cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DB - 数据库
    cs.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    cs.DS - 数据结构与算法
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.NE - 神经与进化计算
    cs.NI - 网络和互联网体系结构
    cs.RO - 机器人学
    cs.SD - 声音处理
    cs.SI - 社交网络与信息网络
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    math.CO - 组合数学
    math.DS - 动力系统
    math.ST - 统计理论
    physics.flu-dyn - 流体动力学
    physics.soc-ph - 物理学与社会
    q-bio.NC - 神经元与认知
    q-bio.PE - 人口与发展
    q-fin.ST - 统计金融学
    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]Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
    • [cs.AI]COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression
    • [cs.AI]Hybrid Super Intelligence and Polymetric Analysis
    • [cs.AI]Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines
    • [cs.AI]Neural Class Expression Synthesis
    • [cs.AI]Reinforcement Learning on Human Decision Models for Uniquely Collaborative AI Teammates
    • [cs.AI]Software Engineering for Responsible AI: An Empirical Study and Operationalised Patterns
    • [cs.AI]Sustainable Artificial Intelligence through Continual Learning
    • [cs.AI]Uncertainty-Aware Multiple Instance Learning fromLarge-Scale Long Time Series Data
    • [cs.CL]Achieving Human Parity on Visual Question Answering
    • [cs.CL]Automatic Expansion and Retargeting of Arabic Offensive Language Training
    • [cs.CL]DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing
    • [cs.CL]Detecting Cross-Language Plagiarism using Open Knowledge Graphs
    • [cs.CL]Dynamic-TinyBERT: Boost TinyBERT’s Inference Efficiency by Dynamic Sequence Length
    • [cs.CL]Facilitating reflection in teletandem through automatically generated conversation metrics and playback video
    • [cs.CL]Findings of the Sentiment Analysis of Dravidian Languages in Code-Mixed Text
    • [cs.CL]How Emotionally Stable is ALBERT? Testing Robustness with Stochastic Weight Averaging on a Sentiment Analysis Task
    • [cs.CL]How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN
    • [cs.CL]MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System
    • [cs.CL]Minimum Bayes Risk Decoding with Neural Metrics of Translation Quality
    • [cs.CL]Pegasus@Dravidian-CodeMix-HASOC2021: Analyzing Social Media Content for Detection of Offensive Text
    • [cs.CL]RoBERTuito: a pre-trained language model for social media text in Spanish
    • [cs.CL]SDCUP: Schema Dependency-Enhanced Curriculum Pre-Training for Table Semantic Parsing
    • [cs.CL]Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model
    • [cs.CL]SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization
    • [cs.CL]Supporting Undotted Arabic with Pre-trained Language Models
    • [cs.CL]To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLP
    • [cs.CL]Towards Interpretable and Reliable Reading Comprehension: A Pipeline Model with Unanswerability Prediction
    • [cs.CR]A Secure Experimentation Sandbox for the design and execution of trusted and secure analytics in the aviation domain
    • [cs.CR]A big data intelligence marketplace and secure analytics experimentation platform for the aviation industry
    • [cs.CR]Attacking Deep Learning AI Hardware with Universal Adversarial Perturbation
    • [cs.CV]3D Lip Event Detection via Interframe Motion Divergence at Multiple Temporal Resolutions
    • [cs.CV]Adaptive Shrink-Mask for Text Detection
    • [cs.CV]Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy
    • [cs.CV]Blind VQA on 360° Video via Progressively Learning from Pixels, Frames and Video
    • [cs.CV]Boosting Supervised Learning Performance with Co-training
    • [cs.CV]ClipCap: CLIP Prefix for Image Captioning
    • [cs.CV]Deep neural networks-based denoising models for CT imaging and their efficacy
    • [cs.CV]DeepCurrents: Learning Implicit Representations of Shapes with Boundaries
    • [cs.CV]Developing a Machine Learning Algorithm-Based Classification Models for the Detection of High-Energy Gamma Particles
    • [cs.CV]Dynamically pruning segformer for efficient semantic segmentation
    • [cs.CV]Edge-preserving Domain Adaptation for semantic segmentation of Medical Images
    • [cs.CV]Efficient deep learning models for land cover image classification
    • [cs.CV]Evaluating Transformers for Lightweight Action Recognition
    • [cs.CV]Fine-Grained Vehicle Classification in Urban Traffic Scenes using Deep Learning
    • [cs.CV]IMFNet: Interpretable Multimodal Fusion for Point Cloud Registration
    • [cs.CV]Interactive segmentation using U-Net with weight map and dynamic user interactions
    • [cs.CV]Learning Modified Indicator Functions for Surface Reconstruction
    • [cs.CV]LiDAR Cluster First and Camera Inference Later: A New Perspective Towards Autonomous Driving
    • [cs.CV]MPF6D: Masked Pyramid Fusion 6D Pose Estimation
    • [cs.CV]One-Shot Generative Domain Adaptation
    • [cs.CV]Perceiving and Modeling Density is All You Need for Image Dehazing
    • [cs.CV]Postdisaster image-based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks
    • [cs.CV]PyTorchVideo: A Deep Learning Library for Video Understanding
    • [cs.CV]RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation
    • [cs.CV]Reference-based Magnetic Resonance Image Reconstruction Using Texture Transforme
    • [cs.CV]Restormer: Efficient Transformer for High-Resolution Image Restoration
    • [cs.CV]Rethinking Drone-Based Search and Rescue with Aerial Person Detection
    • [cs.CV]Robust Person Re-identification with Multi-Modal Joint Defence
    • [cs.CV]SUB-Depth: Self-distillation and Uncertainty Boosting Self-supervised Monocular Depth Estimation
    • [cs.CV]See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation
    • [cs.CV]Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection
    • [cs.CV]SimMIM: A Simple Framework for Masked Image Modeling
    • [cs.CV]Simple but Effective: CLIP Embeddings for Embodied AI
    • [cs.CV]SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking
    • [cs.CV]Swin Transformer V2: Scaling Up Capacity and Resolution
    • [cs.CV]Temporally Consistent Online Depth Estimation in Dynamic Scenes
    • [cs.CV]The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video
    • [cs.CV]Towards Open Vocabulary Object Detection without Human-provided Bounding Boxes
    • [cs.CV]TransMix: Attend to Mix for Vision Transformers
    • [cs.CV]Wiggling Weights to Improve the Robustness of Classifiers
    • [cs.CY]A Survey on Metaverse: the State-of-the-art, Technologies, Applications, and Challenges
    • [cs.DB]GAP Enhancing Semantic Interoperability of Genomic Datasets and Provenance Through Nanopublications
    • [cs.DB]Improving Prediction-Based Lossy Compression Dramatically Via Ratio-Quality Modeling
    • [cs.DC]Case study of SARS-CoV-2 transmission risk assessment in indoor environments using cloud computing resources
    • [cs.DC]Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems
    • [cs.DC]QGTC: Accelerating Quantized GNN via GPU Tensor Core
    • [cs.DL]A Bibliometric Analysis of the BPM Conference Using Computational Data Analytics
    • [cs.DS]Stream Sampling with Immediate Decision
    • [cs.HC]A co-design approach for a rehabilitation robot coach for physical rehabilitation based on the error classification of motion errors
    • [cs.IR]The Power of Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval
    • [cs.IT]Analysis and Design of Distributed MIMO Networks with a Wireless Fronthaul
    • [cs.IT]On Generalized Galois Cyclic Orbit Flag Codes
    • [cs.LG]A Novel Optimized Asynchronous Federated Learning Framework
    • [cs.LG]A Survey of Generalisation in Deep Reinforcement Learning
    • [cs.LG]Assessing Social Determinants-Related Performance Bias of Machine Learning Models: A case of Hyperchloremia Prediction in ICU Population
    • [cs.LG]CCSL: A Causal Structure Learning Method from Multiple Unknown Environments
    • [cs.LG]CLMB: deep contrastive learning for robust metagenomic binning
    • [cs.LG]Contrastive Multiview Coding for Enzyme-Substrate Interaction Prediction
    • [cs.LG]Covered Information Disentanglement: Model Transparency via Unbiased Permutation Importance
    • [cs.LG]DIVA: Dataset Derivative of a Learning Task
    • [cs.LG]Data-driven discovery of Bäcklund transforms and soliton evolution equations via deep neural network learning schemes
    • [cs.LG]DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior
    • [cs.LG]Docking-based Virtual Screening with Multi-Task Learning
    • [cs.LG]Enhanced Membership Inference Attacks against Machine Learning Models
    • [cs.LG]Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings
    • [cs.LG]FLSys: Toward an Open Ecosystem for FederatedLearning Mobile Apps
    • [cs.LG]Features selection in NBA outcome prediction through Deep Learning
    • [cs.LG]GAETS: A Graph Autoencoder Time Series Approach Towards Battery Parameter Estimation
    • [cs.LG]Improving Transferability of Representations via Augmentation-Aware Self-Supervision
    • [cs.LG]LAnoBERT : System Log Anomaly Detection based on BERT Masked Language Model
    • [cs.LG]Low Precision Decentralized Distributed Training with Heterogeneous Data
    • [cs.LG]Merging Models with Fisher-Weighted Averaging
    • [cs.LG]On the Effectiveness of Sparsification for Detecting the Deep Unknowns
    • [cs.LG]Optimal Simple Regret in Bayesian Best Arm Identification
    • [cs.LG]Personalized Federated Learning through Local Memorization
    • [cs.LG]Route Optimization via Environment-Aware Deep Network and Reinforcement Learning
    • [cs.LG]Self-Attending Task Generative Adversarial Network for Realistic Satellite Image Creation
    • [cs.LG]Self-Learning Tuning for Post-Silicon Validation
    • [cs.LG]Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning
    • [cs.LG]The People’s Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage
    • [cs.LG]The Prominence of Artificial Intelligence in COVID-19
    • [cs.LG]Training Neural Networks with Fixed Sparse Masks
    • [cs.LG]You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
    • [cs.NE]Continuous learning of spiking networks trained with local rules
    • [cs.NE]Evolutionary Algorithm for Graph Coloring Problem
    • [cs.NE]L4-Norm Weight Adjustments for Converted Spiking Neural Networks
    • [cs.NI]An Experimental Study of Latency for IEEE 802.11be Multi-link Operation
    • [cs.RO]A Low-Cost, Easy-to-Manufacture, Flexible, Multi-Taxel Tactile Sensor and its Application to In-Hand Object Recognition
    • [cs.RO]Assisted Robust Reward Design
    • [cs.RO]Backswimmer Inspired Miniature Robot with Buoyancy Auto-Regulation through Controlled Nucleation and Release of Microbubbles
    • [cs.RO]Complex Terrain Navigation via Model Error Prediction
    • [cs.RO]Hybrid Feedback for Autonomous Navigation in Environments with Arbitrary Convex Obstacles
    • [cs.RO]Lidar with Velocity: Motion Distortion Correction of Point Clouds from Oscillating Scanning Lidars
    • [cs.RO]Monitoring Over the Long Term: Intermittent Deployment and Sensing Strategies for Multi-Robot Teams
    • [cs.RO]On the Effectiveness of Iterative Learning Control
    • [cs.RO]Punyo-1: Soft tactile-sensing upper-body robot for large object manipulation and physical human interaction
    • [cs.RO]Submodular Optimization for Coupled Task Allocation and Intermittent Deployment Problems
    • [cs.RO]Technology Report:Multi-Mobile Robot Localization and Navigation based on Visible Light Positioning
    • [cs.RO]The Effects of Learning in Morphologically Evolving Robot Systems
    • [cs.RO]Unsupervised Online Learning for Robotic Interestingness with Visual Memory
    • [cs.RO]Visual Navigation Using Sparse Optical Flow and Time-to-Transit
    • [cs.SD]Towards Intelligibility-Oriented Audio-Visual Speech Enhancement
    • [cs.SI]Transformation of Node to Knowledge Graph Embeddings for Faster Link Prediction in Social Networks
    • [eess.AS]BLOOM-Net: Blockwise Optimization for Masking Networks Toward Scalable and Efficient Speech Enhancement
    • [eess.IV]A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration
    • [eess.IV]Large-scale Building Height Retrieval from Single SAR Imagery based on Bounding Box Regression Networks
    • [eess.IV]Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction
    • [eess.SP]A Modular 1D-CNN Architecture for Real-time Digital Pre-distortion
    • [eess.SP]CSI Clustering with Variational Autoencoding
    • [eess.SP]LiDAR-Aided Mobile Blockage Prediction in Real-World Millimeter Wave Systems
    • [eess.SP]Radar Aided 6G Beam Prediction: Deep Learning Algorithms and Real-World Demonstration
    • [math.CO]On the Existence of Coproducts in Categories of q-Matroids
    • [math.DS]Information-theoretic formulation of dynamical systems: causality, modeling, and control
    • [math.ST]Bounds in 今日学术视野(2021.11.20) - 图1 Wasserstein distance on the normal approximation of general M-estimators
    • [math.ST]Ergodic Estimators of double exponential Ornstein-Ulenbeck process
    • [math.ST]Unbiased Risk Estimation in the Normal Means Problem via Coupled Bootstrap Techniques
    • [physics.flu-dyn]Learning Free-Surface Flow with Physics-Informed Neural Networks
    • [physics.soc-ph]Adversarial attacks on voter model dynamics in complex networks
    • [q-bio.NC]Locally Learned Synaptic Dropout for Complete Bayesian Inference
    • [q-bio.PE]A Novel Compartmental Approach to Modeling COVID-19 Disease Dynamics and Analyzing the Effect of Common Preventative Measures
    • [q-fin.ST]Effect of the U.S.—China Trade War on Stock Markets: A Financial Contagion Perspective
    • [quant-ph]Near-Optimal Quantum Algorithms for Multivariate Mean Estimation
    • [stat.AP]Estimating the concentration parameter of a von Mises distribution: a systematic simulation benchmark
    • [stat.AP]Neural Network Kalman filtering for 3D object tracking from linear array ultrasound data
    • [stat.AP]Number of New Top 2% Researchers from China and USA Over Time
    • [stat.ME]A sample size heuristic for network scale-up studies
    • [stat.ME]Bayes factors for accelerated life testing models
    • [stat.ME]Extending the coefficient of variation for measuring heterogeneity following a meta-regression
    • [stat.ME]Implicit copula variational inference
    • [stat.ME]Nonparametric Scanning For Nonrandom Missing Data With Continuous Instrumental Variables
    • [stat.ME]Return-to-baseline multiple imputation for missing values in clinical trials
    • [stat.ML]C-OPH: Improving the Accuracy of One Permutation Hashing (OPH) with Circulant Permutations
    • [stat.ML]Causal Forecasting:Generalization Bounds for Autoregressive Models
    • [stat.ML]From Optimality to Robustness: Dirichlet Sampling Strategies in Stochastic Bandits
    • [stat.ML]MCCE: Monte Carlo sampling of realistic counterfactual explanations
    • [stat.ML]Sampling To Improve Predictions For Underrepresented Observations In Imbalanced Data

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

    • [cs.AI]Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
    Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel Rubin, Adrian Weller, Joan Lasenby, Chuangsheng Zheng, Jianming Wang, Zhen Li, Carola-Bibiane Schönlieb, Tian Xia
    http://arxiv.org/abs/2111.09461v1

    • [cs.AI]COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression
    Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao
    http://arxiv.org/abs/2111.09562v1

    • [cs.AI]Hybrid Super Intelligence and Polymetric Analysis
    Vladislav Dorofeev, Petro Trokhimchuk
    http://arxiv.org/abs/2111.09762v1

    • [cs.AI]Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines
    Xuejing Zheng, Chao Yu, Chen Chen, Jianye Hao, Hankz Hankui Zhuo
    http://arxiv.org/abs/2111.09475v1

    • [cs.AI]Neural Class Expression Synthesis
    N’Dah Jean Kouagou, Stefan Heindorf, Caglar Demir, Axel-Cyrille Ngonga Ngomo
    http://arxiv.org/abs/2111.08486v2

    • [cs.AI]Reinforcement Learning on Human Decision Models for Uniquely Collaborative AI Teammates
    Nicholas Kantack
    http://arxiv.org/abs/2111.09800v1

    • [cs.AI]Software Engineering for Responsible AI: An Empirical Study and Operationalised Patterns
    Qinghua Lu, Liming Zhu, Xiwei Xu, Jon Whittle, David Douglas, Conrad Sanderson
    http://arxiv.org/abs/2111.09478v1

    • [cs.AI]Sustainable Artificial Intelligence through Continual Learning
    Andrea Cossu, Marta Ziosi, Vincenzo Lomonaco
    http://arxiv.org/abs/2111.09437v1

    • [cs.AI]Uncertainty-Aware Multiple Instance Learning fromLarge-Scale Long Time Series Data
    Yuansheng Zhu, Weishi Shi, Deep Shankar Pandey, Yang Liu, Xiaofan Que, Daniel E. Krutz, Qi Yu
    http://arxiv.org/abs/2111.08625v2

    • [cs.CL]Achieving Human Parity on Visual Question Answering
    Ming Yan, Haiyang Xu, Chenliang Li, Junfeng Tian, Bin Bi, Wei Wang, Weihua Chen, Xianzhe Xu, Fan Wang, Zheng Cao, Ji Zhang, Songfang Huang, Fei Huang, Luo Si, Rong Jin
    http://arxiv.org/abs/2111.08896v2

    • [cs.CL]Automatic Expansion and Retargeting of Arabic Offensive Language Training
    Hamdy Mubarak, Ahmed Abdelali, Kareem Darwish, Younes Samih
    http://arxiv.org/abs/2111.09574v1

    • [cs.CL]DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing
    Pengcheng He, Jianfeng Gao, Weizhu Chen
    http://arxiv.org/abs/2111.09543v1

    • [cs.CL]Detecting Cross-Language Plagiarism using Open Knowledge Graphs
    Johannes Stegmüller, Fabian Bauer-Marquart, Norman Meuschke, Terry Ruas, Moritz Schubotz, Bela Gipp
    http://arxiv.org/abs/2111.09749v1

    • [cs.CL]Dynamic-TinyBERT: Boost TinyBERT’s Inference Efficiency by Dynamic Sequence Length
    Shira Guskin, Moshe Wasserblat, Ke Ding, Gyuwan Kim
    http://arxiv.org/abs/2111.09645v1

    • [cs.CL]Facilitating reflection in teletandem through automatically generated conversation metrics and playback video
    Aparajita Dey-Plissonneau, Hyowon Lee, Michael Scriney, Alan F. Smeaton, Vincent Pradier, Hamza Riaz
    http://arxiv.org/abs/2111.08788v2

    • [cs.CL]Findings of the Sentiment Analysis of Dravidian Languages in Code-Mixed Text
    Bharathi Raja Chakravarthi, Ruba Priyadharshini, Sajeetha Thavareesan, Dhivya Chinnappa, Durairaj Thenmozhi, Elizabeth Sherly, John P. McCrae, Adeep Hande, Rahul Ponnusamy, Shubhanker Banerjee, Charangan Vasantharajan
    http://arxiv.org/abs/2111.09811v1

    • [cs.CL]How Emotionally Stable is ALBERT? Testing Robustness with Stochastic Weight Averaging on a Sentiment Analysis Task
    Urja Khurana, Eric Nalisnick, Antske Fokkens
    http://arxiv.org/abs/2111.09612v1

    • [cs.CL]How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN
    R. Thomas McCoy, Paul Smolensky, Tal Linzen, Jianfeng Gao, Asli Celikyilmaz
    http://arxiv.org/abs/2111.09509v1

    • [cs.CL]MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System
    Rhys Compton, Ilya Valmianski, Li Deng, Costa Huang, Namit Katariya, Xavier Amatriain, Anitha Kannan
    http://arxiv.org/abs/2111.09381v1

    • [cs.CL]Minimum Bayes Risk Decoding with Neural Metrics of Translation Quality
    Markus Freitag, David Grangier, Qijun Tan, Bowen Liang
    http://arxiv.org/abs/2111.09388v1

    • [cs.CL]Pegasus@Dravidian-CodeMix-HASOC2021: Analyzing Social Media Content for Detection of Offensive Text
    Pawan Kalyan Jada, Konthala Yasaswini, Karthik Puranik, Anbukkarasi Sampath, Sathiyaraj Thangasamy, Kingston Pal Thamburaj
    http://arxiv.org/abs/2111.09836v1

    • [cs.CL]RoBERTuito: a pre-trained language model for social media text in Spanish
    Juan Manuel Pérez, Damián A. Furman, Laura Alonso Alemany, Franco Luque
    http://arxiv.org/abs/2111.09453v1

    • [cs.CL]SDCUP: Schema Dependency-Enhanced Curriculum Pre-Training for Table Semantic Parsing
    Bowen Qin, Lihan Wang, Binyuan Hui, Ruiying Geng, Zheng Cao, Min Yang, Jian Sun, Yongbin Li
    http://arxiv.org/abs/2111.09486v1

    • [cs.CL]Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model
    Hongjiang Jing, Zuchao Li, Hai Zhao, Shu Jiang
    http://arxiv.org/abs/2111.09634v1

    • [cs.CL]SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization
    Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst
    http://arxiv.org/abs/2111.09525v1

    • [cs.CL]Supporting Undotted Arabic with Pre-trained Language Models
    Aviad Rom, Kfir Bar
    http://arxiv.org/abs/2111.09791v1

    • [cs.CL]To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLP
    Gözde Gül Şahin
    http://arxiv.org/abs/2111.09618v1

    • [cs.CL]Towards Interpretable and Reliable Reading Comprehension: A Pipeline Model with Unanswerability Prediction
    Kosuke Nishida, Kyosuke Nishida, Itsumi Saito, Sen Yoshida
    http://arxiv.org/abs/2111.09029v2

    • [cs.CR]A Secure Experimentation Sandbox for the design and execution of trusted and secure analytics in the aviation domain
    Dimitrios Miltiadou, Stamatis Pitsios, Dimitrios Spyropoulos, Dimitrios Alexandrou, Fenareti Lampathaki, Domenico Messina, Konstantinos Perakis
    http://arxiv.org/abs/2111.09863v1

    • [cs.CR]A big data intelligence marketplace and secure analytics experimentation platform for the aviation industry
    Dimitrios Miltiadou, Stamatis Pitsios, Dimitrios Spyropoulos, Dimitrios Alexandrou, Fenareti Lampathaki, Domenico Messina, Konstantinos Perakis
    http://arxiv.org/abs/2111.09872v1

    • [cs.CR]Attacking Deep Learning AI Hardware with Universal Adversarial Perturbation
    Mehdi Sadi, B. M. S. Bahar Talukder, Kaniz Mishty, Md Tauhidur Rahman
    http://arxiv.org/abs/2111.09488v1

    • [cs.CV]3D Lip Event Detection via Interframe Motion Divergence at Multiple Temporal Resolutions
    Jie Zhang, Robert B. Fisher
    http://arxiv.org/abs/2111.09485v1

    • [cs.CV]Adaptive Shrink-Mask for Text Detection
    Chuang Yang, Mulin Chen, Yuan Yuan, Qi Wang, Xuelong Li
    http://arxiv.org/abs/2111.09560v1

    • [cs.CV]Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy
    Thibault Castells, Seul-Ki Yeom
    http://arxiv.org/abs/2111.09635v1

    • [cs.CV]Blind VQA on 360° Video via Progressively Learning from Pixels, Frames and Video
    Li Yang, Mai Xu, Shengxi Li, Yichen Guo, Zulin Wang
    http://arxiv.org/abs/2111.09503v1

    • [cs.CV]Boosting Supervised Learning Performance with Co-training
    Xinnan Du, William Zhang, Jose M. Alvarez
    http://arxiv.org/abs/2111.09797v1

    • [cs.CV]ClipCap: CLIP Prefix for Image Captioning
    Ron Mokady, Amir Hertz, Amit H. Bermano
    http://arxiv.org/abs/2111.09734v1

    • [cs.CV]Deep neural networks-based denoising models for CT imaging and their efficacy
    Prabhat KC, Rongping Zeng, M. Mehdi Farhangi, Kyle J. Myers
    http://arxiv.org/abs/2111.09539v1

    • [cs.CV]DeepCurrents: Learning Implicit Representations of Shapes with Boundaries
    David Palmer, Dmitriy Smirnov, Stephanie Wang, Albert Chern, Justin Solomon
    http://arxiv.org/abs/2111.09383v1

    • [cs.CV]Developing a Machine Learning Algorithm-Based Classification Models for the Detection of High-Energy Gamma Particles
    Emmanuel Dadzie, Kelvin Kwakye
    http://arxiv.org/abs/2111.09496v1

    • [cs.CV]Dynamically pruning segformer for efficient semantic segmentation
    Haoli Bai, Hongda Mao, Dinesh Nair
    http://arxiv.org/abs/2111.09499v1

    • [cs.CV]Edge-preserving Domain Adaptation for semantic segmentation of Medical Images
    Thong Vo, Naimul Khan
    http://arxiv.org/abs/2111.09847v1

    • [cs.CV]Efficient deep learning models for land cover image classification
    Ioannis Papoutsis, Nikolaos-Ioannis Bountos, Angelos Zavras, Dimitrios Michail, Christos Tryfonopoulos
    http://arxiv.org/abs/2111.09451v1

    • [cs.CV]Evaluating Transformers for Lightweight Action Recognition
    Raivo Koot, Markus Hennerbichler, Haiping Lu
    http://arxiv.org/abs/2111.09641v1

    • [cs.CV]Fine-Grained Vehicle Classification in Urban Traffic Scenes using Deep Learning
    Syeda Aneeba Najeeb, Rana Hammad Raza, Adeel Yusuf, Zamra Sultan
    http://arxiv.org/abs/2111.09403v1

    • [cs.CV]IMFNet: Interpretable Multimodal Fusion for Point Cloud Registration
    Xiaoshui Huang, Wentao Qu, Yifan Zuo, Yuming Fang, Xiaowei Zhao
    http://arxiv.org/abs/2111.09624v1

    • [cs.CV]Interactive segmentation using U-Net with weight map and dynamic user interactions
    Ragavie Pirabaharan, Naimul Khan
    http://arxiv.org/abs/2111.09740v1

    • [cs.CV]Learning Modified Indicator Functions for Surface Reconstruction
    Dong Xiao, Siyou Lin, Zuoqiang Shi, Bin Wang
    http://arxiv.org/abs/2111.09526v1

    • [cs.CV]LiDAR Cluster First and Camera Inference Later: A New Perspective Towards Autonomous Driving
    Jiyang Chen, Simon Yu, Rohan Tabish, Ayoosh Bansal, Shengzhong Liu, Tarek Abdelzaher, Lui Sha
    http://arxiv.org/abs/2111.09799v1

    • [cs.CV]MPF6D: Masked Pyramid Fusion 6D Pose Estimation
    Nuno Pereira, Luís A. Alexandre
    http://arxiv.org/abs/2111.09378v1

    • [cs.CV]One-Shot Generative Domain Adaptation
    Ceyuan Yang, Yujun Shen, Zhiyi Zhang, Yinghao Xu, Jiapeng Zhu, Zhirong Wu, Bolei Zhou
    http://arxiv.org/abs/2111.09876v1

    • [cs.CV]Perceiving and Modeling Density is All You Need for Image Dehazing
    Tian Ye, Mingchao Jiang, Yunchen Zhang, Liang Chen, Erkang Chen, Pen Chen, Zhiyong Lu
    http://arxiv.org/abs/2111.09733v1

    • [cs.CV]Postdisaster image-based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks
    Xiao Pan, T. Y. Yang
    http://arxiv.org/abs/2111.09862v1

    • [cs.CV]PyTorchVideo: A Deep Learning Library for Video Understanding
    Haoqi Fan, Tullie Murrell, Heng Wang, Kalyan Vasudev Alwala, Yanghao Li, Yilei Li, Bo Xiong, Nikhila Ravi, Meng Li, Haichuan Yang, Jitendra Malik, Ross Girshick, Matt Feiszli, Aaron Adcock, Wan-Yen Lo, Christoph Feichtenhofer
    http://arxiv.org/abs/2111.09887v1

    • [cs.CV]RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation
    Yantao Lu, Xuetao Hao, Shiqi Sun, Weiheng Chai, Muchenxuan Tong, Senem Velipasalar
    http://arxiv.org/abs/2111.09515v1

    • [cs.CV]Reference-based Magnetic Resonance Image Reconstruction Using Texture Transforme
    Pengfei Guo, Vishal M. Patel
    http://arxiv.org/abs/2111.09492v1

    • [cs.CV]Restormer: Efficient Transformer for High-Resolution Image Restoration
    Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang
    http://arxiv.org/abs/2111.09881v1

    • [cs.CV]Rethinking Drone-Based Search and Rescue with Aerial Person Detection
    Pasi Pyrrö, Hassan Naseri, Alexander Jung
    http://arxiv.org/abs/2111.09406v1

    • [cs.CV]Robust Person Re-identification with Multi-Modal Joint Defence
    Yunpeng Gong, Lifei Chen
    http://arxiv.org/abs/2111.09571v1

    • [cs.CV]SUB-Depth: Self-distillation and Uncertainty Boosting Self-supervised Monocular Depth Estimation
    Hang Zhou, Sarah Taylor, David Greenwood
    http://arxiv.org/abs/2111.09692v1

    • [cs.CV]See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation
    Darren Tsai, Julie Stephany Berrio, Mao Shan, Stewart Worrall, Eduardo Nebot
    http://arxiv.org/abs/2111.09450v1

    • [cs.CV]Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection
    Nicolae-Catalin Ristea, Neelu Madan, Radu Tudor Ionescu, Kamal Nasrollahi, Fahad Shahbaz Khan, Thomas B. Moeslund, Mubarak Shah
    http://arxiv.org/abs/2111.09099v2

    • [cs.CV]SimMIM: A Simple Framework for Masked Image Modeling
    Zhenda Xie, Zheng Zhang, Yue Cao, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai, Han Hu
    http://arxiv.org/abs/2111.09886v1

    • [cs.CV]Simple but Effective: CLIP Embeddings for Embodied AI
    Apoorv Khandelwal, Luca Weihs, Roozbeh Mottaghi, Aniruddha Kembhavi
    http://arxiv.org/abs/2111.09888v1

    • [cs.CV]SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking
    Ziqi Pang, Zhichao Li, Naiyan Wang
    http://arxiv.org/abs/2111.09621v1

    • [cs.CV]Swin Transformer V2: Scaling Up Capacity and Resolution
    Ze Liu, Han Hu, Yutong Lin, Zhuliang Yao, Zhenda Xie, Yixuan Wei, Jia Ning, Yue Cao, Zheng Zhang, Li Dong, Furu Wei, Baining Guo
    http://arxiv.org/abs/2111.09883v1

    • [cs.CV]Temporally Consistent Online Depth Estimation in Dynamic Scenes
    Zhaoshuo Li, Wei Ye, Dilin Wang, Francis X. Creighton, Russell H. Taylor, Ganesh Venkatesh, Mathias Unberath
    http://arxiv.org/abs/2111.09337v1

    • [cs.CV]The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video
    John Gideon, Simon Stent
    http://arxiv.org/abs/2111.09748v1

    • [cs.CV]Towards Open Vocabulary Object Detection without Human-provided Bounding Boxes
    Mingfei Gao, Chen Xing, Juan Carlos Niebles, Junnan Li, Ran Xu, Wenhao Liu, Caiming Xiong
    http://arxiv.org/abs/2111.09452v1

    • [cs.CV]TransMix: Attend to Mix for Vision Transformers
    Jie-Neng Chen, Shuyang Sun, Ju He, Philip Torr, Alan Yuille, Song Bai
    http://arxiv.org/abs/2111.09833v1

    • [cs.CV]Wiggling Weights to Improve the Robustness of Classifiers
    Sadaf Gulshad, Ivan Sosnovik, Arnold Smeulders
    http://arxiv.org/abs/2111.09779v1

    • [cs.CY]A Survey on Metaverse: the State-of-the-art, Technologies, Applications, and Challenges
    Huansheng Ning, Hang Wang, Yujia Lin, Wenxi Wang, Sahraoui Dhelim, Fadi Farha, Jianguo Ding, Mahmoud Daneshmand
    http://arxiv.org/abs/2111.09673v1

    • [cs.DB]GAP Enhancing Semantic Interoperability of Genomic Datasets and Provenance Through Nanopublications
    Matheus Feijoó, Rodrigo Jardim, Sergio Serra, Maria Luiza Campos
    http://arxiv.org/abs/2111.08739v2

    • [cs.DB]Improving Prediction-Based Lossy Compression Dramatically Via Ratio-Quality Modeling
    Sian Jin, Sheng Di, Suren Byna, Dingwen Tao, Franck Cappello
    http://arxiv.org/abs/2111.09815v1

    • [cs.DC]Case study of SARS-CoV-2 transmission risk assessment in indoor environments using cloud computing resources
    Kumar Saurabh, Santi Adavani, Kendrick Tan, Masado Ishii, Boshun Gao, Adarsh Krishnamurthy, Hari Sundar, Baskar Ganapathysubramanian
    http://arxiv.org/abs/2111.09353v1

    • [cs.DC]Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems
    Joshua J. Daymude, Andréa W. Richa, Christian Scheideler
    http://arxiv.org/abs/2111.09449v1

    • [cs.DC]QGTC: Accelerating Quantized GNN via GPU Tensor Core
    Yuke Wang, Boyuan Feng, Yufei Ding
    http://arxiv.org/abs/2111.09547v1

    • [cs.DL]A Bibliometric Analysis of the BPM Conference Using Computational Data Analytics
    Fabian Muff, Felix Härer, Hans-Georg Fill
    http://arxiv.org/abs/2111.09737v1

    • [cs.DS]Stream Sampling with Immediate Decision
    Bardia Panahbehagh, Raphaël Jauslin, Yves Tillé
    http://arxiv.org/abs/2111.09309v1

    • [cs.HC]A co-design approach for a rehabilitation robot coach for physical rehabilitation based on the error classification of motion errors
    Maxime Devanne, Sao Mai Nguyen, Olivier Rémy-Néris, Beatrice Le Gales-Garnett, Gilles Kermarrec, André Thépaut
    http://arxiv.org/abs/2111.09729v1

    • [cs.IR]The Power of Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval
    Minghan Li, Diana Nicoleta Popa, Johan Chagnon, Yagmur Gizem Cinar, Eric Gaussier
    http://arxiv.org/abs/2111.09852v1

    • [cs.IT]Analysis and Design of Distributed MIMO Networks with a Wireless Fronthaul
    Hussein A. Ammar, Raviraj Adve, Shahram Shahbazpanahi, Gary Boudreau
    http://arxiv.org/abs/2111.09826v1

    • [cs.IT]On Generalized Galois Cyclic Orbit Flag Codes
    Clementa Alonso-González, Miguel Ángel Navarro-Pérez
    http://arxiv.org/abs/2111.09615v1

    • [cs.LG]A Novel Optimized Asynchronous Federated Learning Framework
    Zhicheng Zhou, Hailong Chen, Kunhua Li, Fei Hu, Bingjie Yan, Jieren Cheng, Xuyan Wei, Bernie Liu, Xiulai Li, Fuwen Chen, Yongji Sui
    http://arxiv.org/abs/2111.09487v1

    • [cs.LG]A Survey of Generalisation in Deep Reinforcement Learning
    Robert Kirk, Amy Zhang, Edward Grefenstette, Tim Rocktäschel
    http://arxiv.org/abs/2111.09794v1

    • [cs.LG]Assessing Social Determinants-Related Performance Bias of Machine Learning Models: A case of Hyperchloremia Prediction in ICU Population
    Songzi Liu, Yuan Luo
    http://arxiv.org/abs/2111.09507v1

    • [cs.LG]CCSL: A Causal Structure Learning Method from Multiple Unknown Environments
    Wei Chen, Yunjin Wu, Ruichu Cai, Yueguo Chen, Zhifeng Hao
    http://arxiv.org/abs/2111.09666v1

    • [cs.LG]CLMB: deep contrastive learning for robust metagenomic binning
    Pengfei Zhang, Zhengyuan Jiang, Yixuan Wang, Yu Li
    http://arxiv.org/abs/2111.09656v1

    • [cs.LG]Contrastive Multiview Coding for Enzyme-Substrate Interaction Prediction
    Apurva Kalia, Dilip Krishnan, Soha Hassoun
    http://arxiv.org/abs/2111.09467v1

    • [cs.LG]Covered Information Disentanglement: Model Transparency via Unbiased Permutation Importance
    João Pereira, Erik S. G. Stroes, Aeilko H. Zwinderman, Evgeni Levin
    http://arxiv.org/abs/2111.09744v1

    • [cs.LG]DIVA: Dataset Derivative of a Learning Task
    Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito, Stefano Soatto
    http://arxiv.org/abs/2111.09785v1

    • [cs.LG]Data-driven discovery of Bäcklund transforms and soliton evolution equations via deep neural network learning schemes
    Zijian Zhou, Li Wang, Zhenya Yan
    http://arxiv.org/abs/2111.09489v1

    • [cs.LG]DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior
    Manzoor Hussain, Nazakat Ali, Jang-Eui Hong
    http://arxiv.org/abs/2111.09533v1

    • [cs.LG]Docking-based Virtual Screening with Multi-Task Learning
    Zijing Liu, Xianbin Ye, Xiaoming Fang, Fan Wang, Hua Wu, Haifeng Wang
    http://arxiv.org/abs/2111.09502v1

    • [cs.LG]Enhanced Membership Inference Attacks against Machine Learning Models
    Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Reza Shokri
    http://arxiv.org/abs/2111.09679v1

    • [cs.LG]Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings
    Matias Valdenegro-Toro
    http://arxiv.org/abs/2111.09808v1

    • [cs.LG]FLSys: Toward an Open Ecosystem for FederatedLearning Mobile Apps
    Han Hu, Xiaopeng Jiang, Vijaya Datta Mayyuri, An Chen, Devu M. Shila, Adriaan Larmuseau, Ruoming Jin, Cristian Borcea, NhatHai Phan
    http://arxiv.org/abs/2111.09445v1

    • [cs.LG]Features selection in NBA outcome prediction through Deep Learning
    Manlio Migliorati
    http://arxiv.org/abs/2111.09695v1

    • [cs.LG]GAETS: A Graph Autoencoder Time Series Approach Towards Battery Parameter Estimation
    Edward Elson Kosasih, Rucha Bhalchandra Joshi, Janamejaya Channegowda
    http://arxiv.org/abs/2111.09314v1

    • [cs.LG]Improving Transferability of Representations via Augmentation-Aware Self-Supervision
    Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin
    http://arxiv.org/abs/2111.09613v1

    • [cs.LG]LAnoBERT : System Log Anomaly Detection based on BERT Masked Language Model
    Yukyung Lee, Jina Kim, Pilsung Kang
    http://arxiv.org/abs/2111.09564v1

    • [cs.LG]Low Precision Decentralized Distributed Training with Heterogeneous Data
    Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy
    http://arxiv.org/abs/2111.09389v1

    • [cs.LG]Merging Models with Fisher-Weighted Averaging
    Michael Matena, Colin Raffel
    http://arxiv.org/abs/2111.09832v1

    • [cs.LG]On the Effectiveness of Sparsification for Detecting the Deep Unknowns
    Yiyou Sun, Yixuan Li
    http://arxiv.org/abs/2111.09805v1

    • [cs.LG]Optimal Simple Regret in Bayesian Best Arm Identification
    Junpei Komiyama, Kaito Ariu, Masahiro Kato, Chao Qin
    http://arxiv.org/abs/2111.09885v1

    • [cs.LG]Personalized Federated Learning through Local Memorization
    Othmane Marfoq, Giovanni Neglia, Laetitia Kameni, Richard Vidal
    http://arxiv.org/abs/2111.09360v1

    • [cs.LG]Route Optimization via Environment-Aware Deep Network and Reinforcement Learning
    Pengzhan Guo, Keli Xiao, Zeyang Ye, Wei Zhu
    http://arxiv.org/abs/2111.09124v1

    • [cs.LG]Self-Attending Task Generative Adversarial Network for Realistic Satellite Image Creation
    Nathan Toner, Justin Fletcher
    http://arxiv.org/abs/2111.09463v1

    • [cs.LG]Self-Learning Tuning for Post-Silicon Validation
    Peter Domanski, Dirk Pflüger, Jochen Rivoir, Raphaël Latty
    http://arxiv.org/abs/2111.08995v2

    • [cs.LG]Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning
    Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee
    http://arxiv.org/abs/2111.09858v1

    • [cs.LG]The People’s Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage
    Daniel Galvez, Greg Diamos, Juan Ciro, Juan Felipe Cerón, Keith Achorn, Anjali Gopi, David Kanter, Maximilian Lam, Mark Mazumder, Vijay Janapa Reddi
    http://arxiv.org/abs/2111.09344v1

    • [cs.LG]The Prominence of Artificial Intelligence in COVID-19
    MD Abdullah Al Nasim, Aditi Dhali, Faria Afrin, Noshin Tasnim Zaman, Nazmul Karim
    http://arxiv.org/abs/2111.09537v1

    • [cs.LG]Training Neural Networks with Fixed Sparse Masks
    Yi-Lin Sung, Varun Nair, Colin Raffel
    http://arxiv.org/abs/2111.09839v1

    • [cs.LG]You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
    Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Fung, Vikas Singh
    http://arxiv.org/abs/2111.09714v1

    • [cs.NE]Continuous learning of spiking networks trained with local rules
    Dmitry Antonov, Kirill Sviatov, Sergey Sukhov
    http://arxiv.org/abs/2111.09553v1

    • [cs.NE]Evolutionary Algorithm for Graph Coloring Problem
    Robiul Islam, Arup Kumar Pramanik
    http://arxiv.org/abs/2111.09743v1

    • [cs.NE]L4-Norm Weight Adjustments for Converted Spiking Neural Networks
    Jason Allred, Kaushik Roy
    http://arxiv.org/abs/2111.09446v1

    • [cs.NI]An Experimental Study of Latency for IEEE 802.11be Multi-link Operation
    Marc Carrascosa, Giovanni Geraci, Edward Knightly, Boris Bellalta
    http://arxiv.org/abs/2111.09281v1

    • [cs.RO]A Low-Cost, Easy-to-Manufacture, Flexible, Multi-Taxel Tactile Sensor and its Application to In-Hand Object Recognition
    Tessa J. Pannen, Steffen Puhlmann, Oliver Brock
    http://arxiv.org/abs/2111.09687v1

    • [cs.RO]Assisted Robust Reward Design
    Jerry Zhi-Yang He, Anca D. Dragan
    http://arxiv.org/abs/2111.09884v1

    • [cs.RO]Backswimmer Inspired Miniature Robot with Buoyancy Auto-Regulation through Controlled Nucleation and Release of Microbubbles
    Dror Kobo, Bat-El Pinchasik
    http://arxiv.org/abs/2111.09648v1

    • [cs.RO]Complex Terrain Navigation via Model Error Prediction
    Adam Polevoy, Craig Knuth, Katie M. Popek, Kapil D. Katyal
    http://arxiv.org/abs/2111.09768v1

    • [cs.RO]Hybrid Feedback for Autonomous Navigation in Environments with Arbitrary Convex Obstacles
    Mayur Sawant, Soulaimane Berkane, Ilia Polusin, Abdelhamid Tayebi
    http://arxiv.org/abs/2111.09380v1

    • [cs.RO]Lidar with Velocity: Motion Distortion Correction of Point Clouds from Oscillating Scanning Lidars
    Wen Yang, Zheng Gong, Baifu Huang, Xiaoping Hong
    http://arxiv.org/abs/2111.09497v1

    • [cs.RO]Monitoring Over the Long Term: Intermittent Deployment and Sensing Strategies for Multi-Robot Teams
    Jun Liu, Ryan K. Williams
    http://arxiv.org/abs/2111.09386v1

    • [cs.RO]On the Effectiveness of Iterative Learning Control
    Anirudh Vemula, Wen Sun, Maxim Likhachev, J. Andrew Bagnell
    http://arxiv.org/abs/2111.09434v1

    • [cs.RO]Punyo-1: Soft tactile-sensing upper-body robot for large object manipulation and physical human interaction
    Aimee Goncalves, Naveen Kuppuswamy, Andrew Beaulieu, Avinash Uttamchandani, Katherine M. Tsui, Alex Alspach
    http://arxiv.org/abs/2111.09354v1

    • [cs.RO]Submodular Optimization for Coupled Task Allocation and Intermittent Deployment Problems
    Jun Liu, Ryan K. Williams
    http://arxiv.org/abs/2111.09387v1

    • [cs.RO]Technology Report:Multi-Mobile Robot Localization and Navigation based on Visible Light Positioning
    Yanyi Chen, Zhiqing Zhong, Shangsheng Wen, Weipeng Guan
    http://arxiv.org/abs/2111.09050v2

    • [cs.RO]The Effects of Learning in Morphologically Evolving Robot Systems
    Jie Luo, Aart Stuurman, Jakub M. Tomczak, Jacintha Ellers, Agoston E. Eiben
    http://arxiv.org/abs/2111.09851v1

    • [cs.RO]Unsupervised Online Learning for Robotic Interestingness with Visual Memory
    Chen Wang, Yuheng Qiu, Wenshan Wang, Yafei Hu, Seungchan Kim, Sebastian Scherer
    http://arxiv.org/abs/2111.09793v1

    • [cs.RO]Visual Navigation Using Sparse Optical Flow and Time-to-Transit
    Chiara Boretti, Philippe Bich, Yanyu Zhang, John Baillieul
    http://arxiv.org/abs/2111.09669v1

    • [cs.SD]Towards Intelligibility-Oriented Audio-Visual Speech Enhancement
    Tassadaq Hussain, Mandar Gogate, Kia Dashtipour, Amir Hussain
    http://arxiv.org/abs/2111.09642v1

    • [cs.SI]Transformation of Node to Knowledge Graph Embeddings for Faster Link Prediction in Social Networks
    Archit Parnami, Mayuri Deshpande, Anant Kumar Mishra, Minwoo Lee
    http://arxiv.org/abs/2111.09308v1

    • [eess.AS]BLOOM-Net: Blockwise Optimization for Masking Networks Toward Scalable and Efficient Speech Enhancement
    Sunwoo Kim, Minje Kim
    http://arxiv.org/abs/2111.09372v1

    • [eess.IV]A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration
    Théo Bodrito, Alexandre Zouaoui, Jocelyn Chanussot, Julien Mairal
    http://arxiv.org/abs/2111.09708v1

    • [eess.IV]Large-scale Building Height Retrieval from Single SAR Imagery based on Bounding Box Regression Networks
    Yao Sun, Lichao Mou, Yuanyuan Wang, Sina Montazeri, Xiao Xiang Zhu
    http://arxiv.org/abs/2111.09460v1

    • [eess.IV]Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction
    George Yiasemis, Clara I. Sánchez, Jan-Jakob Sonke, Jonas Teuwen
    http://arxiv.org/abs/2111.09639v1

    • [eess.SP]A Modular 1D-CNN Architecture for Real-time Digital Pre-distortion
    Udara De Silva, Toshiaki Koike-Akino, Rui Ma, Ao Yamashita, Hideyuki Nakamizo
    http://arxiv.org/abs/2111.09637v1

    • [eess.SP]CSI Clustering with Variational Autoencoding
    Michael Baur, Michael Würth, Vlad-Costin Andrei, Michael Koller, Wolfgang Utschick
    http://arxiv.org/abs/2111.09758v1

    • [eess.SP]LiDAR-Aided Mobile Blockage Prediction in Real-World Millimeter Wave Systems
    Shunyao Wu, Chaitali Chakrabarti, Ahmed Alkhateeb
    http://arxiv.org/abs/2111.09581v1

    • [eess.SP]Radar Aided 6G Beam Prediction: Deep Learning Algorithms and Real-World Demonstration
    Umut Demirhan, Ahmed Alkhateeb
    http://arxiv.org/abs/2111.09676v1

    • [math.CO]On the Existence of Coproducts in Categories of q-Matroids
    Heide Gluesing-Luerssen, Benjamin Jany
    http://arxiv.org/abs/2111.09723v1

    • [math.DS]Information-theoretic formulation of dynamical systems: causality, modeling, and control
    Adrián Lozano-Durán, Gonzalo Arranz
    http://arxiv.org/abs/2111.09484v1

    • [math.ST]Bounds in 今日学术视野(2021.11.20) - 图2 Wasserstein distance on the normal approximation of general M-estimators
    François Bachoc, Max Fathi
    http://arxiv.org/abs/2111.09721v1

    • [math.ST]Ergodic Estimators of double exponential Ornstein-Ulenbeck process
    Yaozhong Hu, Neha Sharma
    http://arxiv.org/abs/2111.09573v1

    • [math.ST]Unbiased Risk Estimation in the Normal Means Problem via Coupled Bootstrap Techniques
    Natalia L. Oliveira, Jing Lei, Ryan J. Tibshirani
    http://arxiv.org/abs/2111.09447v1

    • [physics.flu-dyn]Learning Free-Surface Flow with Physics-Informed Neural Networks
    Raphael Leiteritz, Marcel Hurler, Dirk Pflüger
    http://arxiv.org/abs/2111.09705v1

    • [physics.soc-ph]Adversarial attacks on voter model dynamics in complex networks
    Katsumi Chiyomaru, Kazuhiro Takemoto
    http://arxiv.org/abs/2111.09561v1

    • [q-bio.NC]Locally Learned Synaptic Dropout for Complete Bayesian Inference
    Kevin L. McKee, Ian C. Crandell, Rishidev Chaudhuri, Randall C. O’Reilly
    http://arxiv.org/abs/2111.09780v1

    • [q-bio.PE]A Novel Compartmental Approach to Modeling COVID-19 Disease Dynamics and Analyzing the Effect of Common Preventative Measures
    Caden Lin
    http://arxiv.org/abs/2111.09402v1

    • [q-fin.ST]Effect of the U.S.—China Trade War on Stock Markets: A Financial Contagion Perspective
    Minseog Oh, Donggyu Kim
    http://arxiv.org/abs/2111.09655v1

    • [quant-ph]Near-Optimal Quantum Algorithms for Multivariate Mean Estimation
    Arjan Cornelissen, Yassine Hamoudi, Sofiene Jerbi
    http://arxiv.org/abs/2111.09787v1

    • [stat.AP]Estimating the concentration parameter of a von Mises distribution: a systematic simulation benchmark
    Guillaume Marrelec, Alain Giron
    http://arxiv.org/abs/2111.09660v1

    • [stat.AP]Neural Network Kalman filtering for 3D object tracking from linear array ultrasound data
    Arttu Arjas, Erwin J. Alles, Efthymios Maneas, Simon Arridge, Adrien Desjardins, Mikko J. Sillanpää, Andreas Hauptmann
    http://arxiv.org/abs/2111.09631v1

    • [stat.AP]Number of New Top 2% Researchers from China and USA Over Time
    Lei Liu, Song Yao, Kevin Liu
    http://arxiv.org/abs/2111.09473v1

    • [stat.ME]A sample size heuristic for network scale-up studies
    Nathaniel Josephs, Dennis M. Feehan, Forrest W. Crawford
    http://arxiv.org/abs/2111.09684v1

    • [stat.ME]Bayes factors for accelerated life testing models
    Neill Smit, Lizanne Raubenheimer
    http://arxiv.org/abs/2111.09593v1

    • [stat.ME]Extending the coefficient of variation for measuring heterogeneity following a meta-regression
    Maxwell Cairns, Luke A. Prendergast
    http://arxiv.org/abs/2111.09518v1

    • [stat.ME]Implicit copula variational inference
    Michael Stanley Smith, Rubén Loaiza-Maya
    http://arxiv.org/abs/2111.09511v1

    • [stat.ME]Nonparametric Scanning For Nonrandom Missing Data With Continuous Instrumental Variables
    Arkaprabha Ganguli, David Todem
    http://arxiv.org/abs/2111.09429v1

    • [stat.ME]Return-to-baseline multiple imputation for missing values in clinical trials
    Yongming Qu, Biyue Dai
    http://arxiv.org/abs/2111.09423v1

    • [stat.ML]C-OPH: Improving the Accuracy of One Permutation Hashing (OPH) with Circulant Permutations
    Xiaoyun Li, Ping Li
    http://arxiv.org/abs/2111.09544v1

    • [stat.ML]Causal Forecasting:Generalization Bounds for Autoregressive Models
    Leena Chennuru Vankadara, Philipp Michael Faller, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing
    http://arxiv.org/abs/2111.09831v1

    • [stat.ML]From Optimality to Robustness: Dirichlet Sampling Strategies in Stochastic Bandits
    Dorian Baudry, Patrick Saux, Odalric-Ambrym Maillard
    http://arxiv.org/abs/2111.09724v1

    • [stat.ML]MCCE: Monte Carlo sampling of realistic counterfactual explanations
    Annabelle Redelmeier, Martin Jullum, Kjersti Aas, Anders Løland
    http://arxiv.org/abs/2111.09790v1

    • [stat.ML]Sampling To Improve Predictions For Underrepresented Observations In Imbalanced Data
    Rune D. Kjærsgaard, Manja G. Grønberg, Line K. H. Clemmensen
    http://arxiv.org/abs/2111.09065v2