learning of Feature Descriptors
    • [cs.CV]Domain Adaptive Semantic Segmentation with Regional Contrastive Consistency Regularization
    • [cs.CV]EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset
    • [cs.CV]Efficient Training of High-Resolution Representation Seismic Image Fault Segmentation Network by Weakening Anomaly Labels
    • [cs.CV]EfficientPhys: Enabling Simple, Fast and Accurate Camera-Based Vitals Measurement
    • [cs.CV]FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation
    • [cs.CV]Fast and Robust Structural Damage Analysis of Civil Infrastructure Using UAV Imagery
    • [cs.CV]Finegrained_Identity_Preserving_Landmark_Synthesis_for_Face_Reenactment
    • [cs.CV]Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization
    • [cs.CV]Google Landmark Retrieval 2021 Competition Third Place Solution
    • [cs.CV]Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks
    • [cs.CV]Harnessing Unlabeled Data to Improve Generalization of Biometric Gender and Age Classifiers
    • [cs.CV]High-order Tensor Pooling with Attention for Action Recognition
    • [cs.CV]Identity-Guided Face Generation with Multi-modal Contour Conditions
    • [cs.CV]Increasing a microscope’s effective field of view via overlapped imaging and machine learning
    • [cs.CV]Investigating Transfer Learning Capabilities of Vision Transformers and CNNs by Fine-Tuning a Single Trainable Block
    • [cs.CV]K-Splits: Improved K-Means Clustering Algorithm to Automatically Detect the Number of Clusters
    • [cs.CV]K-Splits: Improved K-Means Clustering Algorithm to Automatically Detect the Number of Clusters
    • [cs.CV]LDC-Net: A Unified Framework for Localization, Detection and Counting in Dense Crowds
    • [cs.CV]LSC-GAN: Latent Style Code Modeling for Continuous Image-to-image Translation
    • [cs.CV]Label quality in AffectNet: results of crowd-based re-annotation
    • [cs.CV]Label-Occurrence-Balanced Mixup for Lo
    1398
    ng-tailed Recognition
    • [cs.CV]Learnable Adaptive Cosine Estimator (LACE) for Image Classification
    • [cs.CV]Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency
    • [cs.CV]Learning Single/Multi-Attribute of Object with Symmetry and Group
    • [cs.CV]Learning a Self-Expressive Network for Subspace Clustering
    • [cs.CV]Modality-Guided Subnetwork for Salient Object Detection
    • [cs.CV]Morphable Detector for Object Detection on Demand
    • [cs.CV]Multi-Class Cell Detection Using Spatial Context Representation
    • [cs.CV]Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT
    • [cs.CV]Multiple Object Trackers in OpenCV: A Benchmark
    • [cs.CV]NViT: Vision Transformer Compression and Parameter Redistribution
    • [cs.CV]Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans
    • [cs.CV]Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery
    • [cs.CV]Pano-AVQA: Grounded Audio-Visual Question Answering on 360今日学术视野(2021.10.13) - 图1 Videos
    • [cs.CV]Performance Evaluation of Deep Transfer Learning on Multiclass Identification of Common Weed Species in Cotton Production Systems
    • [cs.CV]Point Cloud Augmentation with Weighted Local Transformations
    • [cs.CV]Predicting decision-making in the future: Human versus Machine
    • [cs.CV]RankingMatch: Delving into Semi-Supervised Learning with Consistency Regularization and Ranking Loss
    • [cs.CV]Recurrent Attention Models with Object-centric Capsule Representation for Multi-object Recognition
    • [cs.CV]Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Framework
    • [cs.CV]Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning
    • [cs.CV]Robustness Evaluation of Transformer-based Form Field Extractors via Form Attacks
    • [cs.CV]SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification
    • [cs.CV]SOMA: Solving Optical Marker-Based MoCap Automatically
    • [cs.CV]Self-Supervised 3D Face Reconstruction via Conditional Estimation
    • [cs.CV]Self-appearance-aided Differential Evolution for Motion Transfer
    • [cs.CV]Semi-Autoregressive Image Captioning
    • [cs.CV]Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning
    • [cs.CV]SignBERT: Pre-Training of Hand-Model-Aware Representation for Sign Language Recognition
    • [cs.CV]Sim2Air - Synthetic aerial dataset for UAV monitoring
    • [cs.CV]Sketch Me A Video
    • [cs.CV]Space-Time-Separable Graph Convolutional Network for Pose Forecasting
    • [cs.CV]Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception
    • [cs.CV]Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
    • [cs.CV]SurroundNet: Towards Effective Low-Light Image Enhancement
    • [cs.CV]Synthetic Data for Multi-Parameter Camera-Based Physiological Sensing
    • [cs.CV]TSG: Target-Selective Gradient Backprop for Probing CNN Visual Saliency
    • [cs.CV]Temporally Consistent Video Colorization with Deep Feature Propagation and Self-regularization Learning
    • [cs.CV]The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation
    • [cs.CV]Towards Streaming Egocentric Action Anticipation
    • [cs.CV]Transformer-based Dual Relation Graph for Multi-label Image Recognition
    • [cs.CV]Two-stage Visual Cues Enhancement Network for Referring Image Segmentation
    • [cs.CV]Unsupervised High-Fidelity Facial Texture Generation and Reconstruction
    • [cs.CV]Unsupervised Pose-Aware Part Decomposition for 3D Articulated Objects
    • [cs.CV]Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification
    • [cs.CV]VTBR: Semantic-based Pretraining for Person Re-Identification
    • [cs.CV]Vector-quantized Image Modeling with Improved VQGAN
    • [cs.CV]Vectorization of Raster Manga by Deep Reinforcement Learning
    • [cs.CV]ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation
    • [cs.CV]Visualizing the embedding space to explain the effect of knowledge distillation
    • [cs.CV]Weakly Supervised Contrastive Learning
    • [cs.CV]Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values
    • [cs.CV]ZARTS: On Zero-order Optimization for Neural Architecture Search
    • [cs.CV]ZSpeedL — Evaluating the Performance of Zero-Shot Learning Methods using Low-Power Devices
    • [cs.CY]A New Innovation Concept on End user Contextual and Behavioural Perspectives
    • [cs.CY]Algorithmic collusion: A critical review
    • [cs.CY]Emergent Insight of the Cyber Security Management for Saudi Arabian Universities: A Content Analysis
    • [cs.CY]Ethical Assurance: A practical approach to the responsible design, development, and deployment of data-driven technologies
    • [cs.CY]Using Edge Cases to Disentangle Fairness and Solidarity in AI Ethics
    • [cs.DC]A State Transfer Method That Adapts to Network Bandwidth Variations in Geographic State Machine Replication
    • [cs.DC]Beyond Desktop Computation: Challenges in Scaling a GPU Infrastructure
    • [cs.DC]Deploying Containerized QuantEx Quantum Simulation Software on HPC Systems
    • [cs.DC]Dual Attention-Based Federated Learning for Wireless Traffic Prediction
    • [cs.DC]Evaluation and Ranking of Replica Deployments in Geographic State Machine Replication
    • [cs.DC]Parallel Minimum Spanning Forest Computation using Sparse Matrix Kernels
    • [cs.DC]SplitPlace: Intelligent Placement of Split Neural Nets in Mobile Edge Environments
    • [cs.DC]Themis: A Network Bandwidth-Aware Collective Scheduling Policy for Distributed Training of DL Models
    • [cs.GR]Mesh Draping: Parametrization-Free Neural Mesh Transfer
    • [cs.GT]An Independent Learning Algorithm for a Class of Symmetric Stochastic Games
    • [cs.GT]Transaction Fees on a Honeymoon: Ethereum’s EIP-1559 One Month Later
    • [cs.HC]A Deep Generative Model for Matrix Reordering
    • [cs.HC]Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content
    • [cs.HC]Clustering Human Trust Dynamics for Customized Real-time Prediction
    • [cs.HC]Scope2Screen: Focus+Context Techniques for Pathology Tumor Assessment in Multivariate Image Data
    • [cs.HC]Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings
    • [cs.IR]AskMe: Joint Individual-level and Community-level Behavior Interaction for Question Recommendation
    • [cs.IR]Controllable Recommenders using Deep Generative Models and Disentanglement
    • [cs.IR]Developing Smart Web-Search Using RegEx
    • [cs.IR]Feature Selection for Recommender Systems with Quantum Computing
    • [cs.IR]Lookup or Exploratory: What is Your Search Intent?
    • [cs.IT]A Framework for Private Communication with Secret Block Structure
    • [cs.IT]A Generalization of Array Codes with Local Properties and Efficient Encoding/Decoding
    • [cs.IT]A Novel Negative 今日学术视野(2021.10.13) - 图2 Penalty Approach for Multiuser One-Bit Massive MIMO Downlink with PSK Signaling
    • [cs.IT]A Novel Quantum Calculus-based Complex Least Mean Square Algorithm (q-CLMS)
    • [cs.IT]Adaptive F-FFT Demodulation for ICI Mitigation in Differential Underwater Acoustic OFDM Systems
    • [cs.IT]An Information-Theoretic Analysis of The Cost of Decentralization for Learning and Inference Under Privacy Constraints
    • [cs.IT]Deep Learning for Uplink Spectral Efficiency in Cell-Free Massive MIMO Systems
    • [cs.IT]Efficiently and Globally Solving Joint Beamforming and Compression Problem in the Cooperative Cellular Network via Lagrangian Duality
    • [cs.IT]Enhancing Utility in the Watchdog Privacy Mechanism
    • [cs.IT]ProductAE: Towards Training Larger Channel Codes based on Neural Product Codes
    • [cs.IT]Safeguarding UAV Networks Through Integrated Sensing, Jamming, and Communications
    • [cs.IT]Semi-Blind Multiuser Detection Under the Presence of Reconfigurable Intelligent Surfaces
    • [cs.IT]Simultaneous Transmitting and ReflectingIntelligent Surfaces-Empowered NOMA Networks
    • [cs.IT]Sliced Mutual Information: A Scalable Measure of Statistical Dependence
    • [cs.IT]Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO System
    • [cs.IT]Uplink Performance of Cell-Free Massive MIMO with Multi-Antenna Users Over Jointly-Correlated Rayleigh Fading Channels
    • [cs.LG]A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise Datasets
    • [cs.LG]A Deep Learning Inference Scheme Based on Pipelined Matrix Multiplication Acceleration Design and Non-uniform Quantization
    • [cs.LG]A Proximal Algorithm for Sampling from Non-smooth Potentials
    • [cs.LG]A Review of Physics-based Machine Learning in Civil Engineering
    • [cs.LG]A Survey on Proactive Customer Care: Enabling Science and Steps to Realize it
    • [cs.LG]Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions
    • [cs.LG]Accelerating Multi-Objective Neural Architecture Search by Random-Weight Evaluation
    • [cs.LG]Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning
    • [cs.LG]Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting
    • [cs.LG]Bid Optimization using Maximum Entropy Reinforcement Learning
    • [cs.LG]Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization
    • [cs.LG]Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
    • [cs.LG]Breaking the Softmax Bottleneck for Sequential Recommender Systems with Dropout and Decoupling
    • [cs.LG]Can Stochastic Gradient Langevin Dynamics Provide Differential Privacy for Deep\ Learning?
    • [cs.LG]Certifying Robustness to Programmable Data Bias in Decision Trees
    • [cs.LG]Chaos as an interpretable benchmark for forecasting and data-driven modelling
    • [cs.LG]CoRGi: Content-Rich Graph Neural Networks with Attention
    • [cs.LG]Cognitively Inspired Learning of Incremental Drifting Concepts
    • [cs.LG]Continual Learning with Differential Privacy
    • [cs.LG]Crack detection using tap-testing and machine learning techniques to prevent potential rockfall incidents
    • [cs.LG]Deep Learning of Potential Outcomes
    • [cs.LG]Density-Based Clustering with Kernel Diffusion
    • [cs.LG]Density-based interpretable hypercube region partitioning for mixed numeric and categorical data
    • [cs.LG]Differentially Private Approximate Quantiles
    • [cs.LG]Discriminative Multimodal Learning via Conditional Priors in Generative Models
    • [cs.LG]Disease Informed Neural Networks
    • [cs.LG]Disturbing Target Values for Neural Network Regularization
    • [cs.LG]Does Preprocessing Help Training Over-parameterized Neural Networks?
    • [cs.LG]Embed Everything: A Method for Efficiently Co-Embedding Multi-Modal Spaces
    • [cs.LG]EnsembleNTLDetect: An Intelligent Framework for Electricity Theft Detection in Smart Grid
    • [cs.LG]Equivalence Analysis between Counterfactual Regret Minimization and Online Mirror Descent
    • [cs.LG]Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?
    • [cs.LG]Exchangeability-Aware Sum-Product Networks
    • [cs.LG]Fair Regression under Sample Selection Bias
    • [cs.LG]Fast Attributed Graph Embedding via Density of States
    • [cs.LG]Feature Imitating Networks
    • [cs.LG]Fitting large mixture models using stochastic component selection
    • [cs.LG]Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning
    • [cs.LG]Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits
    • [cs.LG]Gradual Federated Learning with Simulated Annealing
    • [cs.LG]Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
    • [cs.LG]Graph Neural Networks in Real-Time Fraud Detection with Lambda Architecture
    • [cs.LG]Graph-Guided Network for Irregularly Sampled Multivariate Time Series
    • [cs.LG]Heavy Ball Neural Ordinary Differential Equations
    • [cs.LG]Heterogeneous Stream-reservoir Graph Networks with Data Assimilation
    • [cs.LG]Homogeneous Learning: Self-Attention Decentralized Deep Learning
    • [cs.LG]Hybrid Random Features
    • [cs.LG]Instance-based Label Smoothing For Better Calibrated Classification Networks
    • [cs.LG]Intriguing Properties of Input-dependent Randomized Smoothing
    • [cs.LG]Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning
    • [cs.LG]Learning a subspace of policies for online adaptation in Reinforcement Learning
    • [cs.LG]Learning from Ambiguous Demonstrations with Self-Explanation Guided Reinforcement Learning
    • [cs.LG]Learning to Follow Language Instructions with Compositional Policies
    • [cs.LG]Leveraging Transformers for StarCraft Macromanagement Prediction
    • [cs.LG]Long Expressive Memory for Sequence Modeling
    • [cs.LG]Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks
    • [cs.LG]Mixture Model Auto-Encoders: Deep Clustering through Dictionary Learning
    • [cs.LG]Momentum Centering and Asynchronous Update for Adaptive Gradient Methods
    • [cs.LG]Multi-Agent MDP Homomorphic Networks
    • [cs.LG]Multi-Relation Aware Temporal Interaction Network Embedding
    • [cs.LG]Multi-task learning on the edge: cost-efficiency and theoretical optimality
    • [cs.LG]NFT-K: Non-Fungible Tangent Kernels
    • [cs.LG]Neural Algorithmic Reasoners are Implicit Planners
    • [cs.LG]Neural Link Prediction with Walk Pooling
    • [cs.LG]Online Graph Learning in Dynamic Environments
    • [cs.LG]Pairwise Margin Maximization for Deep Neural Networks
    • [cs.LG]Performance Analysis of Fractional Learning Algorithms
    • [cs.LG]Phase Collapse in Neural Networks
    • [cs.LG]ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
    • [cs.LG]Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning
    • [cs.LG]REIN-2: Giving Birth to Prepared Reinforcement Learning Agents Using Reinforcement Learning Agents
    • [cs.LG]Recurrent Model-Free RL is a Strong Baseline for Many POMDPs
    • [cs.LG]Reinforcement Learning In Two Player Zero Sum Simultaneous Action Games
    • [cs.LG]Representation Learning for Online and Offline RL in Low-rank MDPs
    • [cs.LG]SCEHR: Supervised Contrastive Learning for Clinical Risk Prediction using Electronic Health Records
    • [cs.LG]Self-explaining Neural Network with Plausible Explanations
    • [cs.LG]Self-supervised Learning is More Robust to Dataset Imbalance
    • [cs.LG]Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families
    • [cs.LG]SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
    • [cs.LG]SuperShaper: Task-Agnostic Super Pre-training of BERT Models with Variable Hidden Dimensions
    • [cs.LG]Surrogate-Assisted Reference Vector Adaptation to Various Pareto Front Shapes for Many-Objective Bayesian Optimization
    • [cs.LG]The Skellam Mechanism for Differentially Private Federated Learning
    • [cs.LG]Time Series Classification Using Convolutional Neural Network On Imbalanced Datasets
    • [cs.LG]Time-varying Graph Learning Under Structured Temporal Priors
    • [cs.LG]Towards Data-Free Domain Generalization
    • [cs.LG]Towards Demystifying Representation Learning with Non-contrastive Self-supervision
    • [cs.LG]Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach
    • [cs.LG]Two-level Group Convolution
    • [cs.LG]Understanding Pooling in Graph Neural Networks
    • [cs.LG]Unsupervised Source Separation via Bayesian Inference in the Latent Domain
    • [cs.LG]Value-Function-based Sequential Minimization for Bi-level Optimization
    • [cs.LG]Widen The Backdoor To Let More Attackers In
    • [cs.LG]X-model: Improving Data Efficiency in Deep Learning with A Minimax Model
    • [cs.LG]You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction
    • [cs.LO]Dynamic Logic of Legal Competences
    • [cs.MM]Real-time FPGA Design for OMP Targeting 8K Image Reconstruction
    • [cs.NE]Can the brain use waves to solve planning problems?
    • [cs.NE]Learning Division with Neural Arithmetic Logic Modules
    • [cs.NE]Self-adaptive Multi-task Particle Swarm Optimization
    • [cs.NE]Time Complexity Analysis of Evolutionary Algorithms for 2-Hop (1,2)-Minimum Spanning Tree Problem
    • [cs.NE]Towards Explainable Real Estate Valuation via Evolutionary Algorithms
    • [cs.PL]Synthesizing Machine Learning Programs with PAC Guarantees via Statistical Sketching
    • [cs.RO]AMRA    : Anytime Multi-Resolution Multi-Heuristic A_
    • [cs.RO]Adaptive Variable Impedance Control for a Modular Soft Robot Manipulator in Configuration Space
    • [cs.RO]An Augmented Reality Platform for Introducing Reinforcement Learning to K-12 Students with Robots
    • [cs.RO]Autonomous Racing using a Hybrid Imitation-Reinforcement Learning Architecture
    • [cs.RO]Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning
    • [cs.RO]Credit Assignment Safety Learning from Human Demonstrations
    • [cs.RO]Dynamic Control of Soft Robotic Arm
    • [cs.RO]Human-Aware Robot Navigation via Reinforcement Learning with Hindsight Experience Replay and Curriculum Learning
    • [cs.RO]Humans’ Assessment of Robots as Moral Regulators: Importance of Perceived Fairness and Legitimacy
    • [cs.RO]Learning High-Speed Flight in the Wild
    • [cs.RO]Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Clouds
    • [cs.RO]Learning to Control Complex Robots Using High-Dimensional Interfaces: Preliminary Insights
    • [cs.RO]Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World
    • [cs.RO]Leveraging Experience in Lazy Search
    • [cs.RO]Multimodal Sensory Learning for Real-time, Adaptive Manipulation
    • [cs.RO]Nano Version Control and Robots of Robots: Data Driven, Regenerative Production Code
    • [cs.RO]Navigation In Urban Environments Amongst Pedestrians Using Multi-Objective Deep Reinforcement Learning
    • [cs.RO]Optimal Stochastic Evasive Maneuvers Using the Schrodinger’s Equation
    • [cs.RO]Safe Human-Interactive Control via Shielding
    • [cs.RO]Scene Editing as Teleoperation: A Case Study in 6DoF Kit Assembly
    • [cs.RO]Teaching Robots to Grasp Like Humans: An Interactive Approach
    • [cs.RO]Vision-based Navigation for a Small-scale Quadruped Robot Pegasus-Mini
    • [cs.SD]An Overview of Techniques for Biomarker Discovery in Voice Signal
    • [cs.SD]Can Audio Captions Be Evaluated with Image Caption Metrics?
    • [cs.SD]Efficient Training of Audio Transformers with Patchout
    • [cs.SD]LaughNet: synthesizing laughter utterances from waveform silhouettes and a single laughter example
    • [cs.SD]Multi-task Learning with Metadata for Music Mood Classification
    • [cs.SD]PAMA-TTS: Progression-Aware Monotonic Attention for Stable Seq2Seq TTS With Accurate Phoneme Duration Control
    • [cs.SD]Pitch Preservation In Singing Voice Synthesis
    • [cs.SD]Streaming on-device detection of device directed speech from voice and touch-based invocation
    • [cs.SD]Towards High-fidelity Singing Voice Conversion with Acoustic Reference and Contrastive Predictive Coding
    • [cs.SD]Universal Paralinguistic Speech Representations Using Self-Supervised Conformers
    • [cs.SD]Using multiple reference audios and style embedding constraints for speech synthesis
    • [cs.SE]Automatic Recall of Software Lessons Learned for Software Project Managers
    • [cs.SE]Graph-Based Machine Learning Improves Just-in-Time Defect Prediction
    • [cs.SE]Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?
    • [cs.SI]An Analysis of COVID-19 Knowledge Graph Construction and Applications
    • [cs.SI]Influencing the Influencers: Evaluating Person-to-Person Influence on Social Networks Using Granger Causality
    • [cs.SI]The Role of Masks in Mitigating Viral Spread on Networks
    • [econ.EM]On the asymptotic behavior of bubble date estimators
    • [eess.AS]A Comparative Study on Non-Autoregressive Modelings for Speech-to-Text Generation
    • [eess.AS]Complex Network-Based Approach for Feature Extraction and Classification of Musical Genres
    • [eess.AS]Injecting Text and Cross-lingual Supervision in Few-shot Learning from Self-Supervised Models
    • [eess.AS]Interactive Feature Fusion for End-to-End Noise-Robust Speech Recognition
    • [eess.AS]Multi-Channel End-to-End Neural Diarization with Distributed Microphones
    • [eess.AS]Multi-View Self-Attention Based Transformer for Speaker Recognition
    • [eess.AS]Personalized Automatic Speech Recognition Trained on Small Disordered Speech Datasets
    • [eess.AS]Stepwise-Refining Speech Separation Network via Fine-Grained Encoding in High-order Latent Domain
    • [eess.AS]Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis
    • [eess.AS]Wav2vec-S: Semi-Supervised Pre-Training for Speech Recognition
    • [eess.IV]AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation
    • [eess.IV]DenseNet approach to segmentation and classification of dermatoscopic skin lesions images
    • [eess.IV]Exploring constraints on CycleGAN-based CBCT enhancement for adaptive radiotherapy
    • [eess.IV]Invertible Tone Mapping with Selectable Styles
    • [eess.IV]Learning MRI Artifact Removal With Unpaired Data
    • [eess.IV]NormVAE: Normative Modeling on Neuroimaging Data using Variational Autoencoders
    • [eess.IV]Rethinking Noise Synthesis and Modeling in Raw Denoising
    • [eess.IV]Spatial-temporal V-Net for automatic segmentation and quantification of right ventricles in gated myocardial perfusion SPECT images
    • [eess.IV]Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images
    • [eess.IV]Vision Transformer based COVID-19 Detection using Chest X-rays
    • [eess.SP]A Hybrid Scattering Transform for Signals with Isolated Singularities
    • [eess.SP]An Efficient Deep Learning Model for Automatic Modulation Recognition Based on Parameter Estimation and Transformation
    • [eess.SP]Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Rate Control
    • [eess.SP]Stability of Neural Networks on Manifolds to Relative Perturbations
    • [eess.SP]Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space Models
    • [eess.SY]Artificial Intelligence in Electric Machine Drives: Advances and Trends
    • [eess.SY]Non-Parametric Neuro-Adaptive Coordination of Multi-Agent Systems
    • [eess.SY]Safe Model-Based Reinforcement Learning Using Robust Control Barrier Functions
    • [eess.SY]When is gray-box modeling advantageous for virtual flow metering?
    • [math.CO]On 今日学术视野(2021.10.13) - 图3-ary shortened-今日学术视野(2021.10.13) - 图4-perfect-like codes
    • [math.CT]Compositionality as we see it, everywhere around us
    • [math.FA]Fat-shattering dimension of 今日学术视野(2021.10.13) - 图5-fold maxima
    • [math.OC]An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models
    • [math.OC]Convergence of Random Reshuffling Under The Kurdyka-Łojasiewicz Inequality
    • [math.OC]Finding Second-Order Stationary Point for Nonconvex-Strongly-Concave Minimax Problem
    • [math.PR]A tractable class of Multivariate Phase-type distributions for loss modeling: Theoretical developments
    • [math.PR]Tails of bivariate stochastic recurrence equation
    • [math.ST]Approximating Familywise Error Rate for Correlated Normal
    • [math.ST]Dynamic Precise and Imprecise Probability Kinematics
    • [math.ST]Exact Matching of Random Graphs with Constant Correlation
    • [math.ST]Learning from non-irreducible Markov chains
    • [math.ST]Optional Pólya trees: posterior rates and uncertainty quantification
    • [math.ST]Pairwise interaction function estimation of Gibbs point processes using basis expansion
    • [math.ST]Two-stage least squares with a randomly right censored outcome
    • [physics.geo-ph]Deep Bayesian inference for seismic imaging with tasks
    • [physics.geo-ph]Lithological Tomography with the Correlated Pseudo-Marginal Method
    • [physics.pop-ph]Modeling of Pan Evaporation Based on the Development of Machine Learning Methods
    • [physics.soc-ph]Sideward contact tracing and the control of epidemics in large gatherings
    • [q-bio.BM]Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design
    • [q-bio.GN]Multi-modal Self-supervised Pre-training for Regulatory Genome Across Cell Types
    • [q-bio.NC]Are Words the Quanta of Human Language? Extending the Domain of Quantum Cognition
    • [q-bio.QM]COVID-Datathon: Biomarker identification for COVID-19 severity based on BALF scRNA-seq data
    • [q-fin.TR]How Robust are Limit Order Book Representations under Data Perturbation?
    • [q-fin.TR]Reinforcement Learning for Systematic FX Trading
    • [quant-ph]Application of quantum computing to a linear non-Gaussian acyclic model for novel medical knowledge discovery
    • [quant-ph]Hard instance learning for quantum adiabatic prime factorization
    • [quant-ph]Quantum pixel representations and compression for 今日学术视野(2021.10.13) - 图6-dimensional images
    • [stat.AP]Call and Put Option Pricing with Discrete Linear Investment Strategy
    • [stat.AP]Estimating IRI based on pavement distress type, density, and severity: Insights from machine learning techniques
    • [stat.AP]Phase-type distributions for claim severity regression modeling
    • [stat.ME]A computational approach to the Kiefer-Weiss problem for sampling from a Bernoulli population
    • [stat.ME]A parametric quantile beta regression for modeling case fatality rates of COVID-19
    • [stat.ME]Allocation of COVID-19 Testing Budget on a Commute Network of Counties
    • [stat.ME]Birth-and-death Processes in Python: The BirDePy Package
    • [stat.ME]Clustering of Diverse Multiplex Networks
    • [stat.ME]Co-clustering of Spatially Resolved Transcriptomic Data
    • [stat.ME]De-biased Lasso for Generalized Linear Models with A Diverging Number of Covariates
    • [stat.ME]Graphical Assistant Grouped Network Autoregression Model: a Bayesian Nonparametric Recourse
    • [stat.ME]Group-matching algorithms for subjects and items
    • [stat.ME]High-dimensional Inference for Dynamic Treatment Effects
    • [stat.ME]Mixture representations for likelihood ratio ordered distributions
    • [stat.ME]Multiway sparse distance weighted discrimination
    • [stat.ME]Nonparametric kernel estimation of Weibull-tail coefficient in presence of the right random censoring
    • [stat.ME]Ordinary Differential Equation Models and their Computation Methods
    • [stat.ME]Reversible Genetically Modified ModeJumping MCMC
    • [stat.ME]Scaled torus principal component analysis
    • [stat.ME]Simultaneous Cluster Structure Learning and Estimation of Heterogeneous Graphs for Matrix-variate fMRI Data
    • [stat.ME]Truncated Rank-Based Tests for Two-Part Models with Excessive Zeros and Applications to Microbiome Data
    • [stat.ME]Wavelet Estimation for Factor Models with Time-Varying Loadings
    • [stat.ML]Adaptive joint distribution learning
    • [stat.ML]Deep Unsupervised Feature Selection by Discarding Nuisance and Correlated Features
    • [stat.ML]Designing off-sample performance metrics
    • [stat.ML]Learning Temporally Causal Latent Processes from General Temporal Data
    • [stat.ML]Nonparametric Functional Analysis of Generalized Linear Models Under Nonlinear Constraints
    • [stat.ML]Quadratic Multiform Separation: A New Classification Model in Machine Learning
    • [stat.ML]Robust and Scalable SDE Learning: A Functional Perspective
    • [stat.ML]When to Call Your Neighbor? Strategic Communication in Cooperative Stochastic Bandits
    • [stat.ML]β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap

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

    • [cs.AI]Active Altruism Learning and Information Sufficiency for Autonomous Driving
    Jack Geary, Henry Gouk, Subramanian Ramamoorthy
    http://arxiv.org/abs/2110.04580v1

    • [cs.AI]CASPR: A Commonsense Reasoning-based Conversational Socialbot
    Kinjal Basu, Huaduo Wang, Nancy Dominguez, Xiangci Li, Fang Li, Sarat Chandra Varanasi, Gopal Gupta
    http://arxiv.org/abs/2110.05387v1

    • [cs.AI]Interactive Hierarchical Guidance using Language
    Bharat Prakash, Nicholas Waytowich, Tim Oates, Tinoosh Mohsenin
    http://arxiv.org/abs/2110.04649v1

    • [cs.AI]Natural Language for Human-Robot Collaboration: Problems Beyond Language Grounding
    Seth Pate, Wei Xu, Ziyi Yang, Maxwell Love, Siddarth Ganguri, Lawson L. S. Wong
    http://arxiv.org/abs/2110.04441v1

    • [cs.AI]The CaLiGraph Ontology as a Challenge for OWL Reasoners
    Nicolas Heist, Heiko Paulheim
    http://arxiv.org/abs/2110.05028v1

    • [cs.AI]TiKick: Toward Playing Multi-agent Football Full Games from Single-agent Demonstrations
    Shiyu Huang, Wenze Chen, Longfei Zhang, Ziyang Li, Fengming Zhu, Deheng Ye, Ting Chen, Jun Zhu
    http://arxiv.org/abs/2110.04507v1

    • [cs.AI]Towards AI Logic for Social Reasoning
    Huimin Dong, Réka Markovich, Leendert van der Torre
    http://arxiv.org/abs/2110.04452v1

    • [cs.AI]Using Human-Guided Causal Knowledge for More Generalized Robot Task Planning
    Semir Tatlidil, Yanqi Liu, Emily Sheetz, R. Iris Bahar, Steven Sloman
    http://arxiv.org/abs/21
    a0c
    10.04664v1
    a0c
    10.04664v1)

    • [cs.AI]Using Human-Guided Causal Knowledge for More Generalized Robot Task Planning
    Semir Tatlidil, Yanqi Liu, Emily Sheetz, R. Iris Bahar, Steven Sloman
    http://arxiv.org/abs/2110.04664v1

    • [cs.CL]A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution
    Judicael Poumay, Ashwin Ittoo
    http://arxiv.org/abs/2110.05115v1

    • [cs.CL]A Few More Examples May Be Worth Billions of Parameters
    Yuval Kirstain, Patrick Lewis, Sebastian Riedel, Omer Levy
    http://arxiv.org/abs/2110.04374v1

    • [cs.CL]A Framework for Rationale Extraction for Deep QA models
    Sahana Ramnath, Preksha Nema, Deep Sahni, Mitesh M. Khapra
    http://arxiv.org/abs/2110.04620v1

    • [cs.CL]A Review on Part-of-Speech Technologies
    Onyenwe Ikechukwu, Onyedikachukwu Ikechukwu-Onyenwe, Onyedinma Ebele
    http://arxiv.org/abs/2110.04977v1

    • [cs.CL]Advances in Multi-turn Dialogue Comprehension: A Survey
    Zhuosheng Zhang, Hai Zhao
    http://arxiv.org/abs/2110.04984v1

    • [cs.CL]An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognition
    Xuankai Chang, Takashi Maekaku, Pengcheng Guo, Jing Shi, Yen-Ju Lu, Aswin Shanmugam Subramanian, Tianzi Wang, Shu-wen Yang, Yu Tsao, Hung-yi Lee, Shinji Watanabe
    http://arxiv.org/abs/2110.04590v1

    • [cs.CL]An Isotropy Analysis in the Multilingual BERT Embedding Space
    Sara Rajaee, Mohammad Taher Pilehvar
    http://arxiv.org/abs/2110.04504v1

    • [cs.CL]Bayesian Active Summarization
    Alexios Gidiotis, Grigorios Tsoumakas
    http://arxiv.org/abs/2110.04480v1

    • [cs.CL]Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networks
    Songlin Yang, Kewei Tu
    http://arxiv.org/abs/2110.05419v1

    • [cs.CL]Calibrate your listeners! Robust communication-based training for pragmatic speakers
    Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman
    http://arxiv.org/abs/2110.05422v1

    • [cs.CL]Cross Domain Emotion Recognition using Few Shot Knowledge Transfer
    Justin Olah, Sabyasachee Baruah, Digbalay Bose, Shrikanth Narayanan
    http://arxiv.org/abs/2110.05021v1

    • [cs.CL]DCT: Dynamic Compressive Transformer for Modeling Unbounded Sequence
    Kai-Po Chang, Wei-Yun Ma
    http://arxiv.org/abs/2110.04821v1

    • [cs.CL]DMRST: A Joint Framework for Document-Level Multilingual RST Discourse Segmentation and Parsing
    Zhengyuan Liu, Ke Shi, Nancy F. Chen
    http://arxiv.org/abs/2110.04518v1

    • [cs.CL]Detecting Community Sensitive Norm Violations in Online Conversations
    Chan Young Park, Julia Mendelsohn, Karthik Radhakrishnan, Kinjal Jain, Tushar Kanakagiri, David Jurgens, Yulia Tsvetkov
    http://arxiv.org/abs/2110.04419v1

    • [cs.CL]Disentangled Sequence to Sequence Learning for Compositional Generalization
    Hao Zheng, Mirella Lapata
    http://arxiv.org/abs/2110.04655v1

    • [cs.CL]Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence Annotation
    Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III
    http://arxiv.org/abs/2110.04889v1

    • [cs.CL]Document-Level Text Simplification: Dataset, Criteria and Baseline
    Renliang Sun, Hanqi Jin, Xiaojun Wan
    http://arxiv.org/abs/2110.05071v1

    • [cs.CL]Dynamic Forecasting of Conversation Derailment
    Yova Kementchedjhieva, Anders Søgaard
    http://arxiv.org/abs/2110.05111v1

    • [cs.CL]Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality
    Jiashuo Wang, Wenjie LI, Peiqin Lin, Feiteng Mu
    http://arxiv.org/abs/2110.04614v1

    • [cs.CL]Enhance Long Text Understanding via Distilled Gist Detector from Abstractive Summarization
    Yan Liu, Yazheng Yang
    http://arxiv.org/abs/2110.04741v1

    • [cs.CL]Evaluating User Perception of Speech Recognition System Quality with Semantic Distance Metric
    Suyoun Kim, Duc Le, Weiyi Zheng, Tarun Singh, Abhinav Arora, Xiaoyu Zhai, Christian Fuegen, Ozlem Kalinli, Michael L. Seltzer
    http://arxiv.org/abs/2110.05376v1

    • [cs.CL]Explainable Fact-checking through Question Answering
    Jing Yang, Didier Vega-Oliveros, Taís Seibt, Anderson Rocha
    http://arxiv.org/abs/2110.05369v1

    • [cs.CL]Extending Multi-Text Sentence Fusion Resources via Pyramid Annotations
    Daniela Brook Weiss, Paul Roit, Ori Ernst, Ido Dagan
    http://arxiv.org/abs/2110.04517v1

    • [cs.CL]Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference
    William Held, Dan Iter, Dan Jurafsky
    http://arxiv.org/abs/2110.05362v1

    • [cs.CL]Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works
    Jinghui Si, Xutan Peng, Chen Li, Haotian Xu, Jianxin Li
    http://arxiv.org/abs/2110.04525v1

    • [cs.CL]Global Explainability of BERT-Based Evaluation Metrics by Disentangling along Linguistic Factors
    Marvin Kaster, Wei Zhao, Steffen Eger
    http://arxiv.org/abs/2110.04399v1

    • [cs.CL]Have best of both worlds: two-pass hybrid and E2E cascading framework for speech recognition
    Guoli Ye, Vadim Mazalov, Jinyu Li, Yifan Gong
    http://arxiv.org/abs/2110.04891v1

    • [cs.CL]HydraSum — Disentangling Stylistic Features in Text Summarization using Multi-Decoder Models
    Tanya Goyal, Nazneen Fatema Rajani, Wenhao Liu, Wojciech Kryściński
    http://arxiv.org/abs/2110.04400v1

    • [cs.CL]Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning
    Xinghua Zhang, Bowen Yu, Tingwen Liu, Zhenyu Zhang, Jiawei Sheng, Mengge Xue, Hongbo Xu
    http://arxiv.org/abs/2110.04429v1

    • [cs.CL]Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgetting
    Zahra Fatemi, Chen Xing, Wenhao Liu, Caiming Xiong
    http://arxiv.org/abs/2110.05367v1

    • [cs.CL]Improving Multi-Party Dialogue Discourse Parsing via Domain Integration
    Zhengyuan Liu, Nancy F. Chen
    http://arxiv.org/abs/2110.04526v1

    • [cs.CL]It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpretation Data
    Jinming Zhao, Philip Arthur, Gholamreza Haffari, Trevor Cohn, Ehsan Shareghi
    http://arxiv.org/abs/2110.05213v1

    • [cs.CL]K-Wav2vec 2.0: Automatic Speech Recognition based on Joint Decoding of Graphemes and Syllables
    Jounghee Kim, Pilsung Kang
    http://arxiv.org/abs/2110.05172v1

    • [cs.CL]Language Models As or For Knowledge Bases
    Simon Razniewski, Andrew Yates, Nora Kassner, Gerhard Weikum
    http://arxiv.org/abs/2110.04888v1

    • [cs.CL]Leveraging recent advances in Pre-Trained Language Models forEye-Tracking Prediction
    Varun Madhavan, Aditya Girish Pawate, Shraman Pal, Abhranil Chandra
    http://arxiv.org/abs/2110.04475v1

    • [cs.CL]Multi-Task Learning for Situated Multi-Domain End-to-End Dialogue Systems
    Po-Nien Kung, Chung-Cheng Chang, Tse-Hsuan Yang, Hsin-Kai Hsu, Yu-Jia Liou, Yun-Nung Chen
    http://arxiv.org/abs/2110.05221v1

    • [cs.CL]Offensive Language Detection with BERT-based models, By Customizing Attention Probabilities
    Peyman Alavi, Pouria Nikvand, Mehrnoush Shamsfard
    http://arxiv.org/abs/2110.05133v1

    • [cs.CL]On Automatic Text Extractive Summarization Based on Graph and pre-trained Language Model Attention
    Yuan-Ching Lin, Jinwen Ma
    http://arxiv.org/abs/2110.04878v1

    • [cs.CL]On a Benefit of Mask Language Modeling: Robustness to Simplicity Bias
    Ting-Rui Chiang
    http://arxiv.org/abs/2110.05301v1

    • [cs.CL]On the Relation between Syntactic Divergence and Zero-Shot Performance
    Ofir Arviv, Dmitry Nikolaev, Taelin Karidi, Omri Abend
    http://arxiv.org/abs/2110.04644v1

    • [cs.CL]PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction
    Rajdeep Mukherjee, Tapas Nayak, Yash Butala, Sourangshu Bhattacharya, Pawan Goyal
    http://arxiv.org/abs/2110.04794v1

    • [cs.CL]Pre-trained Language Models in Biomedical Domain: A Survey from Multiscale Perspective
    Benyou Wang, Qianqian Xie, Jiahuan Pei, Prayag Tiwari, Zhao Li, Jie fu
    http://arxiv.org/abs/2110.05006v1

    • [cs.CL]Representation of professions in entertainment media: Insights into frequency and sentiment trends through computational text analysis
    Sabyasachee Baruah, Krishna Somandepalli, Shrikanth Narayanan
    http://arxiv.org/abs/2110.03873v2

    • [cs.CL]Rome was built in 1776: A Case Study on Factual Correctness in Knowledge-Grounded Response Generation
    Sashank Santhanam, Behnam Hedayatnia, Spandana Gella, Aishwarya Padmakumar, Seokhwan Kim, Yang Liu, Dilek Hakkani-Tur
    http://arxiv.org/abs/2110.05456v1

    • [cs.CL]Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks
    Hongzhan Lin, Jing Ma, Mingfei Cheng, Zhiwei Yang, Liangliang Chen, Guang Chen
    http://arxiv.org/abs/2110.04522v1

    • [cs.CL]TEET! Tunisian Dataset for Toxic Speech Detection
    Slim Gharbi, Heger Arfaoui, Hatem Haddad, Mayssa Kchaou
    http://arxiv.org/abs/2110.05287v1

    • [cs.CL]The Eval4NLP Shared Task on Explainable Quality Estimation: Overview and Results
    Marina Fomicheva, Piyawat Lertvittayakumjorn, Wei Zhao, Steffen Eger, Yang Gao
    http://arxiv.org/abs/2110.04392v1

    • [cs.CL]The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design
    Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua
    http://arxiv.org/abs/2110.04541v1

    • [cs.CL]Unsupervised Neural Machine Translation with Generative Language Models Only
    Jesse Michael Han, Igor Babuschkin, Harrison Edwards, Arvind Neelakantan, Tao Xu, Stanislas Polu, Alex Ray, Pranav Shyam, Aditya Ramesh, Alec Radford, Ilya Sutskever
    http://arxiv.org/abs/2110.05448v1

    • [cs.CL]Using Document Similarity Methods to create Parallel Datasets for Code Translation
    Mayank Agarwal, Kartik Talamadupula, Fernando Martinez, Stephanie Houde, Michael Muller, John Richards, Steven I Ross, Justin D. Weisz
    http://arxiv.org/abs/2110.05423v1

    • [cs.CL]Wav2vec-Switch: Contrastive Learning from Original-noisy Speech Pairs for Robust Speech Recognition
    Yiming Wang, Jinyu Li, Heming Wang, Yao Qian, Chengyi Wang, Yu Wu
    http://arxiv.org/abs/2110.04934v1

    • [cs.CL]We Need to Talk About Data: The Importance of Data Readiness in Natural Language Processing
    Fredrik Olsson, Magnus Sahlgren
    http://arxiv.org/abs/2110.05464v1

    • [cs.CL]WeTS: A Benchmark for Translation Suggestion
    Zhen Yang, Yingxue Zhang, Ernan Li, Fandong Meng, Jie Zhou
    http://arxiv.org/abs/2110.05151v1

    • [cs.CL]What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study
    Mohamed Abdalla, Krishnapriya Vishnubhotla, Saif M. Mohammad
    http://arxiv.org/abs/2110.04845v1

    • [cs.CL]Yuan 1.0: Large-Scale Pre-trained Language Model in Zero-Shot and Few-Shot Learning
    Shaohua Wu, Xudong Zhao, Tong Yu, Rongguo Zhang, Chong Shen, Hongli Liu, Feng Li, Hong Zhu, Jiangang Luo, Liang Xu, Xuanwei Zhang, Jun Liu
    http://arxiv.org/abs/2110.04725v1

    • [cs.CR]Adversarial Attacks in a Multi-view Setting: An Empirical Study of the Adversarial Patches Inter-view Transferability
    Bilel Tarchoun, Ihsen Alouani, Anouar Ben Khalifa, Mohamed Ali Mahjoub
    http://arxiv.org/abs/2110.04887v1

    • [cs.CR]Blockchain for Edge of Things: Applications, Opportunities, and Challenges
    Thippa Reddy Gadekallu, Quoc-Viet Pham, Dinh C. Nguyen, Praveen Kumar Reddy Maddikunta, N Deepa, Prabadevi B, Pubudu N. Pathirana, Jun Zhao, Won-Joo Hwang
    http://arxiv.org/abs/2110.05022v1

    • [cs.CR]Demystifying the Transferability of Adversarial Attacks in Computer Networks
    Ehsan Nowroozi, Mauro Conti, Yassine Mekdad, Mohammad Hajian Berenjestanaki, Abdeslam EL Fergougui
    http://arxiv.org/abs/2110.04488v1

    • [cs.CV]3D Object Detection Combining Semantic and Geometric Features from Point Clouds
    Hao Peng, Guofeng Tong, Zheng Li, Yaqi Wang, Yuyuan Shao
    http://arxiv.org/abs/2110.04704v1

    • [cs.CV]6D-ViT: Category-Level 6D Object Pose Estimation via Transformer-based Instance Representation Learning
    Lu Zou, Zhangjin Huang
    http://arxiv.org/abs/2110.04792v1

    • [cs.CV]A Closer Look at Prototype Classifier for Few-shot Image Classification
    Mingcheng Hou, Issei Sato
    http://arxiv.org/abs/2110.05076v1

    • [cs.CV]A Feature Consistency Driven Attention Erasing Network for Fine-Grained Image Retrieval
    Qi Zhao, Xu Wang, Shuchang Lyu, Binghao Liu, Yifan Yang
    http://arxiv.org/abs/2110.04479v1

    • [cs.CV]Adaptively Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation
    Hui Shuai, Lele Wu, Qingshan Liu
    http://arxiv.org/abs/2110.05092v1

    • [cs.CV]Adversarial Token Attacks on Vision Transformers
    Ameya Joshi, Gauri Jagatap, Chinmay Hegde
    http://arxiv.org/abs/2110.04337v1

    • [cs.CV]Adversarial Training for Face Recognition Systems using Contrastive Adversarial Learning and Triplet Loss Fine-tuning
    Nazmul Karim, Umar Khalid, Nick Meeker, Sarinda Samarasinghe
    http://arxiv.org/abs/2110.04459v1

    • [cs.CV]An automated threshold Edge Drawing algorithm
    Ciprian Orhei, Muguras Mocofan, Silviu Vert, Radu Vasiu
    http://arxiv.org/abs/2110.05119v1

    • [cs.CV]Arabic Speech Emotion Recognition Employing Wav2vec2.0 and HuBERT Based on BAVED Dataset
    Omar Mohamed, Salah A. Aly
    http://arxiv.org/abs/2110.04425v1

    • [cs.CV]Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor Classification
    Keyu Li, Yangxin Xu, Max Q. -H. Meng
    http://arxiv.org/abs/2110.04563v1

    • [cs.CV]BEV-Net: Assessing Social Distancing Compliance by Joint People Localization and Geometric Reasoning
    Zhirui Dai, Yuepeng Jiang, Yi Li, Bo Liu, Antoni B. Chan, Nuno Vasconcelos
    http://arxiv.org/abs/2110.04931v1

    • [cs.CV]Better Pseudo-label: Joint Domain-aware Label and Dual-classifier for Semi-supervised Domain Generalization
    Ruiqi Wang, Lei Qi, Yinghuan Shi, Yang Gao
    http://arxiv.org/abs/2110.04820v1

    • [cs.CV]Beyond Accuracy: A Consolidated Tool for Visual Question Answering Benchmarking
    Dirk Väth, Pascal Tilli, Ngoc Thang Vu
    http://arxiv.org/abs/2110.05159v1

    • [cs.CV]Beyond Road Extraction: A Dataset for Map Update using Aerial Images
    Favyen Bastani, Sam Madden
    http://arxiv.org/abs/2110.04690v1

    • [cs.CV]Biometric Template Protection for Neural-Network-based Face Recognition Systems: A Survey of Methods and Evaluation Techniques
    Vedrana Krivokuća Hahn, Sébastien Marcel
    http://arxiv.org/abs/2110.05044v1

    • [cs.CV]Boosting Fast Adversarial Training with Learnable Adversarial Initialization
    Xiaojun Jia, Yong Zhang, Baoyuan Wu, Jue Wang, Xiaochun Cao
    http://arxiv.org/abs/2110.05007v1

    • [cs.CV]Bridging the Gap between Label- and Reference-based Synthesis in Multi-attribute Image-to-Image Translation
    Qiusheng Huang, Zhilin Zheng, Xueqi Hu, Li Sun, Qingli Li
    http://arxiv.org/abs/2110.05055v1

    • [cs.CV]BuildingNet: Learning to Label 3D Buildings
    Pratheba Selvaraju, Mohamed Nabail, Marios Loizou, Maria Maslioukova, Melinos Averkiou, Andreas Andreou, Siddhartha Chaudhuri, Evangelos Kalogerakis
    http://arxiv.org/abs/2110.04955v1

    • [cs.CV]CLIP-Adapter: Better Vision-Language Models with Feature Adapters
    Peng Gao, Shijie Geng, Renrui Zhang, Teli Ma, Rongyao Fang, Yongfeng Zhang, Hongsheng Li, Yu Qiao
    http://arxiv.org/abs/2110.04544v1

    • [cs.CV]CLIP4Caption ++: Multi-CLIP for Video Caption
    Mingkang Tang, Zhanyu Wang, Zhaoyang Zeng, Fengyun Rao, Dian Li
    http://arxiv.org/abs/2110.05204v1

    • [cs.CV]COVID-19 Face Mask Recognition with Advanced Face Cut Algorithm for Human Safety Measures
    Arkaprabha Basu, Md Firoj Ali
    http://arxiv.org/abs/2110.04316v1

    • [cs.CV]Class-Balanced Active Learning for Image Classification
    Javad Zolfaghari Bengar, Joost van de Weijer, Laura Lopez Fuentes, Bogdan Raducanu
    http://arxiv.org/abs/2110.04543v1

    • [cs.CV]Colour augmentation for improved semi-supervised semantic segmentation
    Geoff French, Michal Mackiewicz
    http://arxiv.org/abs/2110.04487v1

    • [cs.CV]Compact CNN Models for On-device Ocular-based User Recognition in Mobile Devices
    Ali Almadan, Ajita Rattani
    http://arxiv.org/abs/2110.04953v1

    • [cs.CV]Comparing Facial Expression Recognition in Humans and Machines: Using CAM, GradCAM, and Extremal Perturbation
    Serin Park, Christian Wallraven
    http://arxiv.org/abs/2110.04481v1

    • [cs.CV]DANIEL: A Fast and Robust Consensus Maximization Method for Point Cloud Registration with High Outlier Ratios
    Lei Sun
    http://arxiv.org/abs/2110.05075v1

    • [cs.CV]Deep Learning Based Person Re-Identification Methods: A Survey and Outlook of Recent Works
    Zhangqiang Ming, Min Zhu, Xiaoyong Wei, Xiangkun Wang, Jiamin Zhu, Junlong Cheng, Yong Yang
    http://arxiv.org/abs/2110.04764v1

    • [cs.CV]Deep Long-Tailed Learning: A Survey
    Yifan Zhang, Bingyi Kang, Bryan Hooi, Shuicheng Yan, Jiashi Feng
    http://arxiv.org/abs/2110.04596v1

    • [cs.CV]Deep Video Anomaly Detection: Opportunities and Challenges
    Jing Ren, Feng Xia, Yemeng Liu, Ivan Lee
    http://arxiv.org/abs/2110.05086v1

    • [cs.CV]Differentiable Stereopsis: Meshes from multiple views using differentiable rendering
    Shubham Goel, Georgia Gkioxari, Jitendra Malik
    http://arxiv.org/abs/2110.05472v1

    • [cs.CV]Digging Into Self-Supervised Learning of Feature Descriptors
    Iaroslav Melekhov, Zakaria Laskar, Xiaotian Li, Shuzhe Wang, Juho Kannala
    http://arxiv.org/abs/2110.04773v1

    • [cs.CV]Domain Adaptive Semantic Segmentation with Regional Contrastive Consistency Regularization
    Qianyu Zhou, Chuyun Zhuang, Xuequan Lu, Lizhuang Ma
    http://arxiv.org/abs/2110.05170v1

    • [cs.CV]EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset
    Kaihao Zhang, Dongxu Li, Wenhan Luo, Jingyu Liu, Jiankang Deng, Wei Liu, Stefanos Zafeiriou
    http://arxiv.org/abs/2110.05031v1

    • [cs.CV]Efficient Training of High-Resolution Representation Seismic Image Fault Segmentation Network by Weakening Anomaly Labels
    Yimin Dou, Kewen Li, Jianbing Zhu, Shaoquan Tan, Zongchao Huang, Xiao Li
    http://arxiv.org/abs/2110.05319v1

    • [cs.CV]EfficientPhys: Enabling Simple, Fast and Accurate Camera-Based Vitals Measurement
    Xin Liu, Brian L. Hill, Ziheng Jiang, Shwetak Patel, Daniel McDuff
    http://arxiv.org/abs/2110.04447v1

    • [cs.CV]FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation
    Neelabh Sinha, Michal Balazia, François Bremond
    http://arxiv.org/abs/2110.04828v1

    • [cs.CV]Fast and Robust Structural Damage Analysis of Civil Infrastructure Using UAV Imagery
    Alon Oring
    http://arxiv.org/abs/2110.04806v1

    • [cs.CV]Fine_grained_Identity_Preserving_Landmark_Synthesis_for_Face_Reenactment
    Haichao Zhang, Youcheng Ben, Weixi Zhang, Tao Chen, Gang Yu, Bin Fu
    http://arxiv.org/abs/2110.04708v1

    • [cs.CV]Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization
    Ye Zheng, Xiang Wang, Rui Deng, Tianpeng Bao, Rui Zhao, Liwei Wu
    http://arxiv.org/abs/2110.04538v1

    • [cs.CV]Google Landmark Retrieval 2021 Competition Third Place Solution
    Qishen Ha, Bo Liu, Hongwei Zhang
    http://arxiv.org/abs/2110.04619v1

    • [cs.CV]Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks
    Moshe Eliasof, Benjamin Bodner, Eran Treister
    http://arxiv.org/abs/2110.04824v1

    • [cs.CV]Harnessing Unlabeled Data to Improve Generalization of Biometric Gender and Age Classifiers
    Aakash Varma Nadimpalli, Narsi Reddy, Sreeraj Ramachandran, Ajita Rattani
    http://arxiv.org/abs/2110.04427v1

    • [cs.CV]High-order Tensor Pooling with Attention for Action Recognition
    Piotr Koniusz, Lei Wang, Ke Sun
    http://arxiv.org/abs/2110.05216v1

    • [cs.CV]Identity-Guided Face Generation with Multi-modal Contour Conditions
    Qingyan Bai, Weihao Xia, Fei Yin, Yujiu Yang
    http://arxiv.org/abs/2110.04854v1

    • [cs.CV]Increasing a microscope’s effective field of view via overlapped imaging and machine learning
    Xing Yao, Vinayak Pathak, Haoran Xi, Amey Chaware, Colin Cooke, Kanghyun Kim, Shiqi Xu, Yuting Li, Timothy Dunn, Pavan Chandra Konda, Kevin C. Zhou, Roarke Horstmeyer
    http://arxiv.org/abs/2110.04921v1

    • [cs.CV]Investigating Transfer Learning Capabilities of Vision Transformers and CNNs by Fine-Tuning a Single Trainable Block
    Durvesh Malpure, Onkar Litake, Rajesh Ingle
    http://arxiv.org/abs/2110.05270v1

    • [cs.CV]K-Splits: Improved K-Means Clustering Algorithm to Automatically Detect the Number of Clusters
    Seyed Omid Mohammadi, Ahmad Kalhor, Hossein Bodaghi
    http://arxiv.org/abs/2110.04660v1

    • [cs.CV]K-Splits: Improved K-Means Clustering Algorithm to Automatically Detect the Number of Clusters
    Seyed Omid Mohammadi, Ahmad Kalhor, Hossein Bodaghi
    http://arxiv.org/abs/2110.0
    a45
    4660v1
    a45
    4660v1)

    • [cs.CV]LDC-Net: A Unified Framework for Localization, Detection and Counting in Dense Crowds
    Qi wang, Tao Han, Junyu Gao, Yuan Yuan, Xuelong Li
    http://arxiv.org/abs/2110.04727v1

    • [cs.CV]LSC-GAN: Latent Style Code Modeling for Continuous Image-to-image Translation
    Qiusheng Huang, Xueqi Hu, Li Sun, Qingli Li
    http://arxiv.org/abs/2110.05052v1

    • [cs.CV]Label quality in AffectNet: results of crowd-based re-annotation
    Doo Yon Kim, Christian Wallraven
    http://arxiv.org/abs/2110.04476v1

    • [cs.CV]Label-Occurrence-Balanced Mixup for Lo
    1398
    ng-tailed Recognition
    Shaoyu Zhang, Chen Chen, Xiujuan Zhang, Silong Peng
    http://arxiv.org/abs/2110.04964v1

    • [cs.CV]Learnable Adaptive Cosine Estimator (LACE) for Image Classification
    Joshua Peeples, Connor McCurley, Sarah Walker, Dylan Stewart, Alina Zare
    http://arxiv.org/abs/2110.05324v1

    • [cs.CV]Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency
    Soubhik Sanyal, Alex Vorobiov, Timo Bolkart, Matthew Loper, Betty Mohler, Larry Davis, Javier Romero, Michael J. Black
    http://arxiv.org/abs/2110.05458v1

    • [cs.CV]Learning Single/Multi-Attribute of Object with Symmetry and Group
    Yong-Lu Li, Yue Xu, Xinyu Xu, Xiaohan Mao, Cewu Lu
    http://arxiv.org/abs/2110.04603v1

    • [cs.CV]Learning a Self-Expressive Network for Subspace Clustering
    Shangzhi Zhang, Chong You, René Vidal, Chun-Guang Li
    http://arxiv.org/abs/2110.04318v1

    • [cs.CV]Modality-Guided Subnetwork for Salient Object Detection
    Zongwei Wu, Guillaume Allibert, Christophe Stolz, Chao Ma, Cédric Demonceaux
    http://arxiv.org/abs/2110.04904v1

    • [cs.CV]Morphable Detector for Object Detection on Demand
    Xiangyun Zhao, Xu Zou, Ying Wu
    http://arxiv.org/abs/2110.04917v1

    • [cs.CV]Multi-Class Cell Detection Using Spatial Context Representation
    Shahira Abousamra, David Belinsky, John Van Arnam, Felicia Allard, Eric Yee, Rajarsi Gupta, Tahsin Kurc, Dimitris Samaras, Joel Saltz, Chao Chen
    http://arxiv.org/abs/2110.04886v1

    • [cs.CV]Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT
    Xianghua Ye, Dazhou Guo, Chen-kan Tseng, Jia Ge, Tsung-Min Hung, Ping-Ching Pai, Yanping Ren, Lu Zheng, Xinli Zhu, Ling Peng, Ying Chen, Xiaohua Chen, Chen-Yu Chou, Danni Chen, Jiaze Yu, Yuzhen Chen, Feiran Jiao, Yi Xin, Lingyun Huang, Guotong Xie, Jing Xiao, Le Lu, Senxiang Yan, Dakai Jin, Tsung-Ying Ho
    http://arxiv.org/abs/2110.05280v1

    • [cs.CV]Multiple Object Trackers in OpenCV: A Benchmark
    Nađa Dardagan, Adnan Brđanin, Džemil Džigal, Amila Akagic
    http://arxiv.org/abs/2110.05102v1

    • [cs.CV]NViT: Vision Transformer Compression and Parameter Redistribution
    Huanrui Yang, Hongxu Yin, Pavlo Molchanov, Hai Li, Jan Kautz
    http://arxiv.org/abs/2110.04869v1

    • [cs.CV]Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans
    Ainaz Eftekhar, Alexander Sax, Roman Bachmann, Jitendra Malik, Amir Zamir
    http://arxiv.org/abs/2110.04994v1

    • [cs.CV]Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery
    Thomas W. Webb, Neelanjan Bhowmik, Yona Falinie A. Gaus, Toby P. Breckon
    http://arxiv.org/abs/2110.04906v1

    • [cs.CV]Pano-AVQA: Grounded Audio-Visual Question Answering on 360今日学术视野(2021.10.13) - 图7 Videos
    Heeseung Yun, Youngjae Yu, Wonsuk Yang, Kangil Lee, Gunhee Kim
    http://arxiv.org/abs/2110.05122v1

    • [cs.CV]Performance Evaluation of Deep Transfer Learning on Multiclass Identification of Common Weed Species in Cotton Production Systems
    Dong Chen, Yuzhen Lu, Zhaojiang Li, Sierra Young
    http://arxiv.org/abs/2110.04960v1

    • [cs.CV]Point Cloud Augmentation with Weighted Local Transformations
    Sihyeon Kim, Sanghyeok Lee, Dasol Hwang, Jaewon Lee, Seong Jae Hwang, Hyunwoo J. Kim
    http://arxiv.org/abs/2110.05379v1

    • [cs.CV]Predicting decision-making in the future: Human versus Machine
    Hoe Sung Ryu, Uijong Ju, Christian Wallraven
    http://arxiv.org/abs/2110.04465v1

    • [cs.CV]RankingMatch: Delving into Semi-Supervised Learning with Consistency Regularization and Ranking Loss
    Trung Q. Tran, Mingu Kang, Daeyoung Kim
    http://arxiv.org/abs/2110.04430v1

    • [cs.CV]Recurrent Attention Models with Object-centric Capsule Representation for Multi-object Recognition
    Hossein Adeli, Seoyoung Ahn, Gregory Zelinsky
    http://arxiv.org/abs/2110.04954v1

    • [cs.CV]Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Framework
    Qing Yang, Yaping Zhao
    http://arxiv.org/abs/2110.04966v1

    • [cs.CV]Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning
    Chongjian Ge, Youwei Liang, Yibing Song, Jianbo Jiao, Jue Wang, Ping Luo
    http://arxiv.org/abs/2110.05340v1

    • [cs.CV]Robustness Evaluation of Transformer-based Form Field Extractors via Form Attacks
    Le Xue, Mingfei Gao, Zeyuan Chen, Caiming Xiong, Ran Xu
    http://arxiv.org/abs/2110.04413v1

    • [cs.CV]SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification
    Baoquan Zhang, Shanshan Feng, Xutao Li, Yunming Ye, Rui Ye
    http://arxiv.org/abs/2110.04494v1

    • [cs.CV]SOMA: Solving Optical Marker-Based MoCap Automatically
    Nima Ghorbani, Michael J. Black
    http://arxiv.org/abs/2110.04431v1

    • [cs.CV]Self-Supervised 3D Face Reconstruction via Conditional Estimation
    Yandong Wen, Weiyang Liu, Bhiksha Raj, Rita Singh
    http://arxiv.org/abs/2110.04800v1

    • [cs.CV]Self-appearance-aided Differential Evolution for Motion Transfer
    Peirong Liu, Rui Wang, Xuefei Cao, Yipin Zhou, Ashish Shah, Maxime Oquab, Camille Couprie, Ser-Nam Lim
    http://arxiv.org/abs/2110.04658v1

    • [cs.CV]Semi-Autoregressive Image Captioning
    Xu Yan, Zhengcong Fei, Zekang Li, Shuhui Wang, Qingming Huang, Qi Tian
    http://arxiv.org/abs/2110.05342v1

    • [cs.CV]Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning
    Hanzhe Hu, Fangyun Wei, Han Hu, Qiwei Ye, Jinshi Cui, Liwei Wang
    http://arxiv.org/abs/2110.05474v1

    • [cs.CV]SignBERT: Pre-Training of Hand-Model-Aware Representation for Sign Language Recognition
    Hezhen Hu, Weichao Zhao, Wengang Zhou, Yuechen Wang, Houqiang Li
    http://arxiv.org/abs/2110.05382v1

    • [cs.CV]Sim2Air - Synthetic aerial dataset for UAV monitoring
    Antonella Barisic, Frano Petric, Stjepan Bogdan
    http://arxiv.org/abs/2110.05145v1

    • [cs.CV]Sketch Me A Video
    Haichao Zhang, Gang Yu, Tao Chen, Guozhong Luo
    http://arxiv.org/abs/2110.04710v1

    • [cs.CV]Space-Time-Separable Graph Convolutional Network for Pose Forecasting
    Theodoros Sofianos, Alessio Sampieri, Luca Franco, Fabio Galasso
    http://arxiv.org/abs/2110.04573v1

    • [cs.CV]Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception
    Ziwei Wang, Liyuan Pan, Yonhon Ng, Zheyu Zhuang, Robert Mahony
    http://arxiv.org/abs/2110.04988v1

    • [cs.CV]Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
    Yangguang Li, Feng Liang, Lichen Zhao, Yufeng Cui, Wanli Ouyang, Jing Shao, Fengwei Yu, Junjie Yan
    http://arxiv.org/abs/2110.05208v1

    • [cs.CV]SurroundNet: Towards Effective Low-Light Image Enhancement
    Fei Zhou, Xin Sun, Junyu Dong, Haoran Zhao, Xiao Xiang Zhu
    http://arxiv.org/abs/2110.05098v1

    • [cs.CV]Synthetic Data for Multi-Parameter Camera-Based Physiological Sensing
    Daniel McDuff, Xin Liu, Javier Hernandez, Erroll Wood, Tadas Baltrusaitis
    http://arxiv.org/abs/2110.04902v1

    • [cs.CV]TSG: Target-Selective Gradient Backprop for Probing CNN Visual Saliency
    Lin Cheng, Pengfei Fang, Yanjie Liang, Liao Zhang, Chunhua Shen, Hanzi Wang
    http://arxiv.org/abs/2110.05182v1

    • [cs.CV]Temporally Consistent Video Colorization with Deep Feature Propagation and Self-regularization Learning
    Yihao Liu, Hengyuan Zhao, Kelvin C. K. Chan, Xintao Wang, Chen Change Loy, Yu Qiao, Chao Dong
    http://arxiv.org/abs/2110.04562v1

    • [cs.CV]The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation
    Guillem Brasó, Nikita Kister, Laura Leal-Taixé
    http://arxiv.org/abs/2110.05132v1

    • [cs.CV]Towards Streaming Egocentric Action Anticipation
    Antonino Furnari, Giovanni Maria Farinella
    http://arxiv.org/abs/2110.05386v1

    • [cs.CV]Transformer-based Dual Relation Graph for Multi-label Image Recognition
    Jiawei Zhao, Ke Yan, Yifan Zhao, Jia Li
    http://arxiv.org/abs/2110.04722v1

    • [cs.CV]Two-stage Visual Cues Enhancement Network for Referring Image Segmentation
    Yang Jiao, Zequn Jie, Weixin Luo, Jingjing Chen, Yu-Gang Jiang, Xiaolin Wei, Lin Ma
    http://arxiv.org/abs/2110.04435v1

    • [cs.CV]Unsupervised High-Fidelity Facial Texture Generation and Reconstruction
    Ron Slossberg, Ibrahim Jubran, Ron Kimmel
    http://arxiv.org/abs/2110.04760v1

    • [cs.CV]Unsupervised Pose-Aware Part Decomposition for 3D Articulated Objects
    Yuki Kawana, Yusuke Mukuta, Tatsuya Harada
    http://arxiv.org/abs/2110.04411v1

    • [cs.CV]Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification
    Jinghan Sun, Dong Wei, Kai Ma, Liansheng Wang, Yefeng Zheng
    http://arxiv.org/abs/2110.04558v1

    • [cs.CV]VTBR: Semantic-based Pretraining for Person Re-Identification
    Suncheng Xiang, Zirui Zhang, Mengyuan Guan, Hao Chen, Binjie Yan, Ting Liu, Yuzhuo Fu
    http://arxiv.org/abs/2110.05074v1

    • [cs.CV]Vector-quantized Image Modeling with Improved VQGAN
    Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, Yonghui Wu
    http://arxiv.org/abs/2110.04627v1

    • [cs.CV]Vectorization of Raster Manga by Deep Reinforcement Learning
    Hao Su, Jianwei Niu, Xuefeng Liu, Jiahe Cui, Ji Wan
    http://arxiv.org/abs/2110.04830v1

    • [cs.CV]ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation
    Aiden Seungjoon Lee, Hanseok Oh, Minjoon Seo
    http://arxiv.org/abs/2110.05146v1

    • [cs.CV]Visualizing the embedding space to explain the effect of knowledge distillation
    Hyun Seung Lee, Christian Wallraven
    http://arxiv.org/abs/2110.04483v1

    • [cs.CV]Weakly Supervised Contrastive Learning
    Mingkai Zheng, Fei Wang, Shan You, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu
    http://arxiv.org/abs/2110.04770v1

    • [cs.CV]Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values
    Zhenquan Lin, Kailing Guo, Xiaofen Xing, Xiangmin Xu
    http://arxiv.org/abs/2110.04492v1

    • [cs.CV]ZARTS: On Zero-order Optimization for Neural Architecture Search
    Xiaoxing Wang, Wenxuan Guo, Junchi Yan, Jianlin Su, Xiaokang Yang
    http://arxiv.org/abs/2110.04743v1

    • [cs.CV]ZSpeedL — Evaluating the Performance of Zero-Shot Learning Methods using Low-Power Devices
    Cristiano Patrício, João Neves
    http://arxiv.org/abs/2110.04535v1

    • [cs.CY]A New Innovation Concept on End user Contextual and Behavioural Perspectives
    Reem Aman, Shah J. Miah, Janet Dzator
    http://arxiv.org/abs/2110.04539v1

    • [cs.CY]Algorithmic collusion: A critical review
    Florian E. Dorner
    http://arxiv.org/abs/2110.04740v1

    • [cs.CY]Emergent Insight of the Cyber Security Management for Saudi Arabian Universities: A Content Analysis
    Masmali, Miah
    http://arxiv.org/abs/2110.04540v1

    • [cs.CY]Ethical Assurance: A practical approach to the responsible design, development, and deployment of data-driven technologies
    Christopher Burr, David Leslie
    http://arxiv.org/abs/2110.05164v1

    • [cs.CY]Using Edge Cases to Disentangle Fairness and Solidarity in AI Ethics
    James Brusseau
    http://arxiv.org/abs/2110.04837v1

    • [cs.DC]A State Transfer Method That Adapts to Network Bandwidth Variations in Geographic State Machine Replication
    Tairi Chiba, Ren Ohmura, Junya Nakamura
    http://arxiv.org/abs/2110.04448v1

    • [cs.DC]Beyond Desktop Computation: Challenges in Scaling a GPU Infrastructure
    Martin Uray, Eduard Hirsch, Gerold Katzinger, Michael Gadermayr
    http://arxiv.org/abs/2110.05156v1

    • [cs.DC]Deploying Containerized QuantEx Quantum Simulation Software on HPC Systems
    David Brayford, John Brennan, Momme Allalen, Kenneth Hanley, Luigi Iapichino, Lee ORiordan, Niall Moran
    http://arxiv.org/abs/2110.05162v1

    • [cs.DC]Dual Attention-Based Federated Learning for Wireless Traffic Prediction
    Chuanting Zhang, Shuping Dang, Basem Shihada, Mohamed-Slim Alouini
    http://arxiv.org/abs/2110.05183v1

    • [cs.DC]Evaluation and Ranking of Replica Deployments in Geographic State Machine Replication
    Shota Numakura, Junya Nakamura, Ren Ohmura
    http://arxiv.org/abs/2110.04615v1

    • [cs.DC]Parallel Minimum Spanning Forest Computation using Sparse Matrix Kernels
    Tim Baer, Raghavendra Kanakagiri, Edgar Solomonik
    http://arxiv.org/abs/2110.04865v1

    • [cs.DC]SplitPlace: Intelligent Placement of Split Neural Nets in Mobile Edge Environments
    Shreshth Tuli
    http://arxiv.org/abs/2110.04841v1

    • [cs.DC]Themis: A Network Bandwidth-Aware Collective Scheduling Policy for Distributed Training of DL Models
    Saeed Rashidi, William Won, Sudarshan Srinivasan, Srinivas Sridharan, Tushar Krishna
    http://arxiv.org/abs/2110.04478v1

    • [cs.GR]Mesh Draping: Parametrization-Free Neural Mesh Transfer
    Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-Hornung, Daniel Cohen-Or
    http://arxiv.org/abs/2110.05433v1

    • [cs.GT]An Independent Learning Algorithm for a Class of Symmetric Stochastic Games
    Bora Yongacoglu, Gürdal Arslan, Serdar Yüksel
    http://arxiv.org/abs/2110.04638v1

    • [cs.GT]Transaction Fees on a Honeymoon: Ethereum’s EIP-1559 One Month Later
    Daniel Reijsbergen, Shyam Sridhar, Barnabe Monnot, Stefanos Leonardos, Stratis Skoulakis, Georgios Piliouras
    http://arxiv.org/abs/2110.04753v1

    • [cs.HC]A Deep Generative Model for Matrix Reordering
    Oh-Hyun Kwon, Chiun-How Kao, Chun-houh Chen, Kwan-Liu Ma
    http://arxiv.org/abs/2110.04971v1

    • [cs.HC]Accessible Visualization via Natural Language Descriptions: A Four-Level Model of Semantic Content
    Alan Lundgard, Arvind Satyanarayan
    http://arxiv.org/abs/2110.04406v1

    • [cs.HC]Clustering Human Trust Dynamics for Customized Real-time Prediction
    Jundi Liu, Kumar Akash, Teruhisa Misu, Xingwei Wu
    http://arxiv.org/abs/2110.04437v1

    • [cs.HC]Scope2Screen: Focus+Context Techniques for Pathology Tumor Assessment in Multivariate Image Data
    Jared Jessup, Robert Krueger, Simon Warchol, John Hoffer, Jeremy Muhlich, Cecily C. Ritch, Giorgio Gaglia, Shannon Coy, Yu-An Chen, Jia-Ren Lin, Sandro Santagata, Peter K. Sorger, Hanspeter Pfister
    http://arxiv.org/abs/2110.04875v1

    • [cs.HC]Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings
    Simone Azeglio, Arianna Di Bernardo, Gabriele Penna, Fabrizio Pittatore, Simone Poetto, Johannes Gruenwald, Christoph Kapeller, Kyousuke Kamada, Christoph Guger
    http://arxiv.org/abs/2110.04653v1

    • [cs.IR]AskMe: Joint Individual-level and Community-level Behavior Interaction for Question Recommendation
    Nuo Li, Bin Guo, Yan Liu, Lina Yao, Jiaqi Liu, Zhiwen Yu
    http://arxiv.org/abs/2110.05295v1

    • [cs.IR]Controllable Recommenders using Deep Generative Models and Disentanglement
    Samarth Bhargav, Evangelos Kanoulas
    http://arxiv.org/abs/2110.05056v1

    • [cs.IR]Developing Smart Web-Search Using RegEx
    Ikechukwu Onyenwe, Stanley Ogbonna, Ebele Onyedimma, Onyedikachukwu Ikechukwu-Onyenwe, Chidinma Nwafor
    http://arxiv.org/abs/2110.04767v1

    • [cs.IR]Feature Selection for Recommender Systems with Quantum Computing
    Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
    http://arxiv.org/abs/2110.05089v1

    • [cs.IR]Lookup or Exploratory: What is Your Search Intent?
    Manoj K. Agarwal, Tezan Sahu
    http://arxiv.org/abs/2110.04640v1

    • [cs.IT]A Framework for Private Communication with Secret Block Structure
    Maxime Ferreira Da Costa, Urbashi Mitra
    http://arxiv.org/abs/2110.04345v1

    • [cs.IT]A Generalization of Array Codes with Local Properties and Efficient Encoding/Decoding
    Hanxu Hou, Yunghsiang S. Han, Patrick P. C. Lee, You Wu, Guojun Han, Mario Blaum
    http://arxiv.org/abs/2110.04785v1

    • [cs.IT]A Novel Negative 今日学术视野(2021.10.13) - 图8 Penalty Approach for Multiuser One-Bit Massive MIMO Downlink with PSK Signaling
    Zheyu Wu, Bo Jiang, Ya-Feng Liu, Yu-Hong Dai
    http://arxiv.org/abs/2110.04768v1

    • [cs.IT]A Novel Quantum Calculus-based Complex Least Mean Square Algorithm (q-CLMS)
    Alishba Sadiq, Imran Naseem, Shujaat Khan, Muhammad Moinuddin, Roberto Togneri, Mohammed Bennamoun
    http://arxiv.org/abs/2110.04453v1

    • [cs.IT]Adaptive F-FFT Demodulation for ICI Mitigation in Differential Underwater Acoustic OFDM Systems
    Jihui Qiu, Yuzhou Li, Yunlong Huang, Yimeng Wang, Lingyu Gu
    http://arxiv.org/abs/2110.05129v1

    • [cs.IT]An Information-Theoretic Analysis of The Cost of Decentralization for Learning and Inference Under Privacy Constraints
    Sharu Theresa Jose, Osvaldo Simeone
    http://arxiv.org/abs/2110.05014v1

    • [cs.IT]Deep Learning for Uplink Spectral Efficiency in Cell-Free Massive MIMO Systems
    Le Ty Khanh, Pham Quoc Viet, Ha Hoang Kha, Nguyen Minh Hoang
    http://arxiv.org/abs/2110.04968v1

    • [cs.IT]Efficiently and Globally Solving Joint Beamforming and Compression Problem in the Cooperative Cellular Network via Lagrangian Duality
    Xilai Fan, Ya-Feng Liu, Liang Liu
    http://arxiv.org/abs/2110.05085v1

    • [cs.IT]Enhancing Utility in the Watchdog Privacy Mechanism
    Mohammad Amin Zarrabian, Ni Ding, Parastoo Sadeghi, Thierry Rakotoarivelo
    http://arxiv.org/abs/2110.04724v1

    • [cs.IT]ProductAE: Towards Training Larger Channel Codes based on Neural Product Codes
    Mohammad Vahid Jamali, Hamid Saber, Homayoon Hatami, Jung Hyun Bae
    http://arxiv.org/abs/2110.04466v1

    • [cs.IT]Safeguarding UAV Networks Through Integrated Sensing, Jamming, and Communications
    Zhiqiang Wei, Fan Liu, Derrick Wing Kwan Ng, Robert Schober
    http://arxiv.org/abs/2110.04733v1

    • [cs.IT]Semi-Blind Multiuser Detection Under the Presence of Reconfigurable Intelligent Surfaces
    Nikolaos I. Miridakis, Theodoros A. Tsiftsis, Guanghua Yang, Panagiotis A. Karkazis, Helen C. Leligou
    http://arxiv.org/abs/2110.04736v1

    • [cs.IT]Simultaneous Transmitting and ReflectingIntelligent Surfaces-Empowered NOMA Networks
    Mahmoud Aldababsa, Aymen Khaleel, Ertugrul Basar
    http://arxiv.org/abs/2110.05311v1

    • [cs.IT]Sliced Mutual Information: A Scalable Measure of Statistical Dependence
    Ziv Goldfeld, Kristjan Greenewald
    http://arxiv.org/abs/2110.05279v1

    • [cs.IT]Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO System
    Pablo Millán Santos, B. R. Manoj, Meysam Sadeghi, Erik G. Larsson
    http://arxiv.org/abs/2110.04731v1

    • [cs.IT]Uplink Performance of Cell-Free Massive MIMO with Multi-Antenna Users Over Jointly-Correlated Rayleigh Fading Channels
    Zhe Wang, Jiayi Zhang, Bo Ai, Chau Yuen, Mérouane Debbah
    http://arxiv.org/abs/2110.04962v1

    • [cs.LG]A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise Datasets
    Jake Grigsby, Yanjun Qi
    http://arxiv.org/abs/2110.04698v1

    • [cs.LG]A Deep Learning Inference Scheme Based on Pipelined Matrix Multiplication Acceleration Design and Non-uniform Quantization
    Yuyang Zhang, Dik Hin Leung, Min Guo, Yijia Xiao, Haoyue Liu, Yunfei Li, Jiyuan Zhang, Guan Wang, Zhen Chen
    http://arxiv.org/abs/2110.04861v1

    • [cs.LG]A Proximal Algorithm for Sampling from Non-smooth Potentials
    Jiaming Liang, Yongxin Chen
    http://arxiv.org/abs/2110.04597v1

    • [cs.LG]A Review of Physics-based Machine Learning in Civil Engineering
    Shashank Reddy Vadyala, Sai Nethra Betgeri1, Dr. John C. Matthews, Dr. Elizabeth Matthews
    http://arxiv.org/abs/2110.04600v1

    • [cs.LG]A Survey on Proactive Customer Care: Enabling Science and Steps to Realize it
    Viswanath Ganapathy, Sauptik Dhar, Olimpiya Saha, Pelin Kurt Garberson, Javad Heydari, Mohak Shah
    http://arxiv.org/abs/2110.05015v1

    • [cs.LG]Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions
    Nicholas Gao, Stephan Günnemann
    http://arxiv.org/abs/2110.05064v1

    • [cs.LG]Accelerating Multi-Objective Neural Architecture Search by Random-Weight Evaluation
    Shengran Hu, Ran Cheng, Cheng He, Zhichao Lu, Jing Wang, Miao Zhang
    http://arxiv.org/abs/2110.05242v1

    • [cs.LG]Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning
    Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
    http://arxiv.org/abs/2110.05329v1

    • [cs.LG]Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting
    Luca Hermes, Barbara Hammer, Malte Schilling
    http://arxiv.org/abs/2110.04810v1

    • [cs.LG]Bid Optimization using Maximum Entropy Reinforcement Learning
    Mengjuan Liu, Jinyu Liu, Zhengning Hu, Yuchen Ge, Xuyun Nie
    http://arxiv.org/abs/2110.05032v1

    • [cs.LG]Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization
    Shixiang Shane Gu, Manfred Diaz, Daniel C. Freeman, Hiroki Furuta, Seyed Kamyar Seyed Ghasemipour, Anton Raichuk, Byron David, Erik Frey, Erwin Coumans, Olivier Bachem
    http://arxiv.org/abs/2110.04686v1

    • [cs.LG]Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
    Gen Li, Laixi Shi, Yuxin Chen, Yuantao Gu, Yuejie Chi
    http://arxiv.org/abs/2110.04645v1

    • [cs.LG]Breaking the Softmax Bottleneck for Sequential Recommender Systems with Dropout and Decoupling
    Ying-Chen Lin
    http://arxiv.org/abs/2110.05409v1

    • [cs.LG]Can Stochastic Gradient Langevin Dynamics Provide Differential Privacy for Deep\ Learning?
    Guy Heller, Ethan Fetaya
    http://arxiv.org/abs/2110.05057v1

    • [cs.LG]Certifying Robustness to Programmable Data Bias in Decision Trees
    Anna P. Meyer, Aws Albarghouthi, Loris D’Antoni
    http://arxiv.org/abs/2110.04363v1

    • [cs.LG]Chaos as an interpretable benchmark for forecasting and data-driven modelling
    William Gilpin
    http://arxiv.org/abs/2110.05266v1

    • [cs.LG]CoRGi: Content-Rich Graph Neural Networks with Attention
    Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zheng, Miltiadis Allamanis
    http://arxiv.org/abs/2110.04866v1

    • [cs.LG]Cognitively Inspired Learning of Incremental Drifting Concepts
    Mohammad Rostami, Aram Galstyan
    http://arxiv.org/abs/2110.04662v1

    • [cs.LG]Continual Learning with Differential Privacy
    Pradnya Desai, Phung Lai, NhatHai Phan, My T. Thai
    http://arxiv.org/abs/2110.05223v1

    • [cs.LG]Crack detection using tap-testing and machine learning techniques to prevent potential rockfall incidents
    Roya Nasimi, Fernando Moreu, John Stormont
    http://arxiv.org/abs/2110.04923v1

    • [cs.LG]Deep Learning of Potential Outcomes
    Bernard Koch, Tim Sainburg, Pablo Geraldo, Song Jiang, Yizhou Sun, Jacob Gates Foster
    http://arxiv.org/abs/2110.04442v1

    • [cs.LG]Density-Based Clustering with Kernel Diffusion
    Chao Zheng, Yingjie Chen, Chong Chen, Jianqiang Huang, Xian-Sheng Hua
    http://arxiv.org/abs/2110.05096v1

    • [cs.LG]Density-based interpretable hypercube region partitioning for mixed numeric and categorical data
    Samuel Ackerman, Eitan Farchi, Orna Raz, Marcel Zalmanovici, Maya Zohar
    http://arxiv.org/abs/2110.05430v1

    • [cs.LG]Differentially Private Approximate Quantiles
    Haim Kaplan, Shachar Schnapp, Uri Stemmer
    http://arxiv.org/abs/2110.05429v1

    • [cs.LG]Discriminative Multimodal Learning via Conditional Priors in Generative Models
    Rogelio A. Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
    http://arxiv.org/abs/2110.04616v1

    • [cs.LG]Disease Informed Neural Networks
    Sagi Shaier, Maziar Raissi
    http://arxiv.org/abs/2110.05445v1

    • [cs.LG]Disturbing Target Values for Neural Network Regularization
    Yongho Kim, Hanna Lukashonak, Paweena Tarepakdee, Klavdia Zavalich, Mofassir ul Islam Arif
    http://arxiv.org/abs/2110.05003v1

    • [cs.LG]Does Preprocessing Help Training Over-parameterized Neural Networks?
    Zhao Song, Shuo Yang, Ruizhe Zhang
    http://arxiv.org/abs/2110.04622v1

    • [cs.LG]Embed Everything: A Method for Efficiently Co-Embedding Multi-Modal Spaces
    Sarah Di, Robin Yu, Amol Kapoor
    http://arxiv.org/abs/2110.04599v1

    • [cs.LG]EnsembleNTLDetect: An Intelligent Framework for Electricity Theft Detection in Smart Grid
    Yogesh Kulkarni, Sayf Hussain Z, Krithi Ramamritham, Nivethitha Somu
    http://arxiv.org/abs/2110.04502v1

    • [cs.LG]Equivalence Analysis between Counterfactual Regret Minimization and Online Mirror Descent
    Weiming Liu, Huacong Jiang, Bin Li, Houqiang Li
    http://arxiv.org/abs/2110.04961v1

    • [cs.LG]Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?
    Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O’Donoghue, Benjamin Van Roy
    http://arxiv.org/abs/2110.04629v1

    • [cs.LG]Exchangeability-Aware Sum-Product Networks
    Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
    http://arxiv.org/abs/2110.05165v1

    • [cs.LG]Fair Regression under Sample Selection Bias
    Wei Du, Xintao Wu, Hanghang Tong
    http://arxiv.org/abs/2110.04372v1

    • [cs.LG]Fast Attributed Graph Embedding via Density of States
    Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu
    http://arxiv.org/abs/2110.05228v1

    • [cs.LG]Feature Imitating Networks
    Sari Saba-Sadiya, Tuka Alhanai, Mohammad M Ghassemi
    http://arxiv.org/abs/2110.04831v1

    • [cs.LG]Fitting large mixture models using stochastic component selection
    Milan Papež, Tomáš Pevný, Václav Šmídl
    http://arxiv.org/abs/2110.04776v1

    • [cs.LG]Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning
    Danruo Deng, Guangyong Chen, Jianye Hao, Qiong Wang, Pheng-Ann Heng
    http://arxiv.org/abs/2110.04593v1

    • [cs.LG]Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits
    Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
    http://arxiv.org/abs/2110.04844v1

    • [cs.LG]Gradual Federated Learning with Simulated Annealing
    Luong Trung Nguyen, Junhan Kim, Byonghyo Shim
    http://arxiv.org/abs/2110.05178v1

    • [cs.LG]Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
    Benjamin Hudson, Qingbiao Li, Matthew Malencia, Amanda Prorok
    http://arxiv.org/abs/2110.05291v1

    • [cs.LG]Graph Neural Networks in Real-Time Fraud Detection with Lambda Architecture
    Mingxuan Lu, Zhichao Han, Zitao Zhang, Yang Zhao, Yinan Shan
    http://arxiv.org/abs/2110.04559v1

    • [cs.LG]Graph-Guided Network for Irregularly Sampled Multivariate Time Series
    Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik
    http://arxiv.org/abs/2110.05357v1

    • [cs.LG]Heavy Ball Neural Ordinary Differential Equations
    Hedi Xia, Vai Suliafu, Hangjie Ji, Tan M. Nguyen, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
    http://arxiv.org/abs/2110.04840v1

    • [cs.LG]Heterogeneous Stream-reservoir Graph Networks with Data Assimilation
    Shengyu Chen, Alison Appling, Samantha Oliver, Hayley Corson-Dosch, Jordan Read, Jeffrey Sadler, Jacob Zwart, Xiaowei Jia
    http://arxiv.org/abs/2110.04959v1

    • [cs.LG]Homogeneous Learning: Self-Attention Decentralized Deep Learning
    Yuwei Sun, Hideya Ochiai
    http://arxiv.org/abs/2110.05290v1

    • [cs.LG]Hybrid Random Features
    Krzysztof Choromanski, Haoxian Chen, Han Lin, Yuanzhe Ma, Arijit Sehanobish, Deepali Jain, Michael S Ryoo, Jake Varley, Andy Zeng, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller
    http://arxiv.org/abs/2110.04367v1

    • [cs.LG]Instance-based Label Smoothing For Better Calibrated Classification Networks
    Mohamed Maher, Meelis Kull
    http://arxiv.org/abs/2110.05355v1

    • [cs.LG]Intriguing Properties of Input-dependent Randomized Smoothing
    Peter Súkeník, Aleksei Kuvshinov, Stephan Günnemann
    http://arxiv.org/abs/2110.05365v1

    • [cs.LG]Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning
    Trevor McInroe, Lukas Schäfer, Stefano V. Albrecht
    http://arxiv.org/abs/2110.04935v1

    • [cs.LG]Learning a subspace of policies for online adaptation in Reinforcement Learning
    Jean-Baptiste Gaya, Laure Soulier, Ludovic Denoyer
    http://arxiv.org/abs/2110.05169v1

    • [cs.LG]Learning from Ambiguous Demonstrations with Self-Explanation Guided Reinforcement Learning
    Yantian Zha, Lin Guan, Subbarao Kambhampati
    http://arxiv.org/abs/2110.05286v1

    • [cs.LG]Learning to Follow Language Instructions with Compositional Policies
    Vanya Cohen, Geraud Nangue Tasse, Nakul Gopalan, Steven James, Matthew Gombolay, Benjamin Rosman
    http://arxiv.org/abs/2110.04647v1

    • [cs.LG]Leveraging Transformers for StarCraft Macromanagement Prediction
    Muhammad Junaid Khan, Shah Hassan, Gita Sukthankar
    http://arxiv.org/abs/2110.05343v1

    • [cs.LG]Long Expressive Memory for Sequence Modeling
    T. Konstantin Rusch, Siddhartha Mishra, N. Benjamin Erichson, Michael W. Mahoney
    http://arxiv.org/abs/2110.04744v1

    • [cs.LG]Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks
    Cody Blakeney, Gentry Atkinson, Nathaniel Huish, Yan Yan, Vangelis Metris, Ziliang Zong
    http://arxiv.org/abs/2110.04397v1

    • [cs.LG]Mixture Model Auto-Encoders: Deep Clustering through Dictionary Learning
    Alexander Lin, Andrew H. Song, Demba Ba
    http://arxiv.org/abs/2110.04683v1

    • [cs.LG]Momentum Centering and Asynchronous Update for Adaptive Gradient Methods
    Juntang Zhuang, Yifan Ding, Tommy Tang, Nicha Dvornek, Sekhar Tatikonda, James S. Duncan
    http://arxiv.org/abs/2110.05454v1

    • [cs.LG]Multi-Agent MDP Homomorphic Networks
    Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling
    http://arxiv.org/abs/2110.04495v1

    • [cs.LG]Multi-Relation Aware Temporal Interaction Network Embedding
    Ling Chen, Shanshan Yu, Dandan Lyu, Da Wang
    http://arxiv.org/abs/2110.04503v1

    • [cs.LG]Multi-task learning on the edge: cost-efficiency and theoretical optimality
    Sami Fakhry, Romain Couillet, Malik Tiomoko
    http://arxiv.org/abs/2110.04639v1

    • [cs.LG]NFT-K: Non-Fungible Tangent Kernels
    Sina Alemohammad, Hossein Babaei, CJ Barberan, Naiming Liu, Lorenzo Luzi, Blake Mason, Richard G. Baraniuk
    http://arxiv.org/abs/2110.04945v1

    • [cs.LG]Neural Algorithmic Reasoners are Implicit Planners
    Andreea Deac, Petar Veličković, Ognjen Milinković, Pierre-Luc Bacon, Jian Tang, Mladen Nikolić
    http://arxiv.org/abs/2110.05442v1

    • [cs.LG]Neural Link Prediction with Walk Pooling
    Liming Pan, Cheng Shi, Ivan Dokmanić
    http://arxiv.org/abs/2110.04375v1

    • [cs.LG]Online Graph Learning in Dynamic Environments
    Xiang Zhang
    http://arxiv.org/abs/2110.05023v1

    • [cs.LG]Pairwise Margin Maximization for Deep Neural Networks
    Berry Weinstein, Shai Fine, Yacov Hel-Or
    http://arxiv.org/abs/2110.04519v1

    • [cs.LG]Performance Analysis of Fractional Learning Algorithms
    Abdul Wahab, Shujaat Khan, Imran Naseem, Jong Chul Ye
    http://arxiv.org/abs/2110.05201v1

    • [cs.LG]Phase Collapse in Neural Networks
    Florentin Guth, John Zarka, Stéphane Mallat
    http://arxiv.org/abs/2110.05283v1

    • [cs.LG]ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
    Hui-Po Wang, Sebastian U. Stich, Yang He, Mario Fritz
    http://arxiv.org/abs/2110.05323v1

    • [cs.LG]Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning
    Guanlin Liu, Lifeng Lai
    http://arxiv.org/abs/2110.04471v1

    • [cs.LG]REIN-2: Giving Birth to Prepared Reinforcement Learning Agents Using Reinforcement Learning Agents
    Aristotelis Lazaridis, Ioannis Vlahavas
    http://arxiv.org/abs/2110.05128v1

    • [cs.LG]Recurrent Model-Free RL is a Strong Baseline for Many POMDPs
    Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov
    http://arxiv.org/abs/2110.05038v1

    • [cs.LG]Reinforcement Learning In Two Player Zero Sum Simultaneous Action Games
    Patrick Phillips
    http://arxiv.org/abs/2110.04835v1

    • [cs.LG]Representation Learning for Online and Offline RL in Low-rank MDPs
    Masatoshi Uehara, Xuezhou Zhang, Wen Sun
    http://arxiv.org/abs/2110.04652v1

    • [cs.LG]SCEHR: Supervised Contrastive Learning for Clinical Risk Prediction using Electronic Health Records
    Chengxi Zang, Fei Wang
    http://arxiv.org/abs/2110.04943v1

    • [cs.LG]Self-explaining Neural Network with Plausible Explanations
    Sayantan Kumar, Sean C. Yu, Andrew Michelson, Philip R. O. Payne
    http://arxiv.org/abs/2110.04598v1

    • [cs.LG]Self-supervised Learning is More Robust to Dataset Imbalance
    Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma
    http://arxiv.org/abs/2110.05025v1

    • [cs.LG]Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families
    Goutham Rajendran, Bohdan Kivva, Ming Gao, Bryon Aragam
    http://arxiv.org/abs/2110.04719v1

    • [cs.LG]SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
    Talip Ucar, Ehsan Hajiramezanali, Lindsay Edwards
    http://arxiv.org/abs/2110.04361v1

    • [cs.LG]SuperShaper: Task-Agnostic Super Pre-training of BERT Models with Variable Hidden Dimensions
    Vinod Ganesan, Gowtham Ramesh, Pratyush Kumar
    http://arxiv.org/abs/2110.04711v1

    • [cs.LG]Surrogate-Assisted Reference Vector Adaptation to Various Pareto Front Shapes for Many-Objective Bayesian Optimization
    Nobuo Namura
    http://arxiv.org/abs/2110.04689v1

    • [cs.LG]The Skellam Mechanism for Differentially Private Federated Learning
    Naman Agarwal, Peter Kairouz, Ziyu Liu
    http://arxiv.org/abs/2110.04995v1

    • [cs.LG]Time Series Classification Using Convolutional Neural Network On Imbalanced Datasets
    Syed Rawshon Jamil
    http://arxiv.org/abs/2110.04748v1

    • [cs.LG]Time-varying Graph Learning Under Structured Temporal Priors
    Xiang Zhang, Qiao Wang
    http://arxiv.org/abs/2110.05018v1

    • [cs.LG]Towards Data-Free Domain Generalization
    Ahmed Frikha, Haokun Chen, Denis Krompaß, Thomas Runkler, Volker Tresp
    http://arxiv.org/abs/2110.04545v1

    • [cs.LG]Towards Demystifying Representation Learning with Non-contrastive Self-supervision
    Xiang Wang, Xinlei Chen, Simon S. Du, Yuandong Tian
    http://arxiv.org/abs/2110.04947v1

    • [cs.LG]Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach
    Qitian Wu, Chenxiao Yang, Junchi Yan
    http://arxiv.org/abs/2110.04514v1

    • [cs.LG]Two-level Group Convolution
    Youngkyu Lee, Jongho Park, Chang-Ock Lee
    http://arxiv.org/abs/2110.05060v1

    • [cs.LG]Understanding Pooling in Graph Neural Networks
    Daniele Grattarola, Daniele Zambon, Filippo Maria Bianchi, Cesare Alippi
    http://arxiv.org/abs/2110.05292v1

    • [cs.LG]Unsupervised Source Separation via Bayesian Inference in the Latent Domain
    Michele Mancusi, Emilian Postolache, Marco Fumero, Andrea Santilli, Luca Cosmo, Emanuele Rodolà
    http://arxiv.org/abs/2110.05313v1

    • [cs.LG]Value-Function-based Sequential Minimization for Bi-level Optimization
    Risheng Liu, Xuan Liu, Shangzhi Zeng, Jin Zhang, Yixuan Zhang
    http://arxiv.org/abs/2110.04974v1

    • [cs.LG]Widen The Backdoor To Let More Attackers In
    Siddhartha Datta, Giulio Lovisotto, Ivan Martinovic, Nigel Shadbolt
    http://arxiv.org/abs/2110.04571v1

    • [cs.LG]X-model: Improving Data Efficiency in Deep Learning with A Minimax Model
    Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long
    http://arxiv.org/abs/2110.04572v1

    • [cs.LG]You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction
    Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter Gehler, Dominik Janzing, Thomas Brox, Bernhard Schölkopf
    http://arxiv.org/abs/2110.05304v1

    • [cs.LO]Dynamic Logic of Legal Competences
    Huimin Dong, Olivier Roy
    http://arxiv.org/abs/2110.04454v1

    • [cs.MM]Real-time FPGA Design for OMP Targeting 8K Image Reconstruction
    Jiayao Xu, Chen Fu, Zhiqiang Zhang, Jinjia Zhou
    http://arxiv.org/abs/2110.04714v1

    • [cs.NE]Can the brain use waves to solve planning problems?
    Henry Powell, Mathias Winkel, Alexander V. Hopp, Helmut Linde
    http://arxiv.org/abs/2110.05158v1

    • [cs.NE]Learning Division with Neural Arithmetic Logic Modules
    Bhumika Mistry, Katayoun Farrahi, Jonathon Hare
    http://arxiv.org/abs/2110.05177v1

    • [cs.NE]Self-adaptive Multi-task Particle Swarm Optimization
    Xiaolong Zheng, Deyun Zhou, Na Li, Yu Lei, Tao Wu, Maoguo Gong
    http://arxiv.org/abs/2110.04473v1

    • [cs.NE]Time Complexity Analysis of Evolutionary Algorithms for 2-Hop (1,2)-Minimum Spanning Tree Problem
    Feng Shi, Frank Neumann, Jianxin Wang
    http://arxiv.org/abs/2110.04701v1

    • [cs.NE]Towards Explainable Real Estate Valuation via Evolutionary Algorithms
    Sebastian Angrick, Ben Bals, Niko Hastrich, Maximilian Kleissl, Jonas Schmidt, Vanja Doskoč, Maximilian Katzmann, Louise Molitor, Tobias Friedrich
    http://arxiv.org/abs/2110.05116v1

    • [cs.PL]Synthesizing Machine Learning Programs with PAC Guarantees via Statistical Sketching
    Osbert Bastani
    http://arxiv.org/abs/2110.05390v1

    • [cs.RO]AMRA: Anytime Multi-Resolution Multi-Heuristic A
    Dhruv Mauria Saxena, Tushar Kusnur, Maxim Likhachev
    http://arxiv.org/abs/2110.05328v1

    • [cs.RO]Adaptive Variable Impedance Control for a Modular Soft Robot Manipulator in Configuration Space
    Mahmood Mazare, Silvia Tolu, Mostafa Taghizadeh
    http://arxiv.org/abs/2110.04553v1

    • [cs.RO]An Augmented Reality Platform for Introducing Reinforcement Learning to K-12 Students with Robots
    Ziyi Zhang, Samuel Micah Akai-Nettey, Adonai Addo, Chris Rogers, Jivko Sinapov
    http://arxiv.org/abs/2110.04697v1

    • [cs.RO]Autonomous Racing using a Hybrid Imitation-Reinforcement Learning Architecture
    Chinmay Vilas Samak, Tanmay Vilas Samak, Sivanathan Kandhasamy
    http://arxiv.org/abs/2110.05437v1

    • [cs.RO]Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning
    Paul Maria Scheikl, Balázs Gyenes, Tornike Davitashvili, Rayan Younis, André Schulze, Beat P. Müller-Stich, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich
    http://arxiv.org/abs/2110.04857v1

    • [cs.RO]Credit Assignment Safety Learning from Human Demonstrations
    Ahalya Prabhakar, Aude Billard
    http://arxiv.org/abs/2110.04633v1

    • [cs.RO]Dynamic Control of Soft Robotic Arm
    Milad Azizkhani, Isuru S. Godage, Yue Chen
    http://arxiv.org/abs/2110.05001v1

    • [cs.RO]Human-Aware Robot Navigation via Reinforcement Learning with Hindsight Experience Replay and Curriculum Learning
    Keyu Li, Ye Lu, Max Q. -H. Meng
    http://arxiv.org/abs/2110.04564v1

    • [cs.RO]Humans’ Assessment of Robots as Moral Regulators: Importance of Perceived Fairness and Legitimacy
    Boyoung Kim, Elizabeth Phillips
    http://arxiv.org/abs/2110.04729v1

    • [cs.RO]Learning High-Speed Flight in the Wild
    Antonio Loquercio, Elia Kaufmann, René Ranftl, Matthias Müller, Vladlen Koltun, Davide Scaramuzza
    http://arxiv.org/abs/2110.05113v1

    • [cs.RO]Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Clouds
    Bao Thach, Brian Y. Cho, Alan Kuntz, Tucker Hermans
    http://arxiv.org/abs/2110.04685v1

    • [cs.RO]Learning to Control Complex Robots Using High-Dimensional Interfaces: Preliminary Insights
    Jongmin M. Lee, Temesgen Gebrekristos, Dalia De Santis, Mahdieh Nejati-Javaremi, Deepak Gopinath, Biraj Parikh, Ferdinando A. Mussa-Ivaldi, Brenna D. Argall
    http://arxiv.org/abs/2110.04663v1

    • [cs.RO]Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World
    Laura Smith, J. Chase Kew, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine
    http://arxiv.org/abs/2110.05457v1

    • [cs.RO]Leveraging Experience in Lazy Search
    Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots, Siddhartha Srinivasa
    http://arxiv.org/abs/2110.04669v1

    • [cs.RO]Multimodal Sensory Learning for Real-time, Adaptive Manipulation
    Ahalya Prabhakar, Stanislas Furrer, Lorenzo Panchetti, Maxence Perret, Aude Billard
    http://arxiv.org/abs/2110.04634v1

    • [cs.RO]Nano Version Control and Robots of Robots: Data Driven, Regenerative Production Code
    Lukasz Machowski, Tshilidzi Marwala
    http://arxiv.org/abs/2110.04755v1

    • [cs.RO]Navigation In Urban Environments Amongst Pedestrians Using Multi-Objective Deep Reinforcement Learning
    Niranjan Deshpande, Dominique Vaufreydaz, Anne Spalanzani
    http://arxiv.org/abs/2110.05205v1

    • [cs.RO]Optimal Stochastic Evasive Maneuvers Using the Schrodinger’s Equation
    Farhad Farokhi, Magnus Egerstedt
    http://arxiv.org/abs/2110.04956v1

    • [cs.RO]Safe Human-Interactive Control via Shielding
    Jeevana Priya Inala, Yecheng Jason Ma, Osbert Bastani, Xin Zhang, Armando Solar-Lezama
    http://arxiv.org/abs/2110.05440v1

    • [cs.RO]Scene Editing as Teleoperation: A Case Study in 6DoF Kit Assembly
    Shubham Agrawal, Yulong Li, Jen-Shuo Liu, Steven K. Feiner, Shuran Song
    http://arxiv.org/abs/2110.04450v1

    • [cs.RO]Teaching Robots to Grasp Like Humans: An Interactive Approach
    Anna Mészáros, Giovanni Franzese, Jens Kober
    http://arxiv.org/abs/2110.04534v1

    • [cs.RO]Vision-based Navigation for a Small-scale Quadruped Robot Pegasus-Mini
    Deng Ganyu, Luo Jianwen, Sun Caiming, Pan Dongwei, Peng Longyao, Ding Ning, Zhang Aidong
    http://arxiv.org/abs/2110.04426v1

    • [cs.SD]An Overview of Techniques for Biomarker Discovery in Voice Signal
    Rita Singh, Ankit Shah, Hira Dhamyal
    http://arxiv.org/abs/2110.04678v1

    • [cs.SD]Can Audio Captions Be Evaluated with Image Caption Metrics?
    Zelin Zhou, Zhiling Zhang, Xuenan Xu, Zeyu Xie, Mengyue Wu, Kenny Q. Zhu
    http://arxiv.org/abs/2110.04684v1

    • [cs.SD]Efficient Training of Audio Transformers with Patchout
    Khaled Koutini, Jan Schlüter, Hamid Eghbal-zadeh, Gerhard Widmer
    http://arxiv.org/abs/2110.05069v1

    • [cs.SD]LaughNet: synthesizing laughter utterances from waveform silhouettes and a single laughter example
    Hieu-Thi Luong, Junichi Yamagishi
    http://arxiv.org/abs/2110.04946v1

    • [cs.SD]Multi-task Learning with Metadata for Music Mood Classification
    Rajnish Kumar, Manjeet Dahiya
    http://arxiv.org/abs/2110.04765v1

    • [cs.SD]PAMA-TTS: Progression-Aware Monotonic Attention for Stable Seq2Seq TTS With Accurate Phoneme Duration Control
    Yunchao He, Jian Luan, Yujun Wang
    http://arxiv.org/abs/2110.04486v1

    • [cs.SD]Pitch Preservation In Singing Voice Synthesis
    Shujun Liu, Hai Zhu, Kun Wang, Huajun Wang
    http://arxiv.org/abs/2110.05033v1

    • [cs.SD]Streaming on-device detection of device directed speech from voice and touch-based invocation
    Ognjen Rudovic, Akanksha Bindal, Vineet Garg, Pramod Simha, Pranay Dighe, Sachin Kajarekar
    http://arxiv.org/abs/2110.04656v1

    • [cs.SD]Towards High-fidelity Singing Voice Conversion with Acoustic Reference and Contrastive Predictive Coding
    Chao Wang, Zhonghao Li, Benlai Tang, Xiang Yin, Yuan Wan, Yibiao Yu, Zejun Ma
    http://arxiv.org/abs/2110.04754v1

    • [cs.SD]Universal Paralinguistic Speech Representations Using Self-Supervised Conformers
    Joel Shor, Aren Jansen, Wei Han, Daniel Park, Yu Zhang
    http://arxiv.org/abs/2110.04621v1

    • [cs.SD]Using multiple reference audios and style embedding constraints for speech synthesis
    Cheng Gong, Longbiao Wang, Zhenhua Ling, Ju Zhang, Jianwu Dang
    http://arxiv.org/abs/2110.04451v1

    • [cs.SE]Automatic Recall of Software Lessons Learned for Software Project Managers
    Tamer Mohamed Abdellatif, Luiz Fernando Capretz, Danny Ho
    http://arxiv.org/abs/2110.05261v1

    • [cs.SE]Graph-Based Machine Learning Improves Just-in-Time Defect Prediction
    Jonathan Bryan, Pablo Moriano
    http://arxiv.org/abs/2110.05371v1

    • [cs.SE]Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?
    Fabio Calefato, Filippo Lanubile
    http://arxiv.org/abs/2110.05035v1

    • [cs.SI]An Analysis of COVID-19 Knowledge Graph Construction and Applications
    Dominic Flocco, Bryce Palmer-Toy, Ruixiao Wang, Hongyu Zhu, Rishi Sonthalia, Junyuan Lin, Andrea L. Bertozzi, P. Jeffrey Brantingham
    http://arxiv.org/abs/2110.04932v1

    • [cs.SI]Influencing the Influencers: Evaluating Person-to-Person Influence on Social Networks Using Granger Causality
    Richard Kuzma, Iain J. Cruickshank, Kathleen M. Carley
    http://arxiv.org/abs/2110.04899v1

    • [cs.SI]The Role of Masks in Mitigating Viral Spread on Networks
    Yurun Tian, Anirudh Sridhar, H. Vincent Poor, Osman Yagan
    http://arxiv.org/abs/2110.04398v1

    • [econ.EM]On the asymptotic behavior of bubble date estimators
    Eiji Kurozumi, Anton Skrobotov
    http://arxiv.org/abs/2110.04500v1

    • [eess.AS]A Comparative Study on Non-Autoregressive Modelings for Speech-to-Text Generation
    Yosuke Higuchi, Nanxin Chen, Yuya Fujita, Hirofumi Inaguma, Tatsuya Komatsu, Jaesong Lee, Jumon Nozaki, Tianzi Wang, Shinji Watanabe
    http://arxiv.org/abs/2110.05249v1

    • [eess.AS]Complex Network-Based Approach for Feature Extraction and Classification of Musical Genres
    Matheus Henrique Pimenta-Zanon, Glaucia Maria Bressan, Fabrício Martins Lopes
    http://arxiv.org/abs/2110.04654v1

    • [eess.AS]Injecting Text and Cross-lingual Supervision in Few-shot Learning from Self-Supervised Models
    Matthew Wiesner, Desh Raj, Sanjeev Khudanpur
    http://arxiv.org/abs/2110.04863v1

    • [eess.AS]Interactive Feature Fusion for End-to-End Noise-Robust Speech Recognition
    Yuchen Hu, Nana Hou, Chen Chen, Eng Siong Chng
    http://arxiv.org/abs/2110.05267v1

    • [eess.AS]Multi-Channel End-to-End Neural Diarization with Distributed Microphones
    Shota Horiguchi, Yuki Takashima, Paola Garcia, Shinji Watanabe, Yohei Kawaguchi
    http://arxiv.org/abs/2110.04694v1

    • [eess.AS]Multi-View Self-Attention Based Transformer for Speaker Recognition
    Rui Wang, Junyi Ao, Long Zhou, Shujie Liu, Zhihua Wei, Tom Ko, Qing Li, Yu Zhang
    http://arxiv.org/abs/2110.05036v1

    • [eess.AS]Personalized Automatic Speech Recognition Trained on Small Disordered Speech Datasets
    Jimmy Tobin, Katrin Tomanek
    http://arxiv.org/abs/2110.04612v1

    • [eess.AS]Stepwise-Refining Speech Separation Network via Fine-Grained Encoding in High-order Latent Domain
    Zengwei Yao, Wenjie Pei, Fanglin Chen, Guangming Lu, David Zhang
    http://arxiv.org/abs/2110.04791v1

    • [eess.AS]Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis
    Mu Yang, Shaojin Ding, Tianlong Chen, Tong Wang, Zhangyang Wang
    http://arxiv.org/abs/2110.04482v1

    • [eess.AS]Wav2vec-S: Semi-Supervised Pre-Training for Speech Recognition
    Han Zhu, Li Wang, Ying Hou, Jindong Wang, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan
    http://arxiv.org/abs/2110.04484v1

    • [eess.IV]AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation
    Syeda Furruka Banu, Md. Mostafa Kamal Sarker, Mohamed Abdel-Nasser, Domenec Puig, Hatem A. Raswan
    http://arxiv.org/abs/2110.05144v1

    • [eess.IV]DenseNet approach to segmentation and classification of dermatoscopic skin lesions images
    Reza Zare, Arash Pourkazemi
    http://arxiv.org/abs/2110.04632v1

    • [eess.IV]Exploring constraints on CycleGAN-based CBCT enhancement for adaptive radiotherapy
    Suraj Pai
    http://arxiv.org/abs/2110.04659v1

    • [eess.IV]Invertible Tone Mapping with Selectable Styles
    Zhuming Zhang, Menghan Xia, Xueting Liu, Chengze Li, Tien-Tsin Wong
    http://arxiv.org/abs/2110.04491v1

    • [eess.IV]Learning MRI Artifact Removal With Unpaired Data
    Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap
    http://arxiv.org/abs/2110.04604v1

    • [eess.IV]NormVAE: Normative Modeling on Neuroimaging Data using Variational Autoencoders
    Sayantan Kumar, Aristeidis Sotiras
    http://arxiv.org/abs/2110.04903v1

    • [eess.IV]Rethinking Noise Synthesis and Modeling in Raw Denoising
    Yi Zhang, Hongwei Qin, Xiaogang Wang, Hongsheng Li
    http://arxiv.org/abs/2110.04756v1

    • [eess.IV]Spatial-temporal V-Net for automatic segmentation and quantification of right ventricles in gated myocardial perfusion SPECT images
    Chen Zhao, Shi Shi, Zhuo He, Cheng Wang, Zhongqiang Zhao, Xinli Li, Yanli Zhou, Weihua Zhou
    http://arxiv.org/abs/2110.05443v1

    • [eess.IV]Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images
    Kongming Liang, Kai Han, Xiuli Li, Xiaoqing Cheng, Yiming Li, Yizhou Wang, Yizhou Yu
    http://arxiv.org/abs/2110.05039v1

    • [eess.IV]Vision Transformer based COVID-19 Detection using Chest X-rays
    Koushik Sivarama Krishnan, Karthik Sivarama Krishnan
    http://arxiv.org/abs/2110.04458v1

    • [eess.SP]A Hybrid Scattering Transform for Signals with Isolated Singularities
    Michael Perlmutter, Jieqian He, Mark Iwen, Matthew Hirn
    http://arxiv.org/abs/2110.04910v1

    • [eess.SP]An Efficient Deep Learning Model for Automatic Modulation Recognition Based on Parameter Estimation and Transformation
    Fuxin Zhang, Chunbo Luo, Jialang Xu, Yang Luo
    http://arxiv.org/abs/2110.04980v1

    • [eess.SP]Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Rate Control
    Mingyu Yang, Hun-Seok Kim
    http://arxiv.org/abs/2110.04456v1

    • [eess.SP]Stability of Neural Networks on Manifolds to Relative Perturbations
    Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
    http://arxiv.org/abs/2110.04702v1

    • [eess.SP]Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space Models
    Itzik Klein, Guy Revach, Nir Shlezinger, Jonas E. Mehr, Ruud J. G. van Sloun, Yonina. C. Eldar
    http://arxiv.org/abs/2110.04738v1

    • [eess.SY]Artificial Intelligence in Electric Machine Drives: Advances and Trends
    Shen Zhang
    http://arxiv.org/abs/2110.05403v1

    • [eess.SY]Non-Parametric Neuro-Adaptive Coordination of Multi-Agent Systems
    Christos K. Verginis, Zhe Xu, Ufuk Topcu
    http://arxiv.org/abs/2110.05125v1

    • [eess.SY]Safe Model-Based Reinforcement Learning Using Robust Control Barrier Functions
    Yousef Emam, Paul Glotfelter, Zsolt Kira, Magnus Egerstedt
    http://arxiv.org/abs/2110.05415v1

    • [eess.SY]When is gray-box modeling advantageous for virtual flow metering?
    M. Hotvedt, B. Grimstad, D. Ljungquist, L. Imsland
    http://arxiv.org/abs/2110.05034v1

    • [math.CO]On 今日学术视野(2021.10.13) - 图9-ary shortened-今日学术视野(2021.10.13) - 图10-perfect-like codes
    Minjia Shi, Rongsheng Wu, Denis S. Krotov
    http://arxiv.org/abs/2110.05256v1

    • [math.CT]Compositionality as we see it, everywhere around us
    Bob Coecke
    http://arxiv.org/abs/2110.05327v1

    • [math.FA]Fat-shattering dimension of 今日学术视野(2021.10.13) - 图11-fold maxima
    Aryeh Kontorovich, Idan Attias
    http://arxiv.org/abs/2110.04763v1

    • [math.OC]An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models
    Arjun Ashok Rao, Hoi-To Wai
    http://arxiv.org/abs/2110.04523v1

    • [math.OC]Convergence of Random Reshuffling Under The Kurdyka-Łojasiewicz Inequality
    Xiao Li, Andre Milzarek, Junwen Qiu
    http://arxiv.org/abs/2110.04926v1

    • [math.OC]Finding Second-Order Stationary Point for Nonconvex-Strongly-Concave Minimax Problem
    Luo Luo, Cheng Chen
    http://arxiv.org/abs/2110.04814v1

    • [math.PR]A tractable class of Multivariate Phase-type distributions for loss modeling: Theoretical developments
    Martin Bladt
    http://arxiv.org/abs/2110.05179v1

    • [math.PR]Tails of bivariate stochastic recurrence equation
    Ewa Damek, Muneya Matsui
    http://arxiv.org/abs/2110.04546v1

    • [math.ST]Approximating Familywise Error Rate for Correlated Normal
    Monitirtha Dey
    http://arxiv.org/abs/2110.05070v1

    • [math.ST]Dynamic Precise and Imprecise Probability Kinematics
    Michele Caprio, Ruobin Gong
    http://arxiv.org/abs/2110.04382v1

    • [math.ST]Exact Matching of Random Graphs with Constant Correlation
    Cheng Mao, Mark Rudelson, Konstantin Tikhomirov
    http://arxiv.org/abs/2110.05000v1

    • [math.ST]Learning from non-irreducible Markov chains
    Nikola Sandrić, Stjepan Šebek
    http://arxiv.org/abs/2110.04338v1

    • [math.ST]Optional Pólya trees: posterior rates and uncertainty quantification
    Ismaël Castillo, Thibault Randrianarisoa
    http://arxiv.org/abs/2110.05265v1

    • [math.ST]Pairwise interaction function estimation of Gibbs point processes using basis expansion
    Ismaïla Ba, Jean-François Coeurjolly, Francisco Cuevas-Pacheco
    http://arxiv.org/abs/2110.05391v1

    • [math.ST]Two-stage least squares with a randomly right censored outcome
    Jad Beyhum
    http://arxiv.org/abs/2110.05107v1

    • [physics.geo-ph]Deep Bayesian inference for seismic imaging with tasks
    Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
    http://arxiv.org/abs/2110.04825v1

    • [physics.geo-ph]Lithological Tomography with the Correlated Pseudo-Marginal Method
    Lea Friedli, Niklas Linde, David Ginsbourger, Arnaud Doucet
    http://arxiv.org/abs/2110.05210v1

    • [physics.pop-ph]Modeling of Pan Evaporation Based on the Development of Machine Learning Methods
    Mustafa Al-Mukhtar
    http://arxiv.org/abs/2110.04749v1

    • [physics.soc-ph]Sideward contact tracing and the control of epidemics in large gatherings
    Marco Mancastroppa, Andrea Guizzo, Claudio Castellano, Alessandro Vezzani, Raffaella Burioni
    http://arxiv.org/abs/2110.04742v1

    • [q-bio.BM]Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design
    Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi Jaakkola
    http://arxiv.org/abs/2110.04624v1

    • [q-bio.GN]Multi-modal Self-supervised Pre-training for Regulatory Genome Across Cell Types
    Shentong Mo, Xi Fu, Chenyang Hong, Yizhen Chen, Yuxuan Zheng, Xiangru Tang, Zhiqiang Shen, Eric P Xing, Yanyan Lan
    http://arxiv.org/abs/2110.05231v1

    • [q-bio.NC]Are Words the Quanta of Human Language? Extending the Domain of Quantum Cognition
    Diederik Aerts, Lester Beltran
    http://arxiv.org/abs/2110.04913v1

    • [q-bio.QM]COVID-Datathon: Biomarker identification for COVID-19 severity based on BALF scRNA-seq data
    Seyednami Niyakan, Xiaoning Qian
    http://arxiv.org/abs/2110.04986v1

    • [q-fin.TR]How Robust are Limit Order Book Representations under Data Perturbation?
    Yufei Wu, Mahmoud Mahfouz, Daniele Magazzeni, Manuela Veloso
    http://arxiv.org/abs/2110.04752v1

    • [q-fin.TR]Reinforcement Learning for Systematic FX Trading
    Gabriel Borrageiro, Nick Firoozye, Paolo Barucca
    http://arxiv.org/abs/2110.04745v1

    • [quant-ph]Application of quantum computing to a linear non-Gaussian acyclic model for novel medical knowledge discovery
    Hideaki Kawaguchi
    http://arxiv.org/abs/2110.04485v1

    • [quant-ph]Hard instance learning for quantum adiabatic prime factorization
    Jian Lin, Zhengfeng Zhang, Junping Zhang, Xiaopeng Li
    http://arxiv.org/abs/2110.04782v1

    • [quant-ph]Quantum pixel representations and compression for 今日学术视野(2021.10.13) - 图12-dimensional images
    Mercy G. Amankwah, Daan Camps, E. Wes Bethel, Roel Van Beeumen, Talita Perciano
    http://arxiv.org/abs/2110.04405v1

    • [stat.AP]Call and Put Option Pricing with Discrete Linear Investment Strategy
    Niloofar Ghorbani, Andrzej Korzeniowski
    http://arxiv.org/abs/2110.04676v1

    • [stat.AP]Estimating IRI based on pavement distress type, density, and severity: Insights from machine learning techniques
    Yu Qiao, Sikai Chen, Majed Alinizzi, Miltos Alamaniotis, Samuel Labi
    http://arxiv.org/abs/2110.05413v1

    • [stat.AP]Phase-type distributions for claim severity regression modeling
    Martin Bladt
    http://arxiv.org/abs/2110.05207v1

    • [stat.ME]A computational approach to the Kiefer-Weiss problem for sampling from a Bernoulli population
    Andrey Novikov, Andrei Novikov, Fahil Farkhshatov
    http://arxiv.org/abs/2110.04802v1

    • [stat.ME]A parametric quantile beta regression for modeling case fatality rates of COVID-19
    Marcelo Bourguignon, Diego I. Gallardo, Helton Saulo
    http://arxiv.org/abs/2110.04428v1

    • [stat.ME]Allocation of COVID-19 Testing Budget on a Commute Network of Counties
    Yaxuan Huang, Zheng Tracy Ke, Jiashun Jin
    http://arxiv.org/abs/2110.04381v1

    • [stat.ME]Birth-and-death Processes in Python: The BirDePy Package
    Sophie Hautphenne, Brendan Patch
    http://arxiv.org/abs/2110.05067v1

    • [stat.ME]Clustering of Diverse Multiplex Networks
    Marianna Pensky, Yaxuan Wang
    http://arxiv.org/abs/2110.05308v1

    • [stat.ME]Co-clustering of Spatially Resolved Transcriptomic Data
    Andrea Sottosanti, Davide Risso
    http://arxiv.org/abs/2110.04872v1

    • [stat.ME]De-biased Lasso for Generalized Linear Models with A Diverging Number of Covariates
    Lu Xia, Bin Nan, Yi Li
    http://arxiv.org/abs/2110.04433v1

    • [stat.ME]Graphical Assistant Grouped Network Autoregression Model: a Bayesian Nonparametric Recourse
    Yimeng Ren, Xuening Zhu, Guanyu Hu
    http://arxiv.org/abs/2110.04991v1

    • [stat.ME]Group-matching algorithms for subjects and items
    Géza Kiss, Kyle Gorman, Jan P. H. van Santen
    http://arxiv.org/abs/2110.04432v1

    • [stat.ME]High-dimensional Inference for Dynamic Treatment Effects
    Jelena Bradic, Weijie Ji, Yuqian Zhang
    http://arxiv.org/abs/2110.04924v1

    • [stat.ME]Mixture representations for likelihood ratio ordered distributions
    Michael Jauch, Andrés F. Barrientos, Víctor Peña, David S. Matteson
    http://arxiv.org/abs/2110.04852v1

    • [stat.ME]Multiway sparse distance weighted discrimination
    Bin Guo, Lynn E. Eberly, Pierre-Gilles Henry, Christophe Lenglet, Eric F. Lock
    http://arxiv.org/abs/2110.05377v1

    • [stat.ME]Nonparametric kernel estimation of Weibull-tail coefficient in presence of the right random censoring
    Justin Ushize Rutikange, Aliou Diop
    http://arxiv.org/abs/2110.04772v1

    • [stat.ME]Ordinary Differential Equation Models and their Computation Methods
    Jaeyong Lee
    http://arxiv.org/abs/2110.04726v1

    • [stat.ME]Reversible Genetically Modified ModeJumping MCMC
    Aliaksandr Hubin, Florian Frommlet, Geir Storvik
    http://arxiv.org/abs/2110.05316v1

    • [stat.ME]Scaled torus principal component analysis
    Pavlos Zoubouloglou, Eduardo García-Portugués, J. S. Marron
    http://arxiv.org/abs/2110.04758v1

    • [stat.ME]Simultaneous Cluster Structure Learning and Estimation of Heterogeneous Graphs for Matrix-variate fMRI Data
    Dong Liu, Changwei Zhao, Yong He, Lei Liu, Ying Guo, Xinsheng Zhang
    http://arxiv.org/abs/2110.04516v1

    • [stat.ME]Truncated Rank-Based Tests for Two-Part Models with Excessive Zeros and Applications to Microbiome Data
    Wanjie Wang, Zhang Eric Chen, Hongzhe Li
    http://arxiv.org/abs/2110.05368v1

    • [stat.ME]Wavelet Estimation for Factor Models with Time-Varying Loadings
    Duván Humberto Cataño, C. Vladimir Rodríguez-Caballero, Daniel Peña, Chang Chiann
    http://arxiv.org/abs/2110.04416v1

    • [stat.ML]Adaptive joint distribution learning
    Damir Filipovic, Michael Multerer, Paul Schneider
    http://arxiv.org/abs/2110.04829v1

    • [stat.ML]Deep Unsupervised Feature Selection by Discarding Nuisance and Correlated Features
    Uri Shaham, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger
    http://arxiv.org/abs/2110.05306v1

    • [stat.ML]Designing off-sample performance metrics
    Matthew J. Holland
    http://arxiv.org/abs/2110.04996v1

    • [stat.ML]Learning Temporally Causal Latent Processes from General Temporal Data
    Weiran Yao, Yuewen Sun, Alex Ho, Changyin Sun, Kun Zhang
    http://arxiv.org/abs/2110.05428v1

    • [stat.ML]Nonparametric Functional Analysis of Generalized Linear Models Under Nonlinear Constraints
    K. P. Chowdhury
    http://arxiv.org/abs/2110.04998v1

    • [stat.ML]Quadratic Multiform Separation: A New Classification Model in Machine Learning
    Ko-Hui Michael Fan, Chih-Chung Chang, Kuang-Hsiao-Yin Kongguoluo
    http://arxiv.org/abs/2110.04925v1

    • [stat.ML]Robust and Scalable SDE Learning: A Functional Perspective
    Scott Cameron, Tyron Cameron, Arnu Pretorius, Stephen Roberts
    http://arxiv.org/abs/2110.05167v1

    • [stat.ML]When to Call Your Neighbor? Strategic Communication in Cooperative Stochastic Bandits
    Udari Madhushani, Naomi Leonard
    http://arxiv.org/abs/2110.04396v1

    • [stat.ML]β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap
    Pengzhou Wu, Kenji Fukumizu
    http://arxiv.org/abs/2110.05225v1