astro-ph.CO - 宇宙学和天体物理学
    cs.AI - 人工智能
    cs.CE - 计算工程、 金融和科学
    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.DB - 数据库
    cs.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    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.SE - 软件工程
    cs.SI - 社交网络与信息网络
    econ.EM - 计量经济学
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    eess.SY - 系统和控制
    math-ph - 数学物理
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    physics.comp-ph - 计算物理学
    physics.flu-dyn - 流体动力学
    physics.plasm-ph - 等离子体物理
    q-bio.QM - 定量方法
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [astro-ph.CO]Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation
    • [astro-ph.CO]Inferring halo masses with Graph Neural Networks
    • [cs.AI]A first approach to closeness distributions
    • [cs.AI]Accounting for Gaussian Process Imprecision in Bayesian Optimization
    • [cs.AI]An Empirical Study of Finding Similar Exercises
    • [cs.AI]Causal policy ranking
    • [cs.AI]From Convolutions towards Spikes: The Environmental Metric that the Community currently Misses
    • [cs.AI]Improving Learning from Demonstrations by Learning from Experience
    • [cs.AI]JMSNAS: Joint Model Split and Neural Architecture Search for Learning over Mobile Edge Networks
    • [cs.AI]Neural Class Expression Synthesis
    • [cs.AI]Self-encoding Barnacle Mating Optimizer Algorithm for Manpower Scheduling in Flow Shop
    • [cs.AI]The Partially Observable History Process
    • [cs.AI]Uncertainty-Aware Multiple Instance Learning fromLarge-Scale Long Time Series Data
    • [cs.AI]Will We Trust What We Don’t Understand? Impact of Model Interpretability and Outcome Feedback on Trust in AI
    • [cs.CE]Machine Learning-Based Assessment of Energy Behavior of RC Shear Walls
    • [cs.CL]A Comparative Study on Transfer Learning and Distance Metrics in Semantic Clustering over the COVID-19 Tweets
    • [cs.CL]Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair
    • [cs.CL]Assessing gender bias in medical and scientific masked language models with StereoSet
    • [cs.CL]CCA-MDD: A Coupled Cross-Attention based Framework for Streaming Mispronunciation detection and diagnosis
    • [cs.CL]CVSS-BERT: Explainable Natural Language Processing to Determine the Severity of a Computer Security Vulnerability from its Description
    • [cs.CL]Coral: An Approach for Conversational Agents in Mental Health Applications
    • [cs.CL]DataCLUE: A Benchmark Suite for Data-centric NLP
    • [cs.CL]Document AI: Benchmarks, Models and Applications
    • [cs.CL]Exploring Story Generation with Multi-task Objectives in Variational Autoencoders
    • [cs.CL]Few-Shot Self-Rationalization with Natural Language Prompts
    • [cs.CL]Generative Pre-Trained Transformer for Design Concept Generation: An Exploration
    • [cs.CL]Improving the robustness and accuracy of biomedical language models through adversarial training
    • [cs.CL]Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition
    • [cs.CL]Joint Unsupervised and Supervised Training for Multilingual ASR
    • [cs.CL]Literature-Augmented Clinical Outcome Prediction
    • [cs.CL]Meeting Summarization with Pre-training and Clustering Methods
    • [cs.CL]Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts
    • [cs.CL]Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity
    • [cs.CL]NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21
    • [cs.CL]STAMP 4 NLP — An Agile Framework for Rapid Quality-Driven NLP Applications Development
    • [cs.CL]The role of attraction-repulsion dynamics in simulating the emergence of inflectional class systems
    • [cs.CL]WikiContradiction: Detecting Self-Contradiction Articles on Wikipedia
    • [cs.CR]An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences
    • [cs.CV]今日学术视野(2021.11.18) - 图1 for Interaction Prediction
    • [cs.CV]A Data-Driven Approach for Linear and Nonlinear Damage Detection Using Variational Mode Decomposition and GARCH Model
    • [cs.CV]Bengali Handwritten Grapheme Classification: Deep Learning Approach
    • [cs.CV]Beyond Mono to Binaural: Generating Binaural Audio from Mono Audio with Depth and Cross Modal Attention
    • [cs.CV]CAR — Cityscapes Attributes Recognition A Multi-category Attributes Dataset for Autonomous Vehicles
    • [cs.CV]Choose Settings Carefully: Comparing Action Unit detection at Different Settings Using a Large-Scale Dataset
    • [cs.CV]Coarse-to-fine Animal Pose and Shape Estimation
    • [cs.CV]Consistent Semantic Attacks on Optical Flow
    • [cs.CV]DFC: Deep Feature Consistency for Robust Point Cloud Registration
    • [cs.CV]DRINet++: Efficient Voxel-as-point Point Cloud Segmentation
    • [cs.CV]Data Augmentation using Random Image Cropping for High-resolution Virtual Try-On (VITON-CROP)
    • [cs.CV]Delta-GAN-Encoder: Encoding Semantic Changes for Explicit Image Editing, using Few Synthetic Samples
    • [cs.CV]Diversified Multi-prototype Representation for Semi-supervised Segmentation
    • [cs.CV]Enabling equivariance for arbitrary Lie groups
    • [cs.CV]FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows
    • [cs.CV]Fight Detection from Still Images in the Wild
    • [cs.CV]IKEA Object State Dataset: A 6DoF object pose estimation dataset and benchmark for multi-state assembly objects
    • [cs.CV]INTERN: A New Learning Paradigm Towards General Vision
    • [cs.CV]Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding
    • [cs.CV]Keypoint Message Passing for Video-based Person Re-Identification
    • [cs.CV]LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations
    • [cs.CV]Language bias in Visual Question Answering: A Survey and Taxonomy
    • [cs.CV]Learnable Locality-Sensitive Hashing for Video Anomaly Detection
    • [cs.CV]Learning Intrinsic Images for Clothing
    • [cs.CV]NENet: Monocular Depth Estimation via Neural Ensembles
    • [cs.CV]Pansharpening by convolutional neural networks in the full resolution framework
    • [cs.CV]Point detection through multi-instance deep heatmap regression for sutures in endoscopy
    • [cs.CV]Pose Recognition in the Wild: Animal pose estimation using Agglomerative Clustering and Contrastive Learning
    • [cs.CV]Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation
    • [cs.CV]Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion
    • [cs.CV]SEnSeI: A Deep Learning Module for Creating Sensor Independent Cloud Masks
    • [cs.CV]Self-supervised High-fidelity and Re-renderable 3D Facial Reconstruction from a Single Image
    • [cs.CV]SequentialPointNet: A strong parallelized point cloud sequence network for 3D action recognition
    • [cs.CV]ShapeY: Measuring Shape Recognition Capacity Using Nearest Neighbor Matching
    • [cs.CV]Single Image Object Counting and Localizing using Active-Learning
    • [cs.CV]Synthetic Unknown Class Learning for Learning Unknowns
    • [cs.CV]TRIG: Transformer-Based Text Recognizer with Initial Embedding Guidance
    • [cs.CV]Two-dimensional Deep Regression for Early Yield Prediction of Winter Wheat
    • [cs.CV]UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection
    • [cs.CV]Weakly-supervised fire segmentation by visualizing intermediate CNN layers
    • [cs.CV]Which CNNs and Training Settings to Choose for Action Unit Detection? A Study Based on a Large-Scale Dataset
    • [cs.DB]Highly Efficient Indexing Scheme for k-Dominant Skyline Processing over Uncertain Data Streams
    • [cs.DC]Online Self-Evolving Anomaly Detection in Cloud Computing Environments
    • [cs.DC]Project CGX: Scalable Deep Learning on Commodity GPUs
    • [cs.DC]Quo Vadis MPI RMA? Towards a More Efficient Use of MPI One-Sided Communication
    • [cs.DC]Saath: Speeding up CoFlows by Exploiting the Spatial Dimension
    • [cs.DC]Self-Stabilization and Byzantine Tolerance for Maximal Independent Set
    • [cs.DC]Task allocation for decentralized training in heterogeneous environment
    • [cs.DL]Patent Data for Engineering Design: A Review
    • [cs.HC]Words of Wisdom: Representational Harms in Learning From AI Communication
    • [cs.IR]Pre-training Graph Neural Network for Cross Domain Recommendation
    • [cs.IR]QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback
    • [cs.IR]Utilizing Textual Reviews in Latent Factor Models for Recommender Systems
    • [cs.IT]A Markov Chain Approach for Myopic Multi-hop Relaying: Outage and Diversity Analysis
    • [cs.IT]A fixed latency ORBGRAND decoder architecture with LUT-aided error-pattern scheduling
    • [cs.IT]Continuous-Aperture MIMO for Electromagnetic Information Theory
    • [cs.IT]Dense Circulant Lattices From Nonlinear Systems
    • [cs.IT]Faster-than-Nyquist Asynchronous NOMA Outperforms Synchronous NOMA
    • [cs.IT]Faster-than-Nyquist Signaling for MIMO Communications
    • [cs.IT]Generalization Bounds and Algorithms for Learning to Communicate over Additive Noise Channels
    • [cs.IT]Hybrid Beam Alignment for Multi-Path Channels: A Group Testing Viewpoint
    • [cs.IT]Hybrid Reflection Modulation
    • [cs.IT]Introduction to Set Shaping Theory
    • [cs.IT]On Reverse Elastic Channels and the Asymmetry of Commitment Capacity under Channel Elasticity
    • [cs.IT]On The Number of Different Entries in Involutory MDS Matrices over Finite Fields of Characteristic Two
    • [cs.LG]A Unified and Fast Interpretable Model for Predictive Analytics
    • [cs.LG]Assessing Deep Neural Networks as Probability Estimators
    • [cs.LG]Automatically detecting anomalous exoplanet transits
    • [cs.LG]Causal Effect Variational Autoencoder with Uniform Treatment
    • [cs.LG]Comparative Analysis of Machine Learning Models for Predicting Travel Time
    • [cs.LG]Deep Distilling: automated code generation using explainable deep learning
    • [cs.LG]Exploiting Action Impact Regularity and Partially Known Models for Offline Reinforcement Learning
    • [cs.LG]Fairness-aware Online Price Discrimination with Nonparametric Demand Models
    • [cs.LG]FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
    • [cs.LG]FedCostWAvg: A new averaging for better Federated Learning
    • [cs.LG]Free Will Belief as a consequence of Model-based Reinforcement Learning
    • [cs.LG]Grounding Psychological Shape Space in Convolutional Neural Networks
    • [cs.LG]HADFL: Heterogeneity-aware Decentralized Federated Learning Framework
    • [cs.LG]HiRID-ICU-Benchmark — A Comprehensive Machine Learning Benchmark on High-resolution ICU Data
    • [cs.LG]Inference-Time Personalized Federated Learning
    • [cs.LG]Interpretable and Fair Boolean Rule Sets via Column Generation
    • [cs.LG]Interpreting Language Models Through Knowledge Graph Extraction
    • [cs.LG]Inverse-Weighted Survival Games
    • [cs.LG]Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
    • [cs.LG]Learning Augmentation Distributions using Transformed Risk Minimization
    • [cs.LG]Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection
    • [cs.LG]Machine Learning and Ensemble Approach Onto Predicting Heart Disease
    • [cs.LG]Machine Learning-Assisted Analysis of Small Angle X-ray Scattering
    • [cs.LG]Margin-Independent Online Multiclass Learning via Convex Geometry
    • [cs.LG]Mathematical Models for Local Sensing Hashes
    • [cs.LG]MoRe-Fi: Motion-robust and Fine-grained Respiration Monitoring via Deep-Learning UWB Radar
    • [cs.LG]ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control
    • [cs.LG]Modular Networks Prevent Catastrophic Interference in Model-Based Multi-Task Reinforcement Learning
    • [cs.LG]Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection
    • [cs.LG]Natural Gradient Variational Inference with Gaussian Mixture Models
    • [cs.LG]Neural networks with linear threshold activations: structure and algorithms
    • [cs.LG]Neuron-based Pruning of Deep Neural Networks with Better Generalization using Kronecker Factored Curvature Approximation
    • [cs.LG]Non-separable Spatio-temporal Graph Kernels via SPDEs
    • [cs.LG]Off-Policy Actor-Critic with Emphatic Weightings
    • [cs.LG]On Bock’s Conjecture Regarding the Adam Optimizer
    • [cs.LG]On Effective Scheduling of Model-based Reinforcement Learning
    • [cs.LG]Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters
    • [cs.LG]Phase function estimation from a diffuse optical image via deep learning
    • [cs.LG]Polymatrix Competitive Gradient Descent
    • [cs.LG]Rank-Regret Minimization
    • [cs.LG]Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills
    • [cs.LG]Reshaping Smart Energy Transition: An analysis of human-building interactions in Qatar Using Machine Learning Techniques
    • [cs.LG]Robust recovery for stochastic block models
    • [cs.LG]Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks
    • [cs.LG]Selective Ensembles for Consistent Predictions
    • [cs.LG]Solving Linear Algebra by Program Synthesis
    • [cs.LG]Solving Probability and Statistics Problems by Program Synthesis
    • [cs.LG]Switching Recurrent Kalman Networks
    • [cs.LG]Thoughts on the Consistency between Ricci Flow and Neural Network Behavior
    • [cs.LG]TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation
    • [cs.LG]Towards Generating Real-World Time Series Data
    • [cs.LG]VisualEnv: visual Gym environments with Blender
    • [cs.LG]Wyner-Ziv Gradient Compression for Federated Learning
    • [cs.NE]A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting
    • [cs.NI]CLARA: A Constrained Reinforcement Learning Based Resource Allocation Framework for Network Slicing
    • [cs.NI]Common Language for Goal-Oriented Semantic Communications: A Curriculum Learning Framework
    • [cs.NI]HyperNAT: Scaling Up Network AddressTranslation with SmartNICs for Clouds
    • [cs.NI]Learning Robust Scheduling with Search and Attention
    • [cs.RO]2.5D Vehicle Odometry Estimation
    • [cs.RO]Active Vapor-Based Robotic Wiper
    • [cs.RO]Analysis of Model-Free Reinforcement Learning Control Schemes on self-balancing Wheeled Extendible System
    • [cs.RO]GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving
    • [cs.RO]Hierarchical Topometric Representation of 3D Robotic Maps
    • [cs.RO]Joint State and Input Estimation of Agent Based on Recursive Kalman Filter Given Prior Knowledge
    • [cs.RO]Learning to Navigate in a VUCA Environment: Hierarchical Multi-expert Approach
    • [cs.RO]Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing
    • [cs.RO]Towards Real-Time Monocular Depth Estimation for Robotics: A Survey
    • [cs.RO]Virtual Reality for Synergistic Surgical Training and Data Generation
    • [cs.SE]Is CADP an Applicable Formal Method?
    • [cs.SI]Analysis of 5G academic Network based on graph representation learning method
    • [cs.SI]Improving the performance of reputation evaluating by combining the structure of network and nonlinear recovery
    • [cs.SI]Local News Online and COVID in the U.S.: Relationships among Coverage, Cases, Deaths, and Audience
    • [econ.EM]Designing Representative and Balanced Experiments by Local Randomization
    • [econ.EM]Revisiting C.S.Peirce’s Experiment: 150 Years Later
    • [eess.AS]Attention-based Multi-hypothesis Fusion for Speech Summarization
    • [eess.AS]Single-channel speech separation using Soft-minimum Permutation Invariant Training
    • [eess.IV]A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution
    • [eess.IV]A layer-stress learning framework universally augments deep neural network tasks
    • [eess.IV]Advancement of Deep Learning in Pneumonia and Covid-19 Classification and Localization: A Qualitative and Quantitative Analysis
    • [eess.IV]Disparities in Dermatology AI: Assessments Using Diverse Clinical Images
    • [eess.IV]Image-specific Convolutional Kernel Modulation for Single Image Super-resolution
    • [eess.IV]Online Meta Adaptation for Variable-Rate Learned Image Compression
    • [eess.IV]Solving Inverse Problems in Medical Imaging with Score-Based Generative Models
    • [eess.SP]Blockage Prediction Using Wireless Signatures: Deep Learning Enables Real-World Demonstration
    • [eess.SP]Deep Diffusion Models for Robust Channel Estimation
    • [eess.SP]Human-error-potential Estimation based on Wearable Biometric Sensors
    • [eess.SY]Graph neural network-based fault diagnosis: a review
    • [math-ph]Second-order statistics of fermionic Gaussian states
    • [math.OC]Data-Driven Inpatient Bed Assignment Using the P Model
    • [math.OC]Learning Optimal Control with Stochastic Models of Hamiltonian Dynamics
    • [math.OC]Multiclass Optimal Classification Trees with SVM-splits
    • [math.OC]Stochastic Extragradient: General Analysis and Improved Rates
    • [math.PR]Prediction theory in continuous time
    • [math.ST]On Adaptive Confidence Sets for the Wasserstein Distances
    • [math.ST]Properties of linear spectral statistics of frequency-smoothed estimated spectral coherence matrix of high-dimensional Gaussian time series
    • [math.ST]Quantification of fracture roughness by change probabilities and Hurst exponents
    • [physics.comp-ph]Normalizing flows for atomic solids
    • [physics.flu-dyn]Global Sensitivity Analysis of Four Chamber Heart Hemodynamics Using Surrogate Models
    • [physics.plasm-ph]Tracking Blobs in the Turbulent Edge Plasma of Tokamak Fusion Reactors
    • [q-bio.QM]Code-free development and deployment of deep segmentation models for digital pathology
    • [quant-ph]Tensor network to learn the wavefunction of data
    • [stat.AP]An Empirical Evaluation of the Impact of New York’s Bail Reform on Crime Using Synthetic Controls
    • [stat.AP]Bayesian inference of the climbing grade scale
    • [stat.AP]Bayesian, frequentist and fiducial intervals for the difference between two binomial proportions
    • [stat.AP]Hierarchical transfer learning with applications for electricity load forecasting
    • [stat.AP]Joint Estimation of Extreme Precipitation at Different Spatial Scales through Mixture Modelling
    • [stat.AP]Neuro-Hotnet: A Graph Theoretic Approach for Brain FC Estimation
    • [stat.AP]Regional Topics in British Grocery Retail Transactions
    • [stat.ME]Change-point detection for density sequence extracted from SHM data, with application to distributional information break diagnosis encountered in structural condition assessment
    • [stat.ME]Inference for extreme spatial temperature events in a changing climate with application to Ireland
    • [stat.ME]Multi-Parameter Regression Survival Modelling with Random Effects
    • [stat.ME]Sequential Unequal Probability Sampling For Stream Population
    • [stat.ME]Simultaneous inference of correlated marginal tests using intersection-union or union-intersection test principle
    • [stat.ME]Translating questions to estimands in randomized clinical trials with intercurrent events
    • [stat.ML]An adaptive dimension reduction algorithm for latent variables of variational autoencoder
    • [stat.ML]Bayesian Optimization for Cascade-type Multi-stage Processes
    • [stat.ML]Covariate Shift in High-Dimensional Random Feature Regression
    • [stat.ML]Distribution Compression in Near-Linear Time
    • [stat.ML]Learning with convolution and pooling operations in kernel methods
    • [stat.ML]SStaGCN: Simplified stacking based graph convolutional networks
    • [stat.ML]Sequential Community Mode Estimation
    • [stat.ML]Sparse Graph Learning Under Laplacian-Related Constraints

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

    • [astro-ph.CO]Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation
    Alex Cole, Benjamin Kurt Miller, Samuel J. Witte, Maxwell X. Cai, Meiert W. Grootes, Francesco Nattino, Christoph Weniger
    http://arxiv.org/abs/2111.08030v1

    • [astro-ph.CO]Inferring halo masses with Graph Neural Networks
    Pablo Villanueva-Domingo, Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel, Federico Marinacci, David N. Spergel, Lars Hernquist, Mark Vogelsberger, Romeel Dave, Desika Narayanan
    http://arxiv.org/abs/2111.08683v1

    • [cs.AI]A first approach to closeness distributions
    Jesus Cerquides
    http://arxiv.org/abs/2111.08357v1

    • [cs.AI]Accounting for Gaussian Process Imprecision in Bayesian Optimization
    Julian Rodemann, Thomas Augustin
    http://arxiv.org/abs/2111.08299v1

    • [cs.AI]An Empirical Study of Finding Similar Exercises
    Tongwen Huang, Xihua Li
    http://arxiv.org/abs/2111.08322v1

    • [cs.AI]Causal policy ranking
    Daniel McNamee, Hana Chockler
    http://arxiv.org/abs/2111.08415v1

    • [cs.AI]From Convolutions towards Spikes: The Environmental Metric that the Community currently Misses
    Aviral Chharia, Shivu Chauhan, Rahul Upadhyay, Vinay Kumar
    http://arxiv.org/abs/2111.08361v1

    • [cs.AI]Improving Learning from Demonstrations by Learning from Experience
    Haofeng Liu, Yiwen Chen, Jiayi Tan, Marcelo H Ang Jr
    http://arxiv.org/abs/2111.08156v1

    • [cs.AI]JMSNAS: Joint Model Split and Neural Architecture Search for Learning over Mobile Edge Networks
    Yuqing Tian, Zhaoyang Zhang, Zhaohui Yang, Qianqian Yang
    http://arxiv.org/abs/2111.08206v1

    • [cs.AI]Neural Class Expression Synthesis
    N’Dah Jean Kouagou, Stefan Heindorf, Caglar Demir, Axel-Cyrille Ngonga Ngomo
    http://arxiv.org/abs/2111.08486v1

    • [cs.AI]Self-encoding Barnacle Mating Optimizer Algorithm for Manpower Scheduling in Flow Shop
    Shuyun Luo, Wushuang Wang, Mengyuan Fang, Weiqiang Xu
    http://arxiv.org/abs/2111.08246v1

    • [cs.AI]The Partially Observable History Process
    Dustin Morrill, Amy R. Greenwald, Michael Bowling
    http://arxiv.org/abs/2111.08102v1

    • [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/2111.08625v1

    • [cs.AI]Will We Trust What We Don’t Understand? Impact of Model Interpretability and Outcome Feedback on Trust in AI
    Daehwan Ahn, Abdullah Almaatouq, Monisha Gulabani, Kartik Hosanagar
    http://arxiv.org/abs/2111.08222v1

    • [cs.CE]Machine Learning-Based Assessment of Energy Behavior of RC Shear Walls
    Berkay Topaloglu, Gulsen Taskin Kaya, Fatih Sutcu, Zeynep Tuna Deger
    http://arxiv.org/abs/2111.08295v1

    • [cs.CL]A Comparative Study on Transfer Learning and Distance Metrics in Semantic Clustering over the COVID-19 Tweets
    Elnaz Zafarani-Moattar, Mohammad Reza Kangavari, Amir Masoud Rahmani
    http://arxiv.org/abs/2111.08658v1

    • [cs.CL]Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair
    Jason Phang, Angelica Chen, William Huang, Samuel R. Bowman
    http://arxiv.org/abs/2111.08181v1

    • [cs.CL]Assessing gender bias in medical and scientific masked language models with StereoSet
    Robert Robinson
    http://arxiv.org/abs/2111.08088v1

    • [cs.CL]CCA-MDD: A Coupled Cross-Attention based Framework for Streaming Mispronunciation detection and diagnosis
    Nianzu Zheng, Liqun Deng, Wenyong Huang, Yu Ting Yeung, Baohua Xu, Yuanyuan Guo, Yasheng Wang, Xin Jiang, Qun Liu
    http://arxiv.org/abs/2111.08191v1

    • [cs.CL]CVSS-BERT: Explainable Natural Language Processing to Determine the Severity of a Computer Security Vulnerability from its Description
    Mustafizur Shahid, Hervé Debar
    http://arxiv.org/abs/2111.08510v1

    • [cs.CL]Coral: An Approach for Conversational Agents in Mental Health Applications
    Harsh Sakhrani, Saloni Parekh, Shubham Mahajan
    http://arxiv.org/abs/2111.08545v1

    • [cs.CL]DataCLUE: A Benchmark Suite for Data-centric NLP
    Liang Xu, Jiacheng Liu, Xiang Pan, Xiaojing Lu, Xiaofeng Hou
    http://arxiv.org/abs/2111.08647v1

    • [cs.CL]Document AI: Benchmarks, Models and Applications
    Lei Cui, Yiheng Xu, Tengchao Lv, Furu Wei
    http://arxiv.org/abs/2111.08609v1

    • [cs.CL]Exploring Story Generation with Multi-task Objectives in Variational Autoencoders
    Zhuohan Xie, Trevor Cohn, Jey Han Lau
    http://arxiv.org/abs/2111.08133v1

    • [cs.CL]Few-Shot Self-Rationalization with Natural Language Prompts
    Ana Marasović, Iz Beltagy, Doug Downey, Matthew E. Peters
    http://arxiv.org/abs/2111.08284v1

    • [cs.CL]Generative Pre-Trained Transformer for Design Concept Generation: An Exploration
    Qihao Zhu, Jianxi Luo
    http://arxiv.org/abs/2111.08489v1

    • [cs.CL]Improving the robustness and accuracy of biomedical language models through adversarial training
    Milad Moradi, Matthias Samwald
    http://arxiv.org/abs/2111.08529v1

    • [cs.CL]Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition
    Yi-Chang Chen, Chun-Yen Cheng, Ming-Chieh Sung, Yi-Ren Yeh
    http://arxiv.org/abs/2111.08400v1

    • [cs.CL]Joint Unsupervised and Supervised Training for Multilingual ASR
    Junwen Bai, Bo Li, Yu Zhang, Ankur Bapna, Nikhil Siddhartha, Khe Chai Sim, Tara N. Sainath
    http://arxiv.org/abs/2111.08137v1

    • [cs.CL]Literature-Augmented Clinical Outcome Prediction
    Aakanksha Naik, Sravanthi Parasa, Sergey Feldman, Lucy Lu Wang, Tom Hope
    http://arxiv.org/abs/2111.08374v1

    • [cs.CL]Meeting Summarization with Pre-training and Clustering Methods
    Andras Huebner, Wei Ji, Xiang Xiao
    http://arxiv.org/abs/2111.08210v1

    • [cs.CL]Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts
    Yan Zeng, Xinsong Zhang, Hang Li
    http://arxiv.org/abs/2111.08276v1

    • [cs.CL]Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity
    Sheshera Mysore, Arman Cohan, Tom Hope
    http://arxiv.org/abs/2111.08366v1

    • [cs.CL]NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21
    Sandeep Subramanian, Oleksii Hrinchuk, Virginia Adams, Oleksii Kuchaiev
    http://arxiv.org/abs/2111.08634v1

    • [cs.CL]STAMP 4 NLP — An Agile Framework for Rapid Quality-Driven NLP Applications Development
    Philipp Kohl, Oliver Schmidts, Lars Klöser, Henri Werth, Bodo Kraft, Albert Zündorf
    http://arxiv.org/abs/2111.08408v1

    • [cs.CL]The role of attraction-repulsion dynamics in simulating the emergence of inflectional class systems
    Erich R. Round, Sacha Beniamine, Louise Esher
    http://arxiv.org/abs/2111.08465v1

    • [cs.CL]WikiContradiction: Detecting Self-Contradiction Articles on Wikipedia
    Cheng Hsu, Cheng-Te Li, Diego Saez-Trumper, Yi-Zhan Hsu
    http://arxiv.org/abs/2111.08543v1

    • [cs.CR]An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences
    Wei Guo, Benedetta Tondi, Mauro Barni
    http://arxiv.org/abs/2111.08429v1

    • [cs.CV]今日学术视野(2021.11.18) - 图2 for Interaction Prediction
    David Wu, Yunnan Wu
    http://arxiv.org/abs/2111.08184v1

    • [cs.CV]A Data-Driven Approach for Linear and Nonlinear Damage Detection Using Variational Mode Decomposition and GARCH Model
    Vahid Reza Gharehbaghi, Hashem Kalbkhani, Ehsan Noroozinejad Farsangi, T. Y. Yang, Seyedali Mirjalili
    http://arxiv.org/abs/2111.08620v1

    • [cs.CV]Bengali Handwritten Grapheme Classification: Deep Learning Approach
    Tarun Roy, Hasib Hasan, Kowsar Hossain, Masuma Akter Rumi
    http://arxiv.org/abs/2111.08249v1

    • [cs.CV]Beyond Mono to Binaural: Generating Binaural Audio from Mono Audio with Depth and Cross Modal Attention
    Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma
    http://arxiv.org/abs/2111.08046v1

    • [cs.CV]CAR — Cityscapes Attributes Recognition A Multi-category Attributes Dataset for Autonomous Vehicles
    Kareem Metwaly, Aerin Kim, Elliot Branson, Vishal Monga
    http://arxiv.org/abs/2111.08243v1

    • [cs.CV]Choose Settings Carefully: Comparing Action Unit detection at Different Settings Using a Large-Scale Dataset
    Mina Bishay, Ahmed Ghoneim, Mohamed Ashraf, Mohammad Mavadati
    http://arxiv.org/abs/2111.08324v1

    • [cs.CV]Coarse-to-fine Animal Pose and Shape Estimation
    Chen Li, Gim Hee Lee
    http://arxiv.org/abs/2111.08176v1

    • [cs.CV]Consistent Semantic Attacks on Optical Flow
    Tom Koren, Lior Talker, Michael Dinerstein, Roy J Jevnisek
    http://arxiv.org/abs/2111.08485v1

    • [cs.CV]DFC: Deep Feature Consistency for Robust Point Cloud Registration
    Zhu Xu, Zhengyao Bai, Huijie Liu, Qianjie Lu, Shenglan Fan
    http://arxiv.org/abs/2111.07597v2

    • [cs.CV]DRINet++: Efficient Voxel-as-point Point Cloud Segmentation
    Maosheng Ye, Rui Wan, Shuangjie Xu, Tongyi Cao, Qifeng Chen
    http://arxiv.org/abs/2111.08318v1

    • [cs.CV]Data Augmentation using Random Image Cropping for High-resolution Virtual Try-On (VITON-CROP)
    Taewon Kang, Sunghyun Park, Seunghwan Choi, Jaegul Choo
    http://arxiv.org/abs/2111.08270v1

    • [cs.CV]Delta-GAN-Encoder: Encoding Semantic Changes for Explicit Image Editing, using Few Synthetic Samples
    Nir Diamant, Nitsan Shandor, Alex M Bronstein
    http://arxiv.org/abs/2111.08419v1

    • [cs.CV]Diversified Multi-prototype Representation for Semi-supervised Segmentation
    Jizong Peng, Christian Desrosiers, Marco Pedersoli
    http://arxiv.org/abs/2111.08651v1

    • [cs.CV]Enabling equivariance for arbitrary Lie groups
    Lachlan E. MacDonald, Sameera Ramasinghe, Simon Lucey
    http://arxiv.org/abs/2111.08251v1

    • [cs.CV]FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows
    Jiawei Yu, Ye Zheng, Xiang Wang, Wei Li, Yushuang Wu, Rui Zhao, Liwei Wu
    http://arxiv.org/abs/2111.07677v2

    • [cs.CV]Fight Detection from Still Images in the Wild
    Şeymanur Aktı, Ferda Ofli, Muhammad Imran, Hazım Kemal Ekenel
    http://arxiv.org/abs/2111.08370v1

    • [cs.CV]IKEA Object State Dataset: A 6DoF object pose estimation dataset and benchmark for multi-state assembly objects
    Yongzhi Su, Mingxin Liu, Jason Rambach, Antonia Pehrson, Anton Berg, Didier Stricker
    http://arxiv.org/abs/2111.08614v1

    • [cs.CV]INTERN: A New Learning Paradigm Towards General Vision
    Jing Shao, Siyu Chen, Yangguang Li, Kun Wang, Zhenfei Yin, Yinan He, Jianing Teng, Qinghong Sun, Mengya Gao, Jihao Liu, Gengshi Huang, Guanglu Song, Yichao Wu, Yuming Huang, Fenggang Liu, Huan Peng, Shuo Qin, Chengyu Wang, Yujie Wang, Conghui He, Ding Liang, Yu Liu, Fengwei Yu, Junjie Yan, Dahua Lin, Xiaogang Wang, Yu Qiao
    http://arxiv.org/abs/2111.08687v1

    • [cs.CV]Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding
    Bum Jun Kim, Hyeyeon Choi, Hyeonah Jang, Dong Gu Lee, Wonseok Jeong, Sang Woo Kim
    http://arxiv.org/abs/2111.08413v1

    • [cs.CV]Keypoint Message Passing for Video-based Person Re-Identification
    Di Chen, Andreas Doering, Shanshan Zhang, Jian Yang, Juergen Gall, Bernt Schiele
    http://arxiv.org/abs/2111.08279v1

    • [cs.CV]LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations
    Weronika Hryniewska, Adrianna Grudzień, Przemysław Biecek
    http://arxiv.org/abs/2111.08094v1

    • [cs.CV]Language bias in Visual Question Answering: A Survey and Taxonomy
    Desen Yuan
    http://arxiv.org/abs/2111.08531v1

    • [cs.CV]Learnable Locality-Sensitive Hashing for Video Anomaly Detection
    Yue Lu, Congqi Cao, Yanning Zhang
    http://arxiv.org/abs/2111.07839v2

    • [cs.CV]Learning Intrinsic Images for Clothing
    Kuo Jiang, Zian Wang, Xiaodong Yang
    http://arxiv.org/abs/2111.08521v1

    • [cs.CV]NENet: Monocular Depth Estimation via Neural Ensembles
    Shuwei Shao, Ran Li, Zhongcai Pei, Zhong Liu, Weihai Chen, Wentao Zhu, Xingming Wu, Baochang Zhang
    http://arxiv.org/abs/2111.08313v1

    • [cs.CV]Pansharpening by convolutional neural networks in the full resolution framework
    Matteo Ciotola, Sergio Vitale, Antonio Mazza, Giovanni Poggi, Giuseppe Scarpa
    http://arxiv.org/abs/2111.08334v1

    • [cs.CV]Point detection through multi-instance deep heatmap regression for sutures in endoscopy
    Lalith Sharan, Gabriele Romano, Julian Brand, Halvar Kelm, Matthias Karck, Raffaele De Simone, Sandy Engelhardt
    http://arxiv.org/abs/2111.08468v1

    • [cs.CV]Pose Recognition in the Wild: Animal pose estimation using Agglomerative Clustering and Contrastive Learning
    Samayan Bhattacharya, Sk Shahnawaz
    http://arxiv.org/abs/2111.08259v1

    • [cs.CV]Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimation
    William McNally, Kanav Vats, Alexander Wong, John McPhee
    http://arxiv.org/abs/2111.08557v1

    • [cs.CV]Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion
    Anirud Thyagharajan, Benjamin Ummenhofer, Prashant Laddha, Om J Omer, Sreenivas Subramoney
    http://arxiv.org/abs/2111.08434v1

    • [cs.CV]SEnSeI: A Deep Learning Module for Creating Sensor Independent Cloud Masks
    Alistair Francis, John Mrziglod, Panagiotis Sidiropoulos, Jan-Peter Muller
    http://arxiv.org/abs/2111.08349v1

    • [cs.CV]Self-supervised High-fidelity and Re-renderable 3D Facial Reconstruction from a Single Image
    Mingxin Yang, Jianwei Guo, Zhanglin Cheng, Xiaopeng Zhang, Dong-Ming Yan
    http://arxiv.org/abs/2111.08282v1

    • [cs.CV]SequentialPointNet: A strong parallelized point cloud sequence network for 3D action recognition
    Xing Li, Qian Huang, Zhijian Wang, Zhenjie Hou, Tianjin Yang
    http://arxiv.org/abs/2111.08492v1

    • [cs.CV]ShapeY: Measuring Shape Recognition Capacity Using Nearest Neighbor Matching
    Jong Woo Nam, Amanda S. Rios, Bartlett W. Mel
    http://arxiv.org/abs/2111.08174v1

    • [cs.CV]Single Image Object Counting and Localizing using Active-Learning
    Inbar Huberman-Spiegelglas, Raanan Fattal
    http://arxiv.org/abs/2111.08383v1

    • [cs.CV]Synthetic Unknown Class Learning for Learning Unknowns
    Jaeyeon Jang
    http://arxiv.org/abs/2111.08062v1

    • [cs.CV]TRIG: Transformer-Based Text Recognizer with Initial Embedding Guidance
    Yue Tao, Zhiwei Jia, Runze Ma, Shugong Xu
    http://arxiv.org/abs/2111.08314v1

    • [cs.CV]Two-dimensional Deep Regression for Early Yield Prediction of Winter Wheat
    Giorgio Morales, John W. Sheppard
    http://arxiv.org/abs/2111.08069v1

    • [cs.CV]UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection
    Andra Acsintoae, Andrei Florescu, Mariana-Iuliana Georgescu, Tudor Mare, Paul Sumedrea, Radu Tudor Ionescu, Fahad Shahbaz Khan, Mubarak Shah
    http://arxiv.org/abs/2111.08644v1

    • [cs.CV]Weakly-supervised fire segmentation by visualizing intermediate CNN layers
    Milad Niknejad, Alexandre Bernardino
    http://arxiv.org/abs/2111.08401v1

    • [cs.CV]Which CNNs and Training Settings to Choose for Action Unit Detection? A Study Based on a Large-Scale Dataset
    Mina Bishay, Ahmed Ghoneim, Mohamed Ashraf, Mohammad Mavadati
    http://arxiv.org/abs/2111.08320v1

    • [cs.DB]Highly Efficient Indexing Scheme for k-Dominant Skyline Processing over Uncertain Data Streams
    Chuan-Chi Lai, Hsuan-Yu Lin, Chuan-Ming Liu
    http://arxiv.org/abs/2111.08300v1

    • [cs.DC]Online Self-Evolving Anomaly Detection in Cloud Computing Environments
    Haili Wang, Jingda Guo, Xu Ma, Song Fu, Qing Yang, Yunzhong Xu
    http://arxiv.org/abs/2111.08232v1

    • [cs.DC]Project CGX: Scalable Deep Learning on Commodity GPUs
    Ilia Markov, Hamidreza Ramezani, Dan Alistarh
    http://arxiv.org/abs/2111.08617v1

    • [cs.DC]Quo Vadis MPI RMA? Towards a More Efficient Use of MPI One-Sided Communication
    Joseph Schuchart, Christoph Niethammer, José Gracia, George Bosilca
    http://arxiv.org/abs/2111.08142v1

    • [cs.DC]Saath: Speeding up CoFlows by Exploiting the Spatial Dimension
    Akshay Jajoo, Rohan Gandhi, Y. Charlie Hu, Cheng-Kok Koh
    http://arxiv.org/abs/2111.08572v1

    • [cs.DC]Self-Stabilization and Byzantine Tolerance for Maximal Independent Set
    Johanne Cohen, Laurence Pilard, Jonas Sénizergues
    http://arxiv.org/abs/2111.08348v1

    • [cs.DC]Task allocation for decentralized training in heterogeneous environment
    Yongyue Chao, Mingxue Liao, Jiaxin Gao
    http://arxiv.org/abs/2111.08272v1

    • [cs.DL]Patent Data for Engineering Design: A Review
    Shuo Jiang, Serhad Sarica, Binyang Song, Jie Hu, Jianxi Luo
    http://arxiv.org/abs/2111.08500v1

    • [cs.HC]Words of Wisdom: Representational Harms in Learning From AI Communication
    Amanda Buddemeyer, Erin Walker, Malihe Alikhani
    http://arxiv.org/abs/2111.08581v1

    • [cs.IR]Pre-training Graph Neural Network for Cross Domain Recommendation
    Chen Wang, Yueqing Liang, Zhiwei Liu, Tao Zhang, Philip S. Yu
    http://arxiv.org/abs/2111.08268v1

    • [cs.IR]QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback
    Handong Ma, Jiawei Hou, Chenxu Zhu, Weinan Zhang, Ruiming Tang, Jincai Lai, Jieming Zhu, Xiuqiang He, Yong Yu
    http://arxiv.org/abs/2111.08229v1

    • [cs.IR]Utilizing Textual Reviews in Latent Factor Models for Recommender Systems
    Tatev Karen Aslanyan, Flavius Frasincar
    http://arxiv.org/abs/2111.08538v1

    • [cs.IT]A Markov Chain Approach for Myopic Multi-hop Relaying: Outage and Diversity Analysis
    Andreas Nicolaides, Constantinos Psomas, Ioannis Krikidis
    http://arxiv.org/abs/2111.08296v1

    • [cs.IT]A fixed latency ORBGRAND decoder architecture with LUT-aided error-pattern scheduling
    Carlo Condo
    http://arxiv.org/abs/2111.08134v1

    • [cs.IT]Continuous-Aperture MIMO for Electromagnetic Information Theory
    Zijian Zhang, Linglong Dai
    http://arxiv.org/abs/2111.08630v1

    • [cs.IT]Dense Circulant Lattices From Nonlinear Systems
    William Lima da Silva Pinto, Carina Alves
    http://arxiv.org/abs/2111.08084v1

    • [cs.IT]Faster-than-Nyquist Asynchronous NOMA Outperforms Synchronous NOMA
    Shuagyang Li, Zhiqiang Wei, Weijie Yuan, Jinhong Yuan, Baoming Bai, Derrick Wing Kwan Ng, Lajos Hanzo
    http://arxiv.org/abs/2111.08258v1

    • [cs.IT]Faster-than-Nyquist Signaling for MIMO Communications
    Zichao Zhang, Melda Yuksel, Halim Yanikomeroglu
    http://arxiv.org/abs/2111.07867v2

    • [cs.IT]Generalization Bounds and Algorithms for Learning to Communicate over Additive Noise Channels
    Nir Weinberger
    http://arxiv.org/abs/2111.08253v1

    • [cs.IT]Hybrid Beam Alignment for Multi-Path Channels: A Group Testing Viewpoint
    Ozlem Yildiz, Abbas Khalili, Elza Erkip
    http://arxiv.org/abs/2111.08159v1

    • [cs.IT]Hybrid Reflection Modulation
    Zehra Yigit, Ertugrul Basar, Miaowen Wen, Ibrahim Altunbas
    http://arxiv.org/abs/2111.08355v1

    • [cs.IT]Introduction to Set Shaping Theory
    Solomon Kozlov
    http://arxiv.org/abs/2111.08369v1

    • [cs.IT]On Reverse Elastic Channels and the Asymmetry of Commitment Capacity under Channel Elasticity
    Amitalok J. Budkuley, Pranav Joshi, Manideep Mamindlapally, Anuj Kumar Yadav
    http://arxiv.org/abs/2111.08477v1

    • [cs.IT]On The Number of Different Entries in Involutory MDS Matrices over Finite Fields of Characteristic Two
    Muhammad Afifurrahman
    http://arxiv.org/abs/2111.08352v1

    • [cs.LG]A Unified and Fast Interpretable Model for Predictive Analytics
    Rui Ding, Tianchi Qiao, Yunan Zhu, Zhitao Zou, Shi Han, Dongmei Zhang
    http://arxiv.org/abs/2111.08255v1

    • [cs.LG]Assessing Deep Neural Networks as Probability Estimators
    Yu Pan, Kwo-Sen Kuo, Michael L. Rilee, Hongfeng Yu
    http://arxiv.org/abs/2111.08239v1

    • [cs.LG]Automatically detecting anomalous exoplanet transits
    Christoph J. Hönes, Benjamin Kurt Miller, Ana M. Heras, Bernard H. Foing
    http://arxiv.org/abs/2111.08679v1

    • [cs.LG]Causal Effect Variational Autoencoder with Uniform Treatment
    Daniel Jiwoong Im, Kyunghyun Cho, Narges Razavian
    http://arxiv.org/abs/2111.08656v1

    • [cs.LG]Comparative Analysis of Machine Learning Models for Predicting Travel Time
    Armstrong Aboah, Elizabeth Arthur
    http://arxiv.org/abs/2111.08226v1

    • [cs.LG]Deep Distilling: automated code generation using explainable deep learning
    Paul J. Blazek, Kesavan Venkatesh, Milo M. Lin
    http://arxiv.org/abs/2111.08275v1

    • [cs.LG]Exploiting Action Impact Regularity and Partially Known Models for Offline Reinforcement Learning
    Vincent Liu, James Wright, Martha White
    http://arxiv.org/abs/2111.08066v1

    • [cs.LG]Fairness-aware Online Price Discrimination with Nonparametric Demand Models
    Xi Chen, Xuan Zhang, Yuan Zhou
    http://arxiv.org/abs/2111.08221v1

    • [cs.LG]FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
    Yuezhou Wu, Yan Kang, Jiahuan Luo, Yuanqin He, Qiang Yang
    http://arxiv.org/abs/2111.08211v1

    • [cs.LG]FedCostWAvg: A new averaging for better Federated Learning
    Leon Mächler, Ivan Ezhov, Florian Kofler, Suprosanna Shit, Johannes C. Paetzold, Timo Loehr, Benedikt Wiestler, Bjoern Menze
    http://arxiv.org/abs/2111.08649v1

    • [cs.LG]Free Will Belief as a consequence of Model-based Reinforcement Learning
    Erik M. Rehn
    http://arxiv.org/abs/2111.08435v1

    • [cs.LG]Grounding Psychological Shape Space in Convolutional Neural Networks
    Lucas Bechberger, Kai-Uwe Kühnberger
    http://arxiv.org/abs/2111.08409v1

    • [cs.LG]HADFL: Heterogeneity-aware Decentralized Federated Learning Framework
    Jing Cao, Zirui Lian, Weihong Liu, Zongwei Zhu, Cheng Ji
    http://arxiv.org/abs/2111.08274v1

    • [cs.LG]HiRID-ICU-Benchmark — A Comprehensive Machine Learning Benchmark on High-resolution ICU Data
    Hugo Yèche, Rita Kuznetsova, Marc Zimmermann, Matthias Hüser, Xinrui Lyu, Martin Faltys, Gunnar Rätsch
    http://arxiv.org/abs/2111.08536v1

    • [cs.LG]Inference-Time Personalized Federated Learning
    Ohad Amosy, Gal Eyal, Gal Chechik
    http://arxiv.org/abs/2111.08356v1

    • [cs.LG]Interpretable and Fair Boolean Rule Sets via Column Generation
    Connor Lawless, Sanjeeb Dash, Oktay Gunluk, Dennis Wei
    http://arxiv.org/abs/2111.08466v1

    • [cs.LG]Interpreting Language Models Through Knowledge Graph Extraction
    Vinitra Swamy, Angelika Romanou, Martin Jaggi
    http://arxiv.org/abs/2111.08546v1

    • [cs.LG]Inverse-Weighted Survival Games
    Xintian Han, Mark Goldstein, Aahlad Puli, Thomas Wies, Adler J Perotte, Rajesh Ranganath
    http://arxiv.org/abs/2111.08175v1

    • [cs.LG]Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
    Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam
    http://arxiv.org/abs/2111.08202v1

    • [cs.LG]Learning Augmentation Distributions using Transformed Risk Minimization
    Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Edgar Dobriban, Kostas Daniilidis
    http://arxiv.org/abs/2111.08190v1

    • [cs.LG]Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection
    Saswati Ray, Sana Lakdawala, Mononito Goswami, Chufan Gao
    http://arxiv.org/abs/2111.08082v1

    • [cs.LG]Machine Learning and Ensemble Approach Onto Predicting Heart Disease
    Aaditya Surya
    http://arxiv.org/abs/2111.08667v1

    • [cs.LG]Machine Learning-Assisted Analysis of Small Angle X-ray Scattering
    Piotr Tomaszewski, Shun Yu, Markus Borg, Jerk Rönnols
    http://arxiv.org/abs/2111.08645v1

    • [cs.LG]Margin-Independent Online Multiclass Learning via Convex Geometry
    Guru Guruganesh, Allen Liu, Jon Schneider, Joshua Wang
    http://arxiv.org/abs/2111.08057v1

    • [cs.LG]Mathematical Models for Local Sensing Hashes
    Li Wang, Lilon Wangner
    http://arxiv.org/abs/2111.08344v1

    • [cs.LG]MoRe-Fi: Motion-robust and Fine-grained Respiration Monitoring via Deep-Learning UWB Radar
    Tianyue Zheng, Zhe Chen, Shujie Zhang, Chao Cai, Jun Luo
    http://arxiv.org/abs/2111.08195v1

    • [cs.LG]ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control
    Xingshuai Huang, Di Wu, Michael Jenkin, Benoit Boulet
    http://arxiv.org/abs/2111.08067v1

    • [cs.LG]Modular Networks Prevent Catastrophic Interference in Model-Based Multi-Task Reinforcement Learning
    Robin Schiewer, Laurenz Wiskott
    http://arxiv.org/abs/2111.08010v1

    • [cs.LG]Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure Detection
    Una Pale, Tomas Teijeiro, David Atienza
    http://arxiv.org/abs/2111.08463v1

    • [cs.LG]Natural Gradient Variational Inference with Gaussian Mixture Models
    Farzaneh Mahdisoltani
    http://arxiv.org/abs/2111.08002v1

    • [cs.LG]Neural networks with linear threshold activations: structure and algorithms
    Sammy Khalife, Amitabh Basu
    http://arxiv.org/abs/2111.08117v1

    • [cs.LG]Neuron-based Pruning of Deep Neural Networks with Better Generalization using Kronecker Factored Curvature Approximation
    Abdolghani Ebrahimi, Diego Klabjan
    http://arxiv.org/abs/2111.08577v1

    • [cs.LG]Non-separable Spatio-temporal Graph Kernels via SPDEs
    Alexander Nikitin, ST John, Arno Solin, Samuel Kaski
    http://arxiv.org/abs/2111.08524v1

    • [cs.LG]Off-Policy Actor-Critic with Emphatic Weightings
    Eric Graves, Ehsan Imani, Raksha Kumaraswamy, Martha White
    http://arxiv.org/abs/2111.08172v1

    • [cs.LG]On Bock’s Conjecture Regarding the Adam Optimizer
    Mohamed Akrout, Douglas Tweed
    http://arxiv.org/abs/2111.08162v1

    • [cs.LG]On Effective Scheduling of Model-based Reinforcement Learning
    Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li
    http://arxiv.org/abs/2111.08550v1

    • [cs.LG]Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters
    Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu
    http://arxiv.org/abs/2111.05897v2

    • [cs.LG]Phase function estimation from a diffuse optical image via deep learning
    Yuxuan Liang, Chuang Niu, Chen Wei, Shenghan Ren, Wenxiang Cong, Ge Wang
    http://arxiv.org/abs/2111.08227v1

    • [cs.LG]Polymatrix Competitive Gradient Descent
    Jeffrey Ma, Alistair Letcher, Florian Schäfer, Yuanyuan Shi, Anima Anandkumar
    http://arxiv.org/abs/2111.08565v1

    • [cs.LG]Rank-Regret Minimization
    Xingxing Xiao, Jianzhong Li
    http://arxiv.org/abs/2111.08563v1

    • [cs.LG]Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills
    Taku Yamagata, Ryan McConville, Raul Santos-Rodriguez
    http://arxiv.org/abs/2111.08596v1

    • [cs.LG]Reshaping Smart Energy Transition: An analysis of human-building interactions in Qatar Using Machine Learning Techniques
    Rateb Jabbar, Esmat Zaidan, Ahmed ben Said, Ali Ghofrani
    http://arxiv.org/abs/2111.08333v1

    • [cs.LG]Robust recovery for stochastic block models
    Jingqiu Ding, Tommaso d’Orsi, Rajai Nasser, David Steurer
    http://arxiv.org/abs/2111.08568v1

    • [cs.LG]Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks
    Adaku Uchendu, Daniel Campoy, Christopher Menart, Alexandra Hildenbrandt
    http://arxiv.org/abs/2111.08591v1

    • [cs.LG]Selective Ensembles for Consistent Predictions
    Emily Black, Klas Leino, Matt Fredrikson
    http://arxiv.org/abs/2111.08230v1

    • [cs.LG]Solving Linear Algebra by Program Synthesis
    Iddo Drori, Nakul Verma
    http://arxiv.org/abs/2111.08171v1

    • [cs.LG]Solving Probability and Statistics Problems by Program Synthesis
    Leonard Tang, Elizabeth Ke, Nikhil Singh, Nakul Verma, Iddo Drori
    http://arxiv.org/abs/2111.08267v1

    • [cs.LG]Switching Recurrent Kalman Networks
    Giao Nguyen-Quynh, Philipp Becker, Chen Qiu, Maja Rudolph, Gerhard Neumann
    http://arxiv.org/abs/2111.08291v1

    • [cs.LG]Thoughts on the Consistency between Ricci Flow and Neural Network Behavior
    Jun Chen, Tianxin Huang, Wenzhou Chen, Yong Liu
    http://arxiv.org/abs/2111.08410v1

    • [cs.LG]TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation
    Abhyuday Desai, Cynthia Freeman, Zuhui Wang, Ian Beaver
    http://arxiv.org/abs/2111.08095v1

    • [cs.LG]Towards Generating Real-World Time Series Data
    Hengzhi Pei, Kan Ren, Yuqing Yang, Chang Liu, Tao Qin, Dongsheng Li
    http://arxiv.org/abs/2111.08386v1

    • [cs.LG]VisualEnv: visual Gym environments with Blender
    Andrea Scorsoglio, Roberto Furfaro
    http://arxiv.org/abs/2111.08096v1

    • [cs.LG]Wyner-Ziv Gradient Compression for Federated Learning
    Kai Liang, Huiru Zhong, Haoning Chen, Youlong Wu
    http://arxiv.org/abs/2111.08277v1

    • [cs.NE]A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting
    Faizal Hafiz, Jan Broekaert, Davide La Torre, Akshya Swain
    http://arxiv.org/abs/2111.08060v1

    • [cs.NI]CLARA: A Constrained Reinforcement Learning Based Resource Allocation Framework for Network Slicing
    Yongshuai Liu, Jiaxin Ding, Zhi-Li Zhang, Xin Liu
    http://arxiv.org/abs/2111.08397v1

    • [cs.NI]Common Language for Goal-Oriented Semantic Communications: A Curriculum Learning Framework
    Mohammad Karimzadeh Farshbafan, Walid Saad, Merouane Debbah
    http://arxiv.org/abs/2111.08051v1

    • [cs.NI]HyperNAT: Scaling Up Network AddressTranslation with SmartNICs for Clouds
    Shaoke Fang, Qingsong Liu, Wenfei Wu
    http://arxiv.org/abs/2111.08193v1

    • [cs.NI]Learning Robust Scheduling with Search and Attention
    David Sandberg, Tor Kvernvik, Francesco Davide Calabrese
    http://arxiv.org/abs/2111.08073v1

    • [cs.RO]2.5D Vehicle Odometry Estimation
    Ciaran Eising, Leroy-Francisco Pereira, Jonathan Horgan, Anbuchezhiyan Selvaraju, John McDonald, Paul Moran
    http://arxiv.org/abs/2111.08398v1

    • [cs.RO]Active Vapor-Based Robotic Wiper
    Takuya Kiyokawa, Hiroki Katayama, Jun Takamatsu
    http://arxiv.org/abs/2111.08248v1

    • [cs.RO]Analysis of Model-Free Reinforcement Learning Control Schemes on self-balancing Wheeled Extendible System
    Kanishk ., Rushil Kumar, Vikas Rastogi, Ajeet Kumar
    http://arxiv.org/abs/2111.08389v1

    • [cs.RO]GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving
    Raphael Chekroun, Marin Toromanoff, Sascha Hornauer, Fabien Moutarde
    http://arxiv.org/abs/2111.08575v1

    • [cs.RO]Hierarchical Topometric Representation of 3D Robotic Maps
    ZhenpengHe, HaoSun, JiaweiHou, YajunHa, Sören Schwertfeger
    http://arxiv.org/abs/2111.08283v1

    • [cs.RO]Joint State and Input Estimation of Agent Based on Recursive Kalman Filter Given Prior Knowledge
    Zida Wu, Zhaoliang Zheng, Ankur Mehta
    http://arxiv.org/abs/2111.08091v1

    • [cs.RO]Learning to Navigate in a VUCA Environment: Hierarchical Multi-expert Approach
    Wenqi Zhang, Kai Zhao, Peng Li, Xiao Zhu, Faping Ye, Weijie Jiang, Huiqiao Fu, Tao Wang
    http://arxiv.org/abs/2111.08364v1

    • [cs.RO]Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing
    Xianglong Tan, Zhikang Liu, Chen Yu, Andre Rosendo
    http://arxiv.org/abs/2111.08147v1

    • [cs.RO]Towards Real-Time Monocular Depth Estimation for Robotics: A Survey
    Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass
    http://arxiv.org/abs/2111.08600v1

    • [cs.RO]Virtual Reality for Synergistic Surgical Training and Data Generation
    Adnan Munawar, Zhaoshuo Li, Punit Kunjam, Nimesh Nagururu, Andy S. Ding, Peter Kazanzides, Thomas Looi, Francis X. Creighton, Russell H. Taylor, Mathias Unberath
    http://arxiv.org/abs/2111.08097v1

    • [cs.SE]Is CADP an Applicable Formal Method?
    Hubert Garavel, Frédéric Lang, Radu Mateescu, Wendelin Serwe
    http://arxiv.org/abs/2111.08203v1

    • [cs.SI]Analysis of 5G academic Network based on graph representation learning method
    Xiaoming Li, Guangquan Xu, Wei Yu, Pengfei Jiao, Xiangyu Song
    http://arxiv.org/abs/2111.08264v1

    • [cs.SI]Improving the performance of reputation evaluating by combining the structure of network and nonlinear recovery
    Meng Li, Chengyuan Han, Yuanxiang Jiang, Zengru Di
    http://arxiv.org/abs/2111.08092v1

    • [cs.SI]Local News Online and COVID in the U.S.: Relationships among Coverage, Cases, Deaths, and Audience
    Kenneth Joseph, Benjamin D. Horne, Jon Green, John P. Wihbey
    http://arxiv.org/abs/2111.08515v1

    • [econ.EM]Designing Representative and Balanced Experiments by Local Randomization
    Max Cytrynbaum
    http://arxiv.org/abs/2111.08157v1

    • [econ.EM]Revisiting C.S.Peirce’s Experiment: 150 Years Later
    Deep Mukhopadhyay
    http://arxiv.org/abs/2111.08054v1

    • [eess.AS]Attention-based Multi-hypothesis Fusion for Speech Summarization
    Takatomo Kano, Atsunori Ogawa, Marc Delcroix, Shinji Watanabe
    http://arxiv.org/abs/2111.08201v1

    • [eess.AS]Single-channel speech separation using Soft-minimum Permutation Invariant Training
    Midia Yousefi, John H. L. Hansen
    http://arxiv.org/abs/2111.08635v1

    • [eess.IV]A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution
    Yue Shi, Liangxiu Han, Lianghao Han, Sheng Chang, Tongle Hu, Darren Dancey
    http://arxiv.org/abs/2111.08685v1

    • [eess.IV]A layer-stress learning framework universally augments deep neural network tasks
    Shihao Shao, Yong Liu, Qinghua Cui
    http://arxiv.org/abs/2111.08597v1

    • [eess.IV]Advancement of Deep Learning in Pneumonia and Covid-19 Classification and Localization: A Qualitative and Quantitative Analysis
    Aakash Shah, Manan Shah
    http://arxiv.org/abs/2111.08606v1

    • [eess.IV]Disparities in Dermatology AI: Assessments Using Diverse Clinical Images
    Roxana Daneshjou, Kailas Vodrahalli, Weixin Liang, Roberto A Novoa, Melissa Jenkins, Veronica Rotemberg, Justin Ko, Susan M Swetter, Elizabeth E Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, James Zou, Albert Chiou
    http://arxiv.org/abs/2111.08006v1

    • [eess.IV]Image-specific Convolutional Kernel Modulation for Single Image Super-resolution
    Yuanfei Huang, Jie Li, Yanting Hu, Xinbo Gao, Hua Huang
    http://arxiv.org/abs/2111.08362v1

    • [eess.IV]Online Meta Adaptation for Variable-Rate Learned Image Compression
    Wei Jiang, Wei Wang, Songnan Li, Shan Liu
    http://arxiv.org/abs/2111.08256v1

    • [eess.IV]Solving Inverse Problems in Medical Imaging with Score-Based Generative Models
    Yang Song, Liyue Shen, Lei Xing, Stefano Ermon
    http://arxiv.org/abs/2111.08005v1

    • [eess.SP]Blockage Prediction Using Wireless Signatures: Deep Learning Enables Real-World Demonstration
    Shunyao Wu, Muhammad Alrabeiah, Chaitali Chakrabarti, Ahmed Alkhateeb
    http://arxiv.org/abs/2111.08242v1

    • [eess.SP]Deep Diffusion Models for Robust Channel Estimation
    Marius Arvinte, Jonathan I Tamir
    http://arxiv.org/abs/2111.08177v1

    • [eess.SP]Human-error-potential Estimation based on Wearable Biometric Sensors
    Hiroki Ohashi, Hiroto Nagayoshi
    http://arxiv.org/abs/2111.08502v1

    • [eess.SY]Graph neural network-based fault diagnosis: a review
    Zhiwen Chen, Jiamin Xu, Cesare Alippi, Steven X. Ding, Yuri Shardt, Tao Peng, Chunhua Yang
    http://arxiv.org/abs/2111.08185v1

    • [math-ph]Second-order statistics of fermionic Gaussian states
    Youyi Huang, Lu Wei
    http://arxiv.org/abs/2111.08216v1

    • [math.OC]Data-Driven Inpatient Bed Assignment Using the P Model
    Shasha Han, Shuangchi He, Hong Choon Oh
    http://arxiv.org/abs/2111.08269v1

    • [math.OC]Learning Optimal Control with Stochastic Models of Hamiltonian Dynamics
    Chandrajit Bajaj, Minh Nguyen
    http://arxiv.org/abs/2111.08108v1

    • [math.OC]Multiclass Optimal Classification Trees with SVM-splits
    Víctor Blanco, Alberto Japón, Justo Puerto
    http://arxiv.org/abs/2111.08674v1

    • [math.OC]Stochastic Extragradient: General Analysis and Improved Rates
    Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou
    http://arxiv.org/abs/2111.08611v1

    • [math.PR]Prediction theory in continuous time
    N. H. Bingham
    http://arxiv.org/abs/2111.08560v1

    • [math.ST]On Adaptive Confidence Sets for the Wasserstein Distances
    Neil Deo, Thibault Randrianarisoa
    http://arxiv.org/abs/2111.08505v1

    • [math.ST]Properties of linear spectral statistics of frequency-smoothed estimated spectral coherence matrix of high-dimensional Gaussian time series
    Philippe Loubaton, Alexis Rosuel
    http://arxiv.org/abs/2111.08047v1

    • [math.ST]Quantification of fracture roughness by change probabilities and Hurst exponents
    Tim Gutjahr, Sina Hale, Karsten Keller, Philipp Blum, Steffen Winter
    http://arxiv.org/abs/2111.08661v1

    • [physics.comp-ph]Normalizing flows for atomic solids
    Peter Wirnsberger, George Papamakarios, Borja Ibarz, Sébastien Racanière, Andrew J. Ballard, Alexander Pritzel, Charles Blundell
    http://arxiv.org/abs/2111.08696v1

    • [physics.flu-dyn]Global Sensitivity Analysis of Four Chamber Heart Hemodynamics Using Surrogate Models
    Elias Karabelas, Stefano Longobardi, Jana Fuchsberger, Orod Razeghi, Cristobal Rodero, Marina Strocchi, Ronak Rajani, Gundolf Haase, Gernot Plank, Steven Niederer
    http://arxiv.org/abs/2111.08339v1

    • [physics.plasm-ph]Tracking Blobs in the Turbulent Edge Plasma of Tokamak Fusion Reactors
    Woonghee Han, Randall A. Pietersen, Rafael Villamor-Lora, Matthew Beveridge, Nicola Offeddu, Theodore Golfinopoulos, Christian Theiler, James L. Terry, Earl S. Marmar, Iddo Drori
    http://arxiv.org/abs/2111.08570v1

    • [q-bio.QM]Code-free development and deployment of deep segmentation models for digital pathology
    Henrik Sahlin Pettersen, Ilya Belevich, Elin Synnøve Røyset, Erik Smistad, Eija Jokitalo, Ingerid Reinertsen, Ingunn Bakke, André Pedersen
    http://arxiv.org/abs/2111.08430v1

    • [quant-ph]Tensor network to learn the wavefunction of data
    Anatoly Dymarsky, Kirill Pavlenko
    http://arxiv.org/abs/2111.08014v1

    • [stat.AP]An Empirical Evaluation of the Impact of New York’s Bail Reform on Crime Using Synthetic Controls
    Angela Zhou, Andrew Koo, Nathan Kallus, Rene Ropac, Richard Peterson, Stephen Koppel, Tiffany Bergin
    http://arxiv.org/abs/2111.08664v1

    • [stat.AP]Bayesian inference of the climbing grade scale
    Alexei Drummond, Alex Popinga
    http://arxiv.org/abs/2111.08140v1

    • [stat.AP]Bayesian, frequentist and fiducial intervals for the difference between two binomial proportions
    Lizanne Raubenheimer
    http://arxiv.org/abs/2111.08610v1

    • [stat.AP]Hierarchical transfer learning with applications for electricity load forecasting
    Solenne Gaucher, Yannig Goude, Anestis Antoniadis
    http://arxiv.org/abs/2111.08512v1

    • [stat.AP]Joint Estimation of Extreme Precipitation at Different Spatial Scales through Mixture Modelling
    Jordan Richards, Jonathan A. Tawn, Simon J. Brown
    http://arxiv.org/abs/2111.08469v1

    • [stat.AP]Neuro-Hotnet: A Graph Theoretic Approach for Brain FC Estimation
    Nathan Tung, Eli Upfal, Jerome Sanes, Ani Eloyan
    http://arxiv.org/abs/2111.08118v1

    • [stat.AP]Regional Topics in British Grocery Retail Transactions
    Mariflor Vega Carrasco, Mirco Musolesi, Jason O’Sullivan, Rosie Prior, Ioanna Manolopoulou
    http://arxiv.org/abs/2111.08078v1

    • [stat.ME]Change-point detection for density sequence extracted from SHM data, with application to distributional information break diagnosis encountered in structural condition assessment
    Xinyi Lei, Zhicheng Chen, Hui Li, Shiyin Wei
    http://arxiv.org/abs/2111.08260v1

    • [stat.ME]Inference for extreme spatial temperature events in a changing climate with application to Ireland
    Dáire Healy, Andrew Parnell, Peter Thorne, Jonathan Tawn
    http://arxiv.org/abs/2111.08616v1

    • [stat.ME]Multi-Parameter Regression Survival Modelling with Random Effects
    Fatima-Zahra Jaouimaa, Il Do Ha, Kevin Burke
    http://arxiv.org/abs/2111.08573v1

    • [stat.ME]Sequential Unequal Probability Sampling For Stream Population
    Bardia Panahbehagh, Raphaël Jauslin, Yves Tillé
    http://arxiv.org/abs/2111.08433v1

    • [stat.ME]Simultaneous inference of correlated marginal tests using intersection-union or union-intersection test principle
    Ludwig A. Hothorn
    http://arxiv.org/abs/2111.08694v1

    • [stat.ME]Translating questions to estimands in randomized clinical trials with intercurrent events
    Mats J. Stensrud, Oliver Dukes
    http://arxiv.org/abs/2111.08509v1

    • [stat.ML]An adaptive dimension reduction algorithm for latent variables of variational autoencoder
    Yiran Dong, Chuanhou Gao
    http://arxiv.org/abs/2111.08493v1

    • [stat.ML]Bayesian Optimization for Cascade-type Multi-stage Processes
    Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi
    http://arxiv.org/abs/2111.08330v1

    • [stat.ML]Covariate Shift in High-Dimensional Random Feature Regression
    Nilesh Tripuraneni, Ben Adlam, Jeffrey Pennington
    http://arxiv.org/abs/2111.08234v1

    • [stat.ML]Distribution Compression in Near-Linear Time
    Abhishek Shetty, Raaz Dwivedi, Lester Mackey
    http://arxiv.org/abs/rg/abs/2111.07941v1

    • [stat.ML]Learning with convolution and pooling operations in kernel methods
    Theodor Misiakiewicz, Song Mei
    http://arxiv.org/abs/2111.08308v1

    • [stat.ML]SStaGCN: Simplified stacking based graph convolutional networks
    Jia Cai, Zhilong Xiong, Shaogao Lv
    http://arxiv.org/abs/2111.08228v1

    • [stat.ML]Sequential Community Mode Estimation
    Shubham Anand Jain, Shreyas Goenka, Divyam Bapna, Nikhil Karamchandani, Jayakrishnan Nair
    http://arxiv.org/abs/2111.08535v1

    • [stat.ML]Sparse Graph Learning Under Laplacian-Related Constraints
    Jitendra K. Tugnait
    http://arxiv.org/abs/2111.08161v1