cs.AI - 人工智能
cs.AR - 硬件体系结构
cs.CL - 计算与语言
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DB - 数据库
cs.DC - 分布式、并行与集群计算
cs.DS - 数据结构与算法
cs.GR - 计算机图形学
cs.GT - 计算机科学与博弈论
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.MA - 多代理系统
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.SI - 社交网络与信息网络
econ.EM - 计量经济学
eess.IV - 图像与视频处理
eess.SP - 信号处理
eess.SY - 系统和控制
math.OC - 优化与控制
math.ST - 统计理论
physics.comp-ph - 计算物理学
stat.AP - 应用统计
stat.CO - 统计计算
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [cs.AI]Belief propagation for permutations, rankings, and partial orders
• [cs.AI]Learner to learner fuzzy profiles similarity using a hybrid interaction analysis grid
• [cs.AR]SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference
• [cs.CL]A Survey of Knowledge Enhanced Pre-trained Models
• [cs.CL]BERT4GCN: Using BERT Intermediate Layers to Augment GCN for Aspect-based Sentiment Classification
• [cs.CL]Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning
• [cs.CL]Improving Punctuation Restoration for Speech Transcripts via External Data
• [cs.CL]Learning to Ask for Data-Efficient Event Argument Extraction
• [cs.CL]Natural language understanding for logical games
• [cs.CL]Phonology Recognition in American Sign Language
• [cs.CL]Span Labeling Approach for Vietnamese and Chinese Word Segmentation
• [cs.CL]Under the Microscope: Interpreting Readability Assessment Models for Filipino
• [cs.CL]Unpacking the Interdependent Systems of Discrimination: Ableist Bias in NLP Systems through an Intersectional Lens
• [cs.CV]ASH: A Modern Framework for Parallel Spatial Hashing in 3D Perception
• [cs.CV]Accelerating Inverse Rendering By Using a GPU and Reuse of Light Paths
• [cs.CV]Beyond Neighbourhood-Preserving Transformations for Quantization-Based Unsupervised Hashing
• [cs.CV]Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images
• [cs.CV]Consistent Explanations by Contrastive Learning
• [cs.CV]Data-Efficient Instance Segmentation with a Single GPU
• [cs.CV]Deep Learning-based Action Detection in Untrimmed Videos: A Survey
• [cs.CV]Do Self-Supervised and Supervised Methods Learn Similar Visual Representations?
• [cs.CV]Generative Memory-Guided Semantic Reasoning Model for Image Inpainting
• [cs.CV]Geometry Attention Transformer with Position-aware LSTMs for Image Captioning
• [cs.CV]HUMBI: A Large Multiview Dataset of Human Body Expressions and Benchmark Challenge
• [cs.CV]Instance Segmentation Challenge Track Technical Report, VIPriors Workshop at ICCV 2021: Task-Specific Copy-Paste Data Augmentation Method for Instance Segmentation
• [cs.CV]Lightweight Transformer in Federated Setting for Human Activity Recognition
• [cs.CV]Mask or Non-Mask? Robust Face Mask Detector via Triplet-Consistency Representation Learning
• [cs.CV]MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation
• [cs.CV]Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
• [cs.CV]PhiNets: a scalable backbone for low-power AI at the edge
• [cs.CV]ResNet strikes back: An improved training procedure in timm
• [cs.CV]Robustly Removing Deep Sea Lighting Effects for Visual Mapping of Abyssal Plains
• [cs.CV]Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects
• [cs.CV]Self-Supervised Decomposition, Disentanglement and Prediction of Video Sequences while Interpreting Dynamics: A Koopman Perspective
• [cs.CV]Self-supervised Secondary Landmark Detection via 3D Representation Learning
• [cs.CV]Stochastic Modeling for Learnable Human Pose Triangulation
• [cs.CV]Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation
• [cs.CV]Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
• [cs.CV]Survey and synthesis of state of the art in driver monitoring
• [cs.CV]Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection
• [cs.CV]TEACh: Task-driven Embodied Agents that Chat
• [cs.CV]Towards Protecting Face Embeddings in Mobile Face Verification Scenarios
• [cs.CV]Unsupervised Motion Representation Learning with Capsule Autoencoders
• [cs.CV]Video Temporal Relationship Mining for Data-Efficient Person Re-identification
• [cs.CV]Visual Cluster Separation Using High-Dimensional Sharpened Dimensionality Reduction
• [cs.CY]Dynamic Emotions of Supporters and Opponents of Anti-racism Movement from George Floyd Protests
• [cs.DB]LEMON: Explainable Entity Matching
• [cs.DC]Characterizing Concurrency Mechanisms for NVIDIA GPUs under Deep Learning Workloads
• [cs.DC]Towards Generalised Half-Duplex Systems
• [cs.DS]Online Primal-Dual Algorithms with Predictions for Packing Problems
• [cs.GR]GAN-based Reactive Motion Synthesis with Class-aware Discriminators for Human-human Interaction
• [cs.GT]The Complexity of Learning Approval-Based Multiwinner Voting Rules
• [cs.IR]Explainable Point-Based Document Visualizations
• [cs.IR]SAM: A Self-adaptive Attention Module for Context-Aware Recommendation System
• [cs.IT]A Unified Discretization Approach to Compute-Forward: From Discrete to Continuous Inputs
• [cs.IT]Channel Estimation with Reconfigurable Intelligent Surfaces — A General Framework
• [cs.IT]Predicting Flat-Fading Channels via Meta-Learned Closed-Form Linear Filters and Equilibrium Propagation
• [cs.IT]Reconfigurable Intelligent Surfaces Based on Single, Group, and Fully Connected Discrete-Value Impedance Networks
• [cs.IT]Users’ ability to perceive misinformation: An information quality assessment approach
• [cs.IT]Velocity-aware Antenna Selection in Predictor Antenna Systems
• [cs.IT]What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligence
• [cs.LG]A survey on datasets for fairness-aware machine learning
• [cs.LG]An Ensemble-based Multi-Criteria Decision Making Method for COVID-19 Cough Classification
• [cs.LG]Applying Differential Privacy to Tensor Completion
• [cs.LG]Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference
• [cs.LG]Batched Thompson Sampling
• [cs.LG]Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning
• [cs.LG]DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networks
• [cs.LG]Discovering Boundary Values of Feature-based Machine Learning Classifiers through Exploratory Datamorphic Testing
• [cs.LG]Divergence-Regularized Multi-Agent Actor-Critic
• [cs.LG]DualNet: Continual Learning, Fast and Slow
• [cs.LG]Empirical Quantitative Analysis of COVID-19 Forecasting Models
• [cs.LG]Evaluating the fairness of fine-tuning strategies in self-supervised learning
• [cs.LG]Fed-LAMB: Layerwise and Dimensionwise Locally Adaptive Optimization Algorithm
• [cs.LG]Inverse airfoil design method for generating varieties of smooth airfoils using conditional WGAN-gp
• [cs.LG]Iterative Teacher-Aware Learning
• [cs.LG]Large-scale ASR Domain Adaptation by Self- and Semi-supervised Learning
• [cs.LG]Leveraging power grid topology in machine learning assisted optimal power flow
• [cs.LG]Offline Reinforcement Learning with Reverse Model-based Imagination
• [cs.LG]On the Importance of Gradients for Detecting Distributional Shifts in the Wild
• [cs.LG]Open-set Classification of Common Waveforms Using A Deep Feed-forward Network and Binary Isolation Forest Models
• [cs.LG]PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series
• [cs.LG]Personalized Rehabilitation Robotics based on Online Learning Control
• [cs.LG]Predicting COVID-19 Patient Shielding: A Comprehensive Study
• [cs.LG]Probabilistic Robust Autoencoders for Anomaly Detection
• [cs.LG]Q-Net: A Quantitative Susceptibility Mapping-based Deep Neural Network for Differential Diagnosis of Brain Iron Deposition in Hemochromatosis
• [cs.LG]Rapid Assessments of Light-Duty Gasoline Vehicle Emissions Using On-Road Remote Sensing and Machine Learning
• [cs.LG]Reconstruction for Powerful Graph Representations
• [cs.LG]SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time Series
• [cs.LG]Scientific evidence extraction
• [cs.LG]Stochastic Contrastive Learning
• [cs.LG]Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond
• [cs.LG]Tree in Tree: from Decision Trees to Decision Graphs
• [cs.LG]Two ways towards combining Sequential Neural Network and Statistical Methods to Improve the Prediction of Time Series
• [cs.LG]Update in Unit Gradient
• [cs.LG]UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
• [cs.MA]Decentralized Graph-Based Multi-Agent Reinforcement Learning Using Reward Machines
• [cs.MA]Emergence of Theory of Mind Collaboration in Multiagent Systems
• [cs.MA]Temporal Graphs and Temporal Network Characteristics for Bio-Inspired Networks During Optimization
• [cs.NE]New Evolutionary Computation Models and their Applications to Machine Learning
• [cs.NE]Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework
• [cs.NI]A Novel Simplified Swarm Optimization for Generalized Reliability Redundancy Allocation Problem
• [cs.NI]Automating Internet of Things Network Traffic Collection with Robotic Arm Interactions
• [cs.NI]Cellular traffic offloading via Opportunistic Networking with Reinforcement Learning
• [cs.RO]A Sufficient Condition for Convex Hull Property in General Convex Spatio-Temporal Corridors
• [cs.RO]An Under-Actuated Whippletree Mechanism Gripper based on Multi-Objective Design Optimization with Auto-Tuned Weights
• [cs.RO]Batch Belief Trees for Motion Planning Under Uncertainty
• [cs.RO]Dynamic Modeling and Simulation of a Four-wheel Skid-Steer Mobile Robot using Linear Graphs
• [cs.RO]Dynamic Models of Spherical Parallel Robots for Model-Based Control Schemes
• [cs.RO]From SLAM to Situational Awareness: Challenges and Survey
• [cs.RO]Guiding Evolutionary Strategies by Differentiable Robot Simulators
• [cs.RO]Improving Object Permanence using Agent Actions and Reasoning
• [cs.RO]Improving Object Permanence using Agent Actions and Reasoning
• [cs.RO]Learning Reward Functions from Scale Feedback
• [cs.RO]Learning from Demonstrations for Autonomous Soft-tissue Retraction
• [cs.RO]Probabilistic Object Maps for Long-Term Robot Localization
• [cs.RO]Real-Time Risk-Bounded Tube-Based Trajectory Safety Verification
• [cs.RO]Simulation-based multi-criteria comparison of mono-articular and bi-articular exoskeletons during walking with and without load
• [cs.RO]Study of Signal Temporal Logic Robustness Metrics for Robotic Tasks Optimization
• [cs.RO]Topologically-Informed Atlas Learning
• [cs.RO]Validating Robotics Simulators on Real World Impacts
• [cs.RO]Vision-Only Robot Navigation in a Neural Radiance World
• [cs.SI]#ContextMatters: Advantages and Limitations of Using Machine Learning to Support Women in Politics
• [cs.SI]Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences
• [cs.SI]Inequality and Inequity in Network-based Ranking and Recommendation Algorithms
• [cs.SI]Unsupervised Belief Representation Learning in Polarized Networks with Information-Theoretic Variational Graph Auto-Encoders
• [cs.SI]What Happened in Social Media during the 2020 BLM Movement? An Analysis of Deleted and Suspended Users in Twitter
• [econ.EM]Relative Contagiousness of Emerging Virus Variants: An Analysis of SARS-CoV-2 Alpha and Delta Variants
• [eess.IV]A Graph-theoretic Algorithm for Small Bowel Path Tracking in CT Scans
• [eess.IV]DCT based Fusion of Variable Exposure Images for HDRI
• [eess.IV]DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization
• [eess.IV]Development of the algorithm for differentiating bone metastases and trauma of the ribs in bone scintigraphy and demonstration of visual evidence of the algorithm — Using only anterior bone scan view of thorax
• [eess.IV]Learning of Inter-Label Geometric Relationships Using Self-Supervised Learning: Application To Gleason Grade Segmentation
• [eess.IV]Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising
• [eess.IV]Optic Disc Segmentation using Disk-Centered Patch Augmentation
• [eess.IV]Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration
• [eess.SP]A Bayesian approach to location estimation of mobile devices from mobile network operator data
• [eess.SP]A survey on active noise control techniques — Part I: Linear systems
• [eess.SP]Improving Load Forecast in Energy Markets During COVID-19
• [eess.SP]Learn to Communicate with Neural Calibration: Scalability and Generalization
• [eess.SY]Error-free approximation of explicit linear MPC through lattice piecewise affine expression
• [eess.SY]RLO-MPC: Robust Learning-Based Output Feedback MPC for Improving the Performance of Uncertain Systems in Iterative Tasks
• [math.OC]Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation
• [math.ST]Componentwise Equivariant Estimation of Order Restricted Location and Scale Parameters In Bivariate Models: A Unified Study
• [math.ST]Inference on the maximal rank of time-varying covariance matrices using high-frequency data
• [physics.comp-ph]Closed-form discovery of structural errors in models of chaotic systems by integrating Bayesian sparse regression and data assimilation
• [stat.AP]A Riemannian Approach to Multivariate Geostatistical Modeling
• [stat.AP]Confidence intervals for efficiencies in particle physics experiments
• [stat.AP]State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting
• [stat.CO]ebnm: An R Package for Solving the Empirical Bayes Normal Means Problem Using a Variety of Prior Families
• [stat.ME]A Review and Critique of Auxiliary Information-Based Process Monitoring Methods
• [stat.ME]Censored autoregressive regression models with Student- innovations
• [stat.ME]Comparing Sequential Forecasters
• [stat.ME]Confounder importance learning for treatment effect inference
• [stat.ME]Dimension Reduction and Data Visualization for Fréchet Regression
• [stat.ME]Regression-based estimation of heterogeneous treatment effects when extending inferences from a randomized trial to a target population
• [stat.ML]A Cramér Distance perspective on Non-crossing Quantile Regression in Distributional Reinforcement Learning
• [stat.ML]Lagrangian Inference for Ranking Problems
• [stat.ML]Powerpropagation: A sparsity inducing weight reparameterisation
• [stat.ML]Predicting Consumer Purchasing Decision in The Online Food Delivery Industry
• [stat.ML]Score-Based Generative Classifiers
• [stat.ML]Sim and Real: Better Together
• [stat.ML]Smooth Normalizing Flows
• [stat.ML]TyXe: Pyro-based Bayesian neural nets for Pytorch
• [stat.ML]Weight Vector Tuning and Asymptotic Analysis of Binary Linear Classifiers
·····································
• [cs.AI]Belief propagation for permutations, rankings, and partial orders
George T. Cantwell, Cristopher Moore
http://arxiv.org/abs/2110.00513v1
• [cs.AI]Learner to learner fuzzy profiles similarity using a hybrid interaction analysis grid
Chabane Khentout, Khadidja Harbouche, Mahieddine Djoudi
http://arxiv.org/abs/2110.00247v1
• [cs.AR]SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference
Jude Haris, Perry Gibson, José Cano, Nicolas Bohm Agostini, David Kaeli
http://arxiv.org/abs/2110.00478v1
• [cs.CL]A Survey of Knowledge Enhanced Pre-trained Models
Jian Yang, Gang Xiao, Yulong Shen, Wei Jiang, Xinyu Hu, Ying Zhang, Jinghui Peng
http://arxiv.org/abs/2110.00269v1
• [cs.CL]BERT4GCN: Using BERT Intermediate Layers to Augment GCN for Aspect-based Sentiment Classification
Zeguan Xiao, Jiarun Wu, Qingliang Chen, Congjian Deng
http://arxiv.org/abs/2110.00171v1
• [cs.CL]Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning
Chongyang Tao, Jiazhan Feng, Chang Liu, Juntao Li, Xiubo Geng, Daxin Jiang
http://arxiv.org/abs/2110.00159v1
• [cs.CL]Improving Punctuation Restoration for Speech Transcripts via External Data
Xue-Yong Fu, Cheng Chen, Md Tahmid Rahman Laskar, Shashi Bhushan TN, Simon Corston-Oliver
http://arxiv.org/abs/2110.00560v1
• [cs.CL]Learning to Ask for Data-Efficient Event Argument Extraction
Hongbin Ye, Ningyu Zhang, Zhen Bi, Shumin Deng, Chuanqi Tan, Hui Chen, Fei Huang, Huajun Chen
http://arxiv.org/abs/2110.00479v1
• [cs.CL]Natural language understanding for logical games
Adrian Groza, Cristian Nitu
http://arxiv.org/abs/2110.00558v1
• [cs.CL]Phonology Recognition in American Sign Language
Federico Tavella, Aphrodite Galata, Angelo Cangelosi
http://arxiv.org/abs/2110.00453v1
• [cs.CL]Span Labeling Approach for Vietnamese and Chinese Word Segmentation
Duc-Vu Nguyen, Linh-Bao Vo, Dang Van Thin, Ngan Luu-Thuy Nguyen
http://arxiv.org/abs/2110.00156v1
• [cs.CL]Under the Microscope: Interpreting Readability Assessment Models for Filipino
Joseph Marvin Imperial, Ethel Ong
http://arxiv.org/abs/2110.00157v1
• [cs.CL]Unpacking the Interdependent Systems of Discrimination: Ableist Bias in NLP Systems through an Intersectional Lens
Saad Hassan, Matt Huenerfauth, Cecilia Ovesdotter Alm
http://arxiv.org/abs/2110.00521v1
• [cs.CV]ASH: A Modern Framework for Parallel Spatial Hashing in 3D Perception
Wei Dong, Yixing Lao, Michael Kaess, Vladlen Koltun
http://arxiv.org/abs/2110.00511v1
• [cs.CV]Accelerating Inverse Rendering By Using a GPU and Reuse of Light Paths
Ido Czerninski, Yoav Y. Schechner
http://arxiv.org/abs/2110.00085v1
• [cs.CV]Beyond Neighbourhood-Preserving Transformations for Quantization-Based Unsupervised Hashing
Sobhan Hemati, H. R. Tizhoosh
http://arxiv.org/abs/2110.00216v1
• [cs.CV]Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images
Zhuowan Li, Elias Stengel-Eskin, Yixiao Zhang, Cihang Xie, Quan Tran, Benjamin Van Durme, Alan Yuille
http://arxiv.org/abs/2110.00519v1
• [cs.CV]Consistent Explanations by Contrastive Learning
Vipin Pillai, Soroush Abbasi Koohpayegani, Ashley Ouligian, Dennis Fong, Hamed Pirsiavash
http://arxiv.org/abs/2110.00527v1
• [cs.CV]Data-Efficient Instance Segmentation with a Single GPU
Pengyu Chen, Wanhua Li, Jiwen Lu
http://arxiv.org/abs/2110.00242v1
• [cs.CV]Deep Learning-based Action Detection in Untrimmed Videos: A Survey
Elahe Vahdani, Yingli Tian
http://arxiv.org/abs/2110.00111v1
• [cs.CV]Do Self-Supervised and Supervised Methods Learn Similar Visual Representations?
Tom George Grigg, Dan Busbridge, Jason Ramapuram, Russ Webb
http://arxiv.org/abs/2110.00528v1
• [cs.CV]Generative Memory-Guided Semantic Reasoning Model for Image Inpainting
Xin Feng, Wenjie Pei, Fengjun Li, Fanglin Chen, David Zhang, Guangming Lu
http://arxiv.org/abs/2110.00261v1
• [cs.CV]Geometry Attention Transformer with Position-aware LSTMs for Image Captioning
Chi Wang, Yulin Shen, Luping Ji
http://arxiv.org/abs/2110.00335v1
• [cs.CV]HUMBI: A Large Multiview Dataset of Human Body Expressions and Benchmark Challenge
Jae Shin Yoon, Zhixuan Yu, Jaesik Park, Hyun Soo Park
http://arxiv.org/abs/2110.00119v1
• [cs.CV]Instance Segmentation Challenge Track Technical Report, VIPriors Workshop at ICCV 2021: Task-Specific Copy-Paste Data Augmentation Method for Instance Segmentation
Jahongir Yunusov, Shohruh Rakhmatov, Abdulaziz Namozov, Abdulaziz Gaybulayev, Tae-Hyong Kim
http://arxiv.org/abs/2110.00470v1
• [cs.CV]Lightweight Transformer in Federated Setting for Human Activity Recognition
Ali Raza, Kim Phuc Tran, Ludovic Koehl, Shujun Li, Xianyi Zeng, Khaled Benzaidi
http://arxiv.org/abs/2110.00244v1
• [cs.CV]Mask or Non-Mask? Robust Face Mask Detector via Triplet-Consistency Representation Learning
Chun-Wei Yang, Thanh-Hai Phung, Hong-Han Shuai, Wen-Huang Cheng
http://arxiv.org/abs/2110.00523v1
• [cs.CV]MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation
Jonas Heylen, Mark De Wolf, Bruno Dawagne, Marc Proesmans, Luc Van Gool, Wim Abbeloos, Hazem Abdelkawy, Daniel Olmeda Reino
http://arxiv.org/abs/2110.00464v1
• [cs.CV]Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
Zhen Chen, Meilu Zhu, Chen Yang, Yixuan Yuan
http://arxiv.org/abs/2110.00394v1
• [cs.CV]PhiNets: a scalable backbone for low-power AI at the edge
Francesco Paissan, Alberto Ancilotto, Elisabetta Farella
http://arxiv.org/abs/2110.00337v1
• [cs.CV]ResNet strikes back: An improved training procedure in timm
Ross Wightman, Hugo Touvron, Hervé Jégou
http://arxiv.org/abs/2110.00476v1
• [cs.CV]Robustly Removing Deep Sea Lighting Effects for Visual Mapping of Abyssal Plains
Kevin Köser, Yifan Song, Lasse Petersen, Emanuel Wenzlaff, Felix Woelk
http://arxiv.org/abs/2110.00480v1
• [cs.CV]Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects
Haoping Xu, Yi Ru Wang, Sagi Eppel, Alàn Aspuru-Guzik, Florian Shkurti, Animesh Garg
http://arxiv.org/abs/2110.00087v1
• [cs.CV]Self-Supervised Decomposition, Disentanglement and Prediction of Video Sequences while Interpreting Dynamics: A Koopman Perspective
Armand Comas, Sandesh Ghimire, Haolin Li, Mario Sznaier, Octavia Camps
http://arxiv.org/abs/2110.00547v1
• [cs.CV]Self-supervised Secondary Landmark Detection via 3D Representation Learning
Praneet C. Bala, Jan Zimmermann, Hyun Soo Park, Benjamin Y. Hayden
http://arxiv.org/abs/2110.00543v1
• [cs.CV]Stochastic Modeling for Learnable Human Pose Triangulation
Kristijan Bartol, David Bojanić, Tomislav Petković, Tomislav Pribanić
http://arxiv.org/abs/2110.00280v1
• [cs.CV]Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation
Zheng Li, Xiang Li, Lingfeng Zhang, Jian Yang, Zhigeng Pan
http://arxiv.org/abs/2110.00329v1
• [cs.CV]Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
Ni Zhang, Junwei Han, Nian Liu, Ling Shao
http://arxiv.org/abs/2110.00338v1
• [cs.CV]Survey and synthesis of state of the art in driver monitoring
Anaïs Halin, Jacques G. Verly, Marc Van Droogenbroeck
http://arxiv.org/abs/2110.00472v1
• [cs.CV]Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection
Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz, Mohsen Ali
http://arxiv.org/abs/2110.00249v1
• [cs.CV]TEACh: Task-driven Embodied Agents that Chat
Aishwarya Padmakumar, Jesse Thomason, Ayush Shrivastava, Patrick Lange, Anjali Narayan-Chen, Spandana Gella, Robinson Piramithu, Gokhan Tur, Dilek Hakkani-Tur
http://arxiv.org/abs/2110.00534v1
• [cs.CV]Towards Protecting Face Embeddings in Mobile Face Verification Scenarios
Vedrana Krivokuća Hahn, Sébastien Marcel
http://arxiv.org/abs/2110.00434v1
• [cs.CV]Unsupervised Motion Representation Learning with Capsule Autoencoders
Ziwei Xu, Xudong Shen, Yongkang Wong, Mohan S Kankanhalli
http://arxiv.org/abs/2110.00529v1
• [cs.CV]Video Temporal Relationship Mining for Data-Efficient Person Re-identification
Siyu Chen, Dengjie Li, Lishuai Gao, Fan Liang, Wei Zhang, Lin Ma
http://arxiv.org/abs/2110.00549v1
• [cs.CV]Visual Cluster Separation Using High-Dimensional Sharpened Dimensionality Reduction
Youngjoo Kim, Alexandru C. Telea, Scott C. Trager, Jos B. T. M. Roerdink
http://arxiv.org/abs/2110.00317v1
• [cs.CY]Dynamic Emotions of Supporters and Opponents of Anti-racism Movement from George Floyd Protests
Jaihyun Park
http://arxiv.org/abs/2109.14269v2
• [cs.DB]LEMON: Explainable Entity Matching
Nils Barlaug
http://arxiv.org/abs/2110.00516v1
• [cs.DC]Characterizing Concurrency Mechanisms for NVIDIA GPUs under Deep Learning Workloads
Guin Gilman, Robert J. Walls
http://arxiv.org/abs/2110.00459v1
• [cs.DC]Towards Generalised Half-Duplex Systems
Cinzia Di Giusto, Loïc Germerie Guizouarn, Etienne Lozes
http://arxiv.org/abs/2110.00145v1
• [cs.DS]Online Primal-Dual Algorithms with Predictions for Packing Problems
Nguyen Kim Thang, Christoph Durr
http://arxiv.org/abs/2110.00391v1
• [cs.GR]GAN-based Reactive Motion Synthesis with Class-aware Discriminators for Human-human Interaction
Qianhui Men, Hubert P. H. Shum, Edmond S. L. Ho, Howard Leung
http://arxiv.org/abs/2110.00380v1
• [cs.GT]The Complexity of Learning Approval-Based Multiwinner Voting Rules
Ioannis Caragiannis, Karl Fehrs
http://arxiv.org/abs/2110.00254v1
• [cs.IR]Explainable Point-Based Document Visualizations
Primož Godec, Nikola Ðukić, Ajda Pretnar, Vesna Tanko, Lan Žagar, Blaž Zupan
http://arxiv.org/abs/2110.00462v1
• [cs.IR]SAM: A Self-adaptive Attention Module for Context-Aware Recommendation System
Jiabin Liu, Zheng Wei, Zhengpin Li, Xiaojun Mao, Jian Wang, Zhongyu Wei, Qi Zhang
http://arxiv.org/abs/2110.00452v1
• [cs.IT]A Unified Discretization Approach to Compute-Forward: From Discrete to Continuous Inputs
Adriano Pastore, Sung Hoon Lim, Chen Feng, Bobak Nazer, Michael Gastpar
http://arxiv.org/abs/2110.00132v1
• [cs.IT]Channel Estimation with Reconfigurable Intelligent Surfaces — A General Framework
A. Lee Swindlehurst, Gui Zhou, Rang Liu, Cunhua Pan, Ming Li
http://arxiv.org/abs/2110.00553v1
• [cs.IT]Predicting Flat-Fading Channels via Meta-Learned Closed-Form Linear Filters and Equilibrium Propagation
Sangwoo Park, Osvaldo Simeone
http://arxiv.org/abs/2110.00414v1
• [cs.IT]Reconfigurable Intelligent Surfaces Based on Single, Group, and Fully Connected Discrete-Value Impedance Networks
Matteo Nerini, Bruno Clerckx
http://arxiv.org/abs/2110.00077v1
• [cs.IT]Users’ ability to perceive misinformation: An information quality assessment approach
Aljaž Zrnec, Marko Poženel, Dejan Lavbič
http://arxiv.org/abs/2110.00230v1
• [cs.IT]Velocity-aware Antenna Selection in Predictor Antenna Systems
Hao Guo, Behrooz Makki, Tommy Svensson
http://arxiv.org/abs/2110.00064v1
• [cs.IT]What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligence
Qiao Lan, Dingzhu Wen, Zezhong Zhang, Qunsong Zeng, Xu Chen, Petar Popovski, Kaibin Huang
http://arxiv.org/abs/2110.00196v1
• [cs.LG]A survey on datasets for fairness-aware machine learning
Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi
http://arxiv.org/abs/2110.00530v1
• [cs.LG]An Ensemble-based Multi-Criteria Decision Making Method for COVID-19 Cough Classification
Nihad Karim Chowdhury, Muhammad Ashad Kabir, Md. Muhtadir Rahman
http://arxiv.org/abs/2110.00508v1
• [cs.LG]Applying Differential Privacy to Tensor Completion
Zheng Wei, Zhengpin Li, Xiaojun Mao, Jian Wang
http://arxiv.org/abs/2110.00539v1
• [cs.LG]Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference
François Rozet, Gilles Louppe
http://arxiv.org/abs/2110.00449v1
• [cs.LG]Batched Thompson Sampling
Cem Kalkanli, Ayfer Ozgur
http://arxiv.org/abs/2110.00202v1
• [cs.LG]Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning
Chi-Ken Lu, Patrick Shafto
http://arxiv.org/abs/2110.00568v1
• [cs.LG]DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networks
Ahmet F. Budak, Prateek Bhansali, Bo Liu, Nan Sun, David Z. Pan, Chandramouli V. Kashyap
http://arxiv.org/abs/2110.00211v1
• [cs.LG]Discovering Boundary Values of Feature-based Machine Learning Classifiers through Exploratory Datamorphic Testing
Hong Zhu, Ian Bayley
http://arxiv.org/abs/2110.00330v1
• [cs.LG]Divergence-Regularized Multi-Agent Actor-Critic
Kefan Su, Zongqing Lu
http://arxiv.org/abs/2110.00304v1
• [cs.LG]DualNet: Continual Learning, Fast and Slow
Quang Pham, Chenghao Liu, Steven Hoi
http://arxiv.org/abs/2110.00175v1
• [cs.LG]Empirical Quantitative Analysis of COVID-19 Forecasting Models
Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, Linda Petzold
http://arxiv.org/abs/2110.00174v1
• [cs.LG]Evaluating the fairness of fine-tuning strategies in self-supervised learning
Jason Ramapuram, Dan Busbridge, Russ Webb
http://arxiv.org/abs/2110.00538v1
• [cs.LG]Fed-LAMB: Layerwise and Dimensionwise Locally Adaptive Optimization Algorithm
Belhal Karimi, Xiaoyun Li, Ping Li
http://arxiv.org/abs/2110.00532v1
• [cs.LG]Inverse airfoil design method for generating varieties of smooth airfoils using conditional WGAN-gp
Kazuo Yonekura, Nozomu Miyamoto, Katsuyuki Suzuki
http://arxiv.org/abs/2110.00212v1
• [cs.LG]Iterative Teacher-Aware Learning
Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu
http://arxiv.org/abs/2110.00137v1
• [cs.LG]Large-scale ASR Domain Adaptation by Self- and Semi-supervised Learning
Dongseong Hwang, Ananya Misra, Zhouyuan Huo, Nikhil Siddhartha, Shefali Garg, David Qiu, Khe Chai Sim, Trevor Strohman, Françoise Beaufays, Yanzhang He
http://arxiv.org/abs/2110.00165v1
• [cs.LG]Leveraging power grid topology in machine learning assisted optimal power flow
Thomas Falconer, Letif Mones
http://arxiv.org/abs/2110.00306v1
• [cs.LG]Offline Reinforcement Learning with Reverse Model-based Imagination
Jianhao Wang, Wenzhe Li, Haozhe Jiang, Guangxiang Zhu, Siyuan Li, Chongjie Zhang
http://arxiv.org/abs/2110.00188v1
• [cs.LG]On the Importance of Gradients for Detecting Distributional Shifts in the Wild
Rui Huang, Andrew Geng, Yixuan Li
http://arxiv.org/abs/2110.00218v1
• [cs.LG]Open-set Classification of Common Waveforms Using A Deep Feed-forward Network and Binary Isolation Forest Models
C. Tanner Fredieu, Anthony Martone, R. Michael Buehrer
http://arxiv.org/abs/2110.00252v1
• [cs.LG]PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-Series
Futoon M. Abushaqra, Hao Xue, Yongli Ren, Flora D. Salim
http://arxiv.org/abs/2110.00071v1
• [cs.LG]Personalized Rehabilitation Robotics based on Online Learning Control
Samuel Tesfazgi, Armin Lederer, Johannes F. Kunz, Alejandro J. Ordóñez-Conejo, Sandra Hirche
http://arxiv.org/abs/2110.00481v1
• [cs.LG]Predicting COVID-19 Patient Shielding: A Comprehensive Study
Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer
http://arxiv.org/abs/2110.00183v1
• [cs.LG]Probabilistic Robust Autoencoders for Anomaly Detection
Yariv Aizenbud, Ofir Lindenbaum, Yuval Kluger
http://arxiv.org/abs/2110.00494v1
• [cs.LG]Q-Net: A Quantitative Susceptibility Mapping-based Deep Neural Network for Differential Diagnosis of Brain Iron Deposition in Hemochromatosis
Soheil Zabihi, Elahe Rahimian, Soumya Sharma, Sean K. Sethi, Sara Gharabaghi, Amir Asif, E. Mark Haacke, Mandar S. Jog, Arash Mohammadi
http://arxiv.org/abs/2110.00203v1
• [cs.LG]Rapid Assessments of Light-Duty Gasoline Vehicle Emissions Using On-Road Remote Sensing and Machine Learning
Yan Xia, Linhui Jiang, Lu Wang, Xue Chen, Jianjie Ye, Tangyan Hou, Liqiang Wang, Yibo Zhang, Mengying Li, Zhen Li, Zhe Song, Yaping Jiang, Weiping Liu, Pengfei Li, Daniel Rosenfeld, John H. Seinfeld, Shaocai Yu
http://arxiv.org/abs/2110.00260v1
• [cs.LG]Reconstruction for Powerful Graph Representations
Leonardo Cotta, Christopher Morris, Bruno Ribeiro
http://arxiv.org/abs/2110.00577v1
• [cs.LG]SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time Series
Jingwei Zuo, Karine Zeitouni, Yehia Taher
http://arxiv.org/abs/2110.00578v1
• [cs.LG]Scientific evidence extraction
Brandon Smock, Rohith Pesala, Robin Abraham
http://arxiv.org/abs/2110.00061v1
• [cs.LG]Stochastic Contrastive Learning
Jason Ramapuram, Dan BusBridge, Xavier Suau, Russ Webb
http://arxiv.org/abs/2110.00552v1
• [cs.LG]Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond
Risheng Liu, Yaohua Liu, Shangzhi Zeng, Jin Zhang
http://arxiv.org/abs/2110.00455v1
• [cs.LG]Tree in Tree: from Decision Trees to Decision Graphs
Bingzhao Zhu, Mahsa Shoaran
http://arxiv.org/abs/2110.00392v1
• [cs.LG]Two ways towards combining Sequential Neural Network and Statistical Methods to Improve the Prediction of Time Series
Jingwei Li
http://arxiv.org/abs/2110.00082v1
• [cs.LG]Update in Unit Gradient
Ching-Hsun. Tseng, Liu-Hsueh. Cheng, Shin-Jye. Lee, Xiaojun Zeng
http://arxiv.org/abs/2110.00199v1
• [cs.LG]UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis
Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
http://arxiv.org/abs/2110.00135v1
• [cs.MA]Decentralized Graph-Based Multi-Agent Reinforcement Learning Using Reward Machines
Jueming Hu, Zhe Xu, Weichang Wang, Guannan Qu, Yutian Pang, Yongming Liu
http://arxiv.org/abs/2110.00096v1
• [cs.MA]Emergence of Theory of Mind Collaboration in Multiagent Systems
Luyao Yuan, Zipeng Fu, Linqi Zhou, Kexin Yang, Song-Chun Zhu
http://arxiv.org/abs/2110.00121v1
• [cs.MA]Temporal Graphs and Temporal Network Characteristics for Bio-Inspired Networks During Optimization
N. DiBrita, K. Eledlebi, H. Hildmann, L. Culley, A. F. Isakovic
http://arxiv.org/abs/2110.00506v1
• [cs.NE]New Evolutionary Computation Models and their Applications to Machine Learning
Mihai Oltean
http://arxiv.org/abs/2110.00468v1
• [cs.NE]Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework
Zhuowen Zou, Haleh Alimohamadi, Farhad Imani, Yeseong Kim, Mohsen Imani
http://arxiv.org/abs/2110.00214v1
• [cs.NI]A Novel Simplified Swarm Optimization for Generalized Reliability Redundancy Allocation Problem
Zhenyao Liu, Jen-Hsuan Chen, Shi-Yi Tan, Wei-Chang Yeh
http://arxiv.org/abs/2110.00133v1
• [cs.NI]Automating Internet of Things Network Traffic Collection with Robotic Arm Interactions
Xi Jiang, Noah Apthorpe
http://arxiv.org/abs/2110.00060v1
• [cs.NI]Cellular traffic offloading via Opportunistic Networking with Reinforcement Learning
Lorenzo Valerio, Raffaele Bruno, Andrea Passarella
http://arxiv.org/abs/2110.00397v1
• [cs.RO]A Sufficient Condition for Convex Hull Property in General Convex Spatio-Temporal Corridors
Weize Zhang, Peyman Yadmellat, Zhiwei Gao
http://arxiv.org/abs/2110.00065v1
• [cs.RO]An Under-Actuated Whippletree Mechanism Gripper based on Multi-Objective Design Optimization with Auto-Tuned Weights
Yusuke Tanaka, Yuki Shirai, Zachary Lacey, Xuan Lin, Jane Liu, Dennis Hong
http://arxiv.org/abs/2110.00083v1
• [cs.RO]Batch Belief Trees for Motion Planning Under Uncertainty
Dongliang Zheng, Panagiotis Tsiotras
http://arxiv.org/abs/2110.00173v1
• [cs.RO]Dynamic Modeling and Simulation of a Four-wheel Skid-Steer Mobile Robot using Linear Graphs
Eric McCormick, Haoxiang Lang, Clarence W. de Silva
http://arxiv.org/abs/2110.00323v1
• [cs.RO]Dynamic Models of Spherical Parallel Robots for Model-Based Control Schemes
Ali Hassani, Abbas Bataleblu, S. A. Khalilpour, Hamid D. Taghirad, Philippe Cardou
http://arxiv.org/abs/2110.00491v1
• [cs.RO]From SLAM to Situational Awareness: Challenges and Survey
Hriday Bavle, Jose Luis Sanchez-Lopez, Eduardo F. Schmidt, Holger Voos
http://arxiv.org/abs/2110.00273v1
• [cs.RO]Guiding Evolutionary Strategies by Differentiable Robot Simulators
Vladislav Kurenkov, Bulat Maksudov
http://arxiv.org/abs/2110.00438v1
• [cs.RO]Improving Object Permanence using Agent Actions and Reasoning
Ying Siu Liang, Chen Zhang, Dongkyu Choi, Kenneth Kwok
http://arxiv.org/abs/2110.00238v1
• [cs.RO]Improving Object Permanence using Agent Actions and Reasoning
Ying Siu Liang, Chen Zhang, Dongkyu Choi, Kenneth Kwok
http://arxiv.org/abs/2
a85
110.00238v1
a85
110.00238v1)
• [cs.RO]Learning Reward Functions from Scale Feedback
Nils Wilde, Erdem Bıyık, Dorsa Sadigh, Stephen L. Smith
http://arxiv.org/abs/2110.00284v1
• [cs.RO]Learning from Demonstrations for Autonomous Soft-tissue Retraction
Ameya Pore, Eleonora Tagliabue, Marco Piccinelli, Diego Dall’Alba, Alicia Casals, Paolo Fiorini
http://arxiv.org/abs/2110.00336v1
• [cs.RO]Probabilistic Object Maps for Long-Term Robot Localization
Amanda Adkins, Joydeep Biswas
http://arxiv.org/abs/2110.00128v1
• [cs.RO]Real-Time Risk-Bounded Tube-Based Trajectory Safety Verification
Ashkan Jasour, Weiqiao Han, Brian Williams
http://arxiv.org/abs/2110.00233v1
• [cs.RO]Simulation-based multi-criteria comparison of mono-articular and bi-articular exoskeletons during walking with and without load
Ali KhalilianMotamed Bonab, Volkan Patoglu
http://arxiv.org/abs/2110.00062v1
• [cs.RO]Study of Signal Temporal Logic Robustness Metrics for Robotic Tasks Optimization
Akshay Dhonthi, Philipp Schillinger, Leonel Rozo, Daniele Nardi
http://arxiv.org/abs/2110.00339v1
• [cs.RO]Topologically-Informed Atlas Learning
Thomas Cohn, Nikhil Devraj, Odest Chadwicke Jenkins
http://arxiv.org/abs/2110.00429v1
• [cs.RO]Validating Robotics Simulators on Real World Impacts
Brian Acosta, William Yang, Michael Posa
http://arxiv.org/abs/2110.00541v1
• [cs.RO]Vision-Only Robot Navigation in a Neural Radiance World
Michal Adamkiewicz, Timothy Chen, Adam Caccavale, Rachel Gardner, Preston Culbertson, Jeannette Bohg, Mac Schwager
http://arxiv.org/abs/2110.00168v1
• [cs.SI]#ContextMatters: Advantages and Limitations of Using Machine Learning to Support Women in Politics
Jacqueline Comer, Sam Work, Kory W Mathewson, Lana Cuthbertson, Kasey Machin
http://arxiv.org/abs/2110.00116v1
• [cs.SI]Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences
Meng Liu, Yong Liu
http://arxiv.org/abs/2110.00267v1
• [cs.SI]Inequality and Inequity in Network-based Ranking and Recommendation Algorithms
Lisette Espín-Noboa, Claudia Wagner, Markus Strohmaier, Fariba Karimi
http://arxiv.org/abs/2110.00072v1
• [cs.SI]Unsupervised Belief Representation Learning in Polarized Networks with Information-Theoretic Variational Graph Auto-Encoders
Jinning Li, Huajie Shao, Dachun Sun, Ruijie Wang, Jinyang, Li, Shengzhong, Liu, Hanghang Tong, Tarek Abdelzaher
http://arxiv.org/abs/2110.00210v1
• [cs.SI]What Happened in Social Media during the 2020 BLM Movement? An Analysis of Deleted and Suspended Users in Twitter
Cagri Toraman, Furkan Şahinuç, Eyup Halit Yilmaz
http://arxiv.org/abs/2110.00070v1
• [econ.EM]Relative Contagiousness of Emerging Virus Variants: An Analysis of SARS-CoV-2 Alpha and Delta Variants
Peter Reinhard Hansen
http://arxiv.org/abs/2110.00533v1
• [eess.IV]A Graph-theoretic Algorithm for Small Bowel Path Tracking in CT Scans
Seung Yeon Shin, Sungwon Lee, Ronald M. Summers
http://arxiv.org/abs/2110.00466v1
• [eess.IV]DCT based Fusion of Variable Exposure Images for HDRI
Vivek Ramakarishnan, Dnyaneshwar Jageshwar Pete
http://arxiv.org/abs/2110.00312v1
• [eess.IV]DeepMCAT: Large-Scale Deep Clustering for Medical Image Categorization
Turkay Kart, Wenjia Bai, Ben Glocker, Daniel Rueckert
http://arxiv.org/abs/2110.00109v1
• [eess.IV]Development of the algorithm for differentiating bone metastases and trauma of the ribs in bone scintigraphy and demonstration of visual evidence of the algorithm — Using only anterior bone scan view of thorax
Shigeaki Higashiyama, Yukino Ohta, Yutaka Katayama, Atsushi Yoshida, Joji Kawabe
http://arxiv.org/abs/2110.00130v1
• [eess.IV]Learning of Inter-Label Geometric Relationships Using Self-Supervised Learning: Application To Gleason Grade Segmentation
Dwarikanath Mahapatra
http://arxiv.org/abs/2110.00404v1
• [eess.IV]Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising
Arjun D Desai, Batu M Ozturkler, Christopher M Sandino, Shreyas Vasanawala, Brian A Hargreaves, Christopher M Re, John M Pauly, Akshay S Chaudhari
http://arxiv.org/abs/2110.00075v1
• [eess.IV]Optic Disc Segmentation using Disk-Centered Patch Augmentation
Saeid Motevali, Aashis Khanal, Rolando Estrada
http://arxiv.org/abs/2110.00512v1
• [eess.IV]Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration
Mikael Le Pendu, Christine Guillemot
http://arxiv.org/abs/2110.00493v1
• [eess.SP]A Bayesian approach to location estimation of mobile devices from mobile network operator data
Martijn Tennekes, Yvonne A. P. M. Gootzen
http://arxiv.org/abs/2110.00439v1
• [eess.SP]A survey on active noise control techniques — Part I: Linear systems
Lu Lu, Kai-Li Yin, Rodrigo C. de Lamare, Zongsheng Zheng, Yi Yu, Xiaomin Yang, Badong Chen
http://arxiv.org/abs/2110.00531v1
• [eess.SP]Improving Load Forecast in Energy Markets During COVID-19
Ziyun Wang, Hao Wang
http://arxiv.org/abs/2110.00181v1
• [eess.SP]Learn to Communicate with Neural Calibration: Scalability and Generalization
Yifan Ma, Yifei Shen, Xianghao Yu, Jun Zhang, S. H. Song, Khaled B. Letaief
http://arxiv.org/abs/2110.00272v1
• [eess.SY]Error-free approximation of explicit linear MPC through lattice piecewise affine expression
Jun Xu
http://arxiv.org/abs/2110.00201v1
• [eess.SY]RLO-MPC: Robust Learning-Based Output Feedback MPC for Improving the Performance of Uncertain Systems in Iterative Tasks
Lukas Brunke, Siqi Zhou, Angela P. Schoellig
http://arxiv.org/abs/2110.00542v1
• [math.OC]Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation
Florian Bernard, Daniel Cremers, Johan Thunberg
http://arxiv.org/abs/2110.00053v1
• [math.ST]Componentwise Equivariant Estimation of Order Restricted Location and Scale Parameters In Bivariate Models: A Unified Study
Naresh Garg, Neeraj Misra
http://arxiv.org/abs/2109.14997v2
• [math.ST]Inference on the maximal rank of time-varying covariance matrices using high-frequency data
Markus Reiß, Lars Winkelmann
http://arxiv.org/abs/2110.00363v1
• [physics.comp-ph]Closed-form discovery of structural errors in models of chaotic systems by integrating Bayesian sparse regression and data assimilation
Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh
http://arxiv.org/abs/2110.00546v1
• [stat.AP]A Riemannian Approach to Multivariate Geostatistical Modeling
Alvaro Riquelme
http://arxiv.org/abs/2109.14550v2
• [stat.AP]Confidence intervals for efficiencies in particle physics experiments
Hans Dembinski, Michael Schmelling
http://arxiv.org/abs/2110.00294v1
• [stat.AP]State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting
Joseph de Vilmarest, Yannig Goude
http://arxiv.org/abs/2110.00334v1
• [stat.CO]ebnm: An R Package for Solving the Empirical Bayes Normal Means Problem Using a Variety of Prior Families
Jason Willwerscheid, Matthew Stephens
http://arxiv.org/abs/2110.00152v1
• [stat.ME]A Review and Critique of Auxiliary Information-Based Process Monitoring Methods
Nesma A. Saleh, Mahmoud A. Mahmoud, William H. Woodall, Sven Knoth
http://arxiv.org/abs/2110.00198v1
• [stat.ME]Censored autoregressive regression models with Student- innovations
Katherine A. L. Valeriano, Fernanda L. Schumacher, Christian E. Galarza, Larissa A. Matos
http://arxiv.org/abs/2110.00224v1
• [stat.ME]Comparing Sequential Forecasters
Yo Joong Choe, Aaditya Ramdas
http://arxiv.org/abs/2110.00115v1
• [stat.ME]Confounder importance learning for treatment effect inference
Miquel Torrens-i-Dinarès, Omiros Papaspiliopoulos, David Rossell
http://arxiv.org/abs/2110.00314v1
• [stat.ME]Dimension Reduction and Data Visualization for Fréchet Regression
Qi Zhang, Lingzhou Xue, Bing Li
http://arxiv.org/abs/2110.00467v1
• [stat.ME]Regression-based estimation of heterogeneous treatment effects when extending inferences from a randomized trial to a target population
Sarah E Robertson, Jon A Steingrimsson, Issa J Dahabreh
http://arxiv.org/abs/2110.00107v1
• [stat.ML]A Cramér Distance perspective on Non-crossing Quantile Regression in Distributional Reinforcement Learning
Alix Lhéritier, Nicolas Bondoux
http://arxiv.org/abs/2110.00535v1
• [stat.ML]Lagrangian Inference for Ranking Problems
Yue Liu, Ethan X. Fang, Junwei Lu
http://arxiv.org/abs/2110.00151v1
• [stat.ML]Powerpropagation: A sparsity inducing weight reparameterisation
Jonathan Schwarz, Siddhant M. Jayakumar, Razvan Pascanu, Peter E. Latham, Yee Whye Teh
http://arxiv.org/abs/2110.00296v1
• [stat.ML]Predicting Consumer Purchasing Decision in The Online Food Delivery Industry
Batool Madani, Hussam Alshraideh
http://arxiv.org/abs/2110.00502v1
• [stat.ML]Score-Based Generative Classifiers
Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
http://arxiv.org/abs/2110.00473v1
• [stat.ML]Sim and Real: Better Together
Shirli Di Castro Shashua, Dotan Di~Castro, Shie Mannor
http://arxiv.org/abs/2110.00445v1
• [stat.ML]Smooth Normalizing Flows
Jonas Köhler, Andreas Krämer, Frank Noé
http://arxiv.org/abs/2110.00351v1
• [stat.ML]TyXe: Pyro-based Bayesian neural nets for Pytorch
Hippolyt Ritter, Theofanis Karaletsos
http://arxiv.org/abs/2110.00276v1
• [stat.ML]Weight Vector Tuning and Asymptotic Analysis of Binary Linear Classifiers
Lama B. Niyazi, Abla Kammoun, Hayssam Dahrouj, Mohamed-Slim Alouini, Tareq Al-Naffouri
http://arxiv.org/abs/2110.00567v1