cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DC - 分布式、并行与集群计算
    cs.FL - 形式语言与自动机理论
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.MA - 多代理系统
    cs.NE - 神经与进化计算
    cs.RO - 机器人学
    cs.SD - 声音处理
    cs.SE - 软件工程
    cs.SI - 社交网络与信息网络
    eess.IV - 图像与视频处理
    eess.SY - 系统和控制
    hep-ex - 高能物理实验
    hep-lat - 高能物理晶格
    math.CT - 范畴论
    math.NA - 数值分析
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.soc-ph - 物理学与社会
    q-bio.QM - 定量方法
    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]AI in (and for) Games
    • [cs.AI]Accelerating Entrepreneurial Decision-Making Through Hybrid Intelligence
    • [cs.AI]An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020)
    • [cs.AI]Design principles for a hybrid intelligence decision support system for business model validation
    • [cs.AI]Finding the unicorn: Predicting early stage startup success through a hybrid intelligence method
    • [cs.AI]Solving the Workflow Satisfiability Problem using General Purpose Solvers
    • [cs.AI]The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systems
    • [cs.AI]Using reinforcement learning to design an AI assistantfor a satisfying co-op experience
    • [cs.CL]今日学术视野(2021.5.11) - 图1-Explainer: Abductive Natural Language Inference via Differentiable Convex Optimization
    • [cs.CL]A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect
    • [cs.CL]A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers
    • [cs.CL]A Grounded Approach to Modeling Generic Knowledge Acquisition
    • [cs.CL]A Survey of Data Augmentation Approaches for NLP
    • [cs.CL]AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection Dataset
    • [cs.CL]Are Pre-trained Convolutions Better than Pre-trained Transformers?
    • [cs.CL]Do language models learn typicality judgments from text?
    • [cs.CL]Efficient Weight factorization for Multilingual Speech Recognition
    • [cs.CL]Graph-based Multilingual Product Retrieval in E-commerce Search
    • [cs.CL]Hone as You Read: A Practical Type of Interactive Summarization
    • [cs.CL]Identity Signals in Emoji Do not Influence Perception of Factual Truth on Twitter
    • [cs.CL]On the logistical difficulties and findings of Jopara Sentiment Analysis
    • [cs.CL]On-the-Fly Controlled Text Generation with Experts and Anti-Experts
    • [cs.CL]Regression Bugs Are In Your Model! Measuring, Reducing and Analyzing Regressions In NLP Model Updates
    • [cs.CL]SpeechNet: A Universal Modularized Model for Speech Processing Tasks
    • [cs.CL]The Shadowy Lives of Emojis: An Analysis of a Hacktivist Collective’s Use of Emojis on Twitter
    • [cs.CL]VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension
    • [cs.CR]A Cybersecurity Guide for Using Fitness Devices
    • [cs.CR]A DLT-based Smart Contract Architecture for Atomic and Scalable Trading
    • [cs.CV]A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: from Traditional Image Processing and Classical Machine Learning to Current Deep Convolutional Neural Networks and Potential Visual Transformers
    • [cs.CV]A^2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentation
    • [cs.CV]Adaptive Domain-Specific Normalization for Generalizable Person Re-Identification
    • [cs.CV]Adaptive Focus for Efficient Video Recognition
    • [cs.CV]Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition
    • [cs.CV]An Intelligent Passive Food Intake Assessment System with Egocentric Cameras
    • [cs.CV]Autoencoder Based Inter-Vehicle Generalization for In-Cabin Occupant Classification
    • [cs.CV]Contrastive Learning for Unsupervised Image-to-Image Translation
    • [cs.CV]Efficient Masked Face Recognition Method during the COVID-19 Pandemic
    • [cs.CV]Exploring Instance Relations for Unsupervised Feature Embedding
    • [cs.CV]Faster and Simpler Siamese Network for Single Object Tracking
    • [cs.CV]Few-Shot Learning for Image Classification of Common Flora
    • [cs.CV]Foreground-guided Facial Inpainting with Fidelity Preservation
    • [cs.CV]Human Object Interaction Detection using Two-Direction Spatial Enhancement and Exclusive Object Prior
    • [cs.CV]Interpretable Social Anchors for Human Trajectory Forecasting in Crowds
    • [cs.CV]MOTR: End-to-End Multiple-Object Tracking with TRansformer
    • [cs.CV]More Separable and Easier to Segment: A Cluster Alignment Method for Cross-Domain Semantic Segmentation
    • [cs.CV]Neural 3D Scene Compression via Model Compression
    • [cs.CV]Probabilistic Ranking-Aware Ensembles for Enhanced Object Detections
    • [cs.CV]Probabilistic Visual Place Recognition for Hierarchical Localization
    • [cs.CV]ResMLP: Feedforward networks for image classification with data-efficient training
    • [cs.CV]Salient Objects in Clutter
    • [cs.CV]Self-paced Resistance Learning against Overfitting on Noisy Labels
    • [cs.CV]Toward Interactive Modulation for Photo-Realistic Image Restoration
    • [cs.CV]Towards Real-World Category-level Articulation Pose Estimation
    • [cs.CY]Digital Voodoo Dolls
    • [cs.CY]Profiling the Cybercriminal: A Systematic Review of Research
    • [cs.CY]fAshIon after fashion: A Report of AI in Fashion
    • [cs.DC]Autonomic Management of Power Consumption with IoT and Fog Computing
    • [cs.DC]Clock Synchronization in Virtualized Distributed Real-Time Systems using IEEE 802.1AS and ACRN
    • [cs.DC]Data-driven scheduling in serverless computing to reduce response time
    • [cs.DC]Leader Election in Arbitrarily Connected Networks with Process Crashes and Weak Channel Reliability
    • [cs.DC]Simulation and evaluation of cloud storage caching for data intensive science
    • [cs.FL]Executable Interval Temporal Logic Specifications
    • [cs.HC]Everyday algorithm auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviors
    • [cs.IR]A Multi-Objective Optimization Method for Achieving Two-sided Fairness in E-commerce Recommendation
    • [cs.IR]DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation
    • [cs.IR]Users’ Perception of Search Engine Biases and Satisfaction
    • [cs.IT]Achievable Physical-Layer Secrecy in Multi-Mode Fiber Channels using Artificial Noise
    • [cs.IT]Coded Gradient Aggregation: A Tradeoff Between Communication Costs at Edge Nodes and at Helper Nodes
    • [cs.IT]Communication With Adversary Identification in Byzantine Multiple Access Channels
    • [cs.IT]Compound Arbitrarily Varying Channels
    • [cs.IT]Content Caching for Shared Medium Networks Under Heterogeneous Users’ Behaviours
    • [cs.IT]Hierarchical sparse recovery from hierarchically structured measurements with application to massive random access
    • [cs.IT]Integrated Sensing and Communication with Multi-Domain Cooperation
    • [cs.IT]Leakage-Resilient Secret Sharing with Constant Share Size
    • [cs.IT]Maximally Recoverable Codes with Hierarchical Locality: Constructions and Field-Size Bounds
    • [cs.IT]On interpolation-based decoding of a class of maximum rank distance codes
    • [cs.IT]Online Multi-Cell Coordinated MIMO Wireless Network Virtualization with Imperfect CSI
    • [cs.IT]RIS-Aided Cell-Free Massive MIMO: Performance Analysis and Competitiveness
    • [cs.IT]Retrieving Data Permutations from Noisy Observations: High and Low Noise Asymptotics
    • [cs.IT]When an Energy-Efficient Scheduling is Optimal for Half-Duplex Relay Networks?
    • [cs.LG]A Family of Hybrid Federated and Centralized Learning Architectures in Machine Learning
    • [cs.LG]A Survey of Applied Machine Learning Techniques for Optical OFDM based Networks
    • [cs.LG]ANNETTE: Accurate Neural Network Execution Time Estimation with Stacked Models
    • [cs.LG]Adapting by Pruning: A Case Study on BERT
    • [cs.LG]An Influence-based Approach for Root Cause Alarm Discovery in Telecom Networks
    • [cs.LG]ConCAD: Contrastive Learning-based Cross Attention for Sleep Apnea Detection
    • [cs.LG]Context-Based Soft Actor Critic for Environments with Non-stationary Dynamics
    • [cs.LG]Diff-ResNets for Few-shot Learning — an ODE Perspective
    • [cs.LG]Differential Privacy for Pairwise Learning: Non-convex Analysis
    • [cs.LG]Energy-Based Anomaly Detection and Localization
    • [cs.LG]Error-Robust Multi-View Clustering: Progress, Challenges and Opportunities
    • [cs.LG]Exact Acceleration of K-Means++ and K-Means今日学术视野(2021.5.11) - 图2
    • [cs.LG]FVM Network to Reduce Computational Cost of CFD Simulation
    • [cs.LG]FedGL: Federated Graph Learning Framework with Global Self-Supervision
    • [cs.LG]GANTL: Towards Practical and Real-Time Topology Optimization with Conditional GANs and Transfer Learning
    • [cs.LG]Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks
    • [cs.LG]Hierarchical Graph Neural Networks
    • [cs.LG]Laplace Matching for fast Approximate Inference in Generalized Linear Models
    • [cs.LG]Learning Controllable Content Generators
    • [cs.LG]Leveraging Multiple Relations for Fashion TrendForecasting Based on Social Media
    • [cs.LG]Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts
    • [cs.LG]Network Pruning That Matters: A Case Study on Retraining Variants
    • [cs.LG]Order in the Court: Explainable AI Methods Prone to Disagreement
    • [cs.LG]PEMNET: A Transfer Learning-based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems
    • [cs.LG]Reward prediction for representation learning and reward shaping
    • [cs.LG]Text similarity analysis for evaluation of descriptive answers
    • [cs.LG]Utilizing Skipped Frames in Action Repeats via Pseudo-Actions
    • [cs.LG]Weather impact on daily cases of COVID-19 in Saudi Arabia using machine learning
    • [cs.MA]Informational Design of Dynamic Multi-Agent System
    • [cs.NE]An Extended Jump Function Benchmark for the Analysis of Randomized Search Heuristics
    • [cs.NE]Semantics in Multi-objective Genetic Programming
    • [cs.RO]CoDE: Collocation for Demonstration Encoding
    • [cs.RO]LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping
    • [cs.RO]Sobi: An Interactive Social Service Robot for Long-Term Autonomy in Open Environments
    • [cs.RO]VIRAL SLAM: Tightly Coupled Camera-IMU-UWB-Lidar SLAM
    • [cs.RO]iCub
    • [cs.SD]SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts
    • [cs.SE]Code2Image: Intelligent Code Analysis by Computer Vision Techniques and Application to Vulnerability Prediction
    • [cs.SE]Detecting Security Fixes in Open-Source Repositories using Static Code Analyzers
    • [cs.SI]An Axiom System for Feedback Centralities
    • [cs.SI]Comparison of Traditional and Hybrid Time Series Models for Forecasting COVID-19 Cases
    • [cs.SI]Identifying critical higher-order interactions in complex networks
    • [eess.IV]DeepRF: Deep Reinforcement Learning Designed RadioFrequency Waveform in MRI
    • [eess.IV]LINN: Lifting Inspired Invertible Neural Network for Image Denoising
    • [eess.IV]NTIRE 2021 Challenge on Perceptual Image Quality Assessment
    • [eess.IV]Self-Adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images
    • [eess.IV]Structured dataset documentation: a datasheet for CheXpert
    • [eess.SY]A Multivariate Density Forecast Approach for Online Power System Security Assessment
    • [eess.SY]Learning-enhanced robust controller synthesis with rigorous statistical and control-theoretic guarantees
    • [hep-ex]Building a Distributed Computing System for LDMX: Challenges of creating and operating a lightweight e-infrastructure for small-to-medium size accelerator experiments
    • [hep-lat]Deep Learning Hamiltonian Monte Carlo
    • [math.CT]Lambek pregroups are Frobenius spiders in preorders
    • [math.NA]Estimate the spectrum of affine dynamical systems from partial observations of a single trajectory data
    • [math.OC]Neural network architectures using min plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs
    • [math.ST]Circuit bases for randomisation
    • [math.ST]Consistent estimation of distribution functions under increasing concave and convex stochastic ordering
    • [math.ST]From Graph Centrality to Data Depth
    • [physics.soc-ph]Meta-validation of bipartite network projections
    • [physics.soc-ph]The Dynamics of Faculty Hiring Networks
    • [q-bio.QM]Interpretable machine learning for high-dimensional trajectories of aging health
    • [stat.AP]A Non-Compensatory Random Utility Choice Model based on Choquet Integral
    • [stat.AP]Calibration of Spatial Forecasts from Citizen Science Urban Air Pollution Data with Sparse Recurrent Neural Networks
    • [stat.AP]Primary analysis method for incomplete CD4 count data from IMPI trial and other trials with similar setting
    • [stat.CO]SEAGLE: A Scalable Exact Algorithm for Large-Scale Set-based GxE Tests in Biobank Data
    • [stat.ME]An Objective Prior from a Scoring Rule
    • [stat.ME]Bayesian spatio-temporal model for high-resolution short-term forecasting of precipitation fields
    • [stat.ME]Double-matched matrix decomposition for multi-view data
    • [stat.ME]Estimating latent linear correlations from fuzzy frequency tables
    • [stat.ME]Estimating the Design Operating Characteristics in Clinical Trials with the Ordinal Scale Disease Progression Endpoint
    • [stat.ME]Granger Causality: A Review and Recent Advances
    • [stat.ME]Robust Estimation of Heterogeneous Treatment Effects using Electronic Health Record Data
    • [stat.ME]The 今日学术视野(2021.5.11) - 图3-value: evaluating stability with respect to distributional shifts
    • [stat.ML]Geometric convergence of elliptical slice sampling
    • [stat.ML]Kernel MMD Two-Sample Tests for Manifold Data
    • [stat.ML]Pairwise Fairness for Ordinal Regression
    • [stat.ML]Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions
    • [stat.ML]Use of High Dimensional Modeling for automatic variables selection: the best path algorithm
    • [stat.ML]What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory

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

    • [cs.AI]AI in (and for) Games
    Kostas Karpouzis, George Tsatiris
    http://arxiv.org/abs/2105.03123v1

    • [cs.AI]Accelerating Entrepreneurial Decision-Making Through Hybrid Intelligence
    Dominik Dellermann
    http://arxiv.org/abs/2105.03365v1

    • [cs.AI]An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020)
    Gauthier Chassang, Mogens Thomsen, Pierre Rumeau, Florence Sèdes, Alejandra Delfin
    http://arxiv.org/abs/2105.03192v1

    • [cs.AI]Design principles for a hybrid intelligence decision support system for business model validation
    Dominik Dellermann, Nikolaus Lipusch, Philipp Ebel, Jan Marco Leimeister
    http://arxiv.org/abs/2105.03356v1

    • [cs.AI]Finding the unicorn: Predicting early stage startup success through a hybrid intelligence method
    Dominik Dellermann, Nikolaus Lipusch, Philipp Ebel, Karl Michael Popp, Jan Marco Leimeister
    http://arxiv.org/abs/2105.03360v1

    • [cs.AI]Solving the Workflow Satisfiability Problem using General Purpose Solvers
    Daniel Karapetyan, Gregory Gutin
    http://arxiv.org/abs/2105.03273v1

    • [cs.AI]The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systems
    Dominik Dellermann, Adrian Calma, Nikolaus Lipusch, Thorsten Weber, Sascha Weigel, Philipp Ebel
    http://arxiv.org/abs/2105.03354v1

    • [cs.AI]Using reinforcement learning to design an AI assistantfor a satisfying co-op experience
    Ajay Krishnan, Niranj Jyothish, Xun Jia
    http://arxiv.org/abs/2105.03414v1

    • [cs.CL]今日学术视野(2021.5.11) - 图4
    Mokanarangan Thayaparan, Marco Valentino, Deborah Ferreira, Julia Rozanova, André Freitas
    http://arxiv.org/abs/2105.03417v1

    • [cs.CL]A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect
    Binbin Xu, Chongyang Tao, Zidu Feng, Youssef Raqui, Sylvie Ranwez
    http://arxiv.org/abs/2105.03409v1

    • [cs.CL]A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers
    Pradeep Dasigi, Kyle Lo, Iz Beltagy, Arman Cohan, Noah A. Smith, Matt Gardner
    http://arxiv.org/abs/2105.03011v1

    • [cs.CL]A Grounded Approach to Modeling Generic Knowledge Acquisition
    Deniz Beser, Joe Cecil, Marjorie Freedman, Jacob Lichtefeld, Mitch Marcus, Sarah Payne, Charles Yang
    http://arxiv.org/abs/2105.03207v1

    • [cs.CL]A Survey of Data Augmentation Approaches for NLP
    Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, Eduard Hovy
    http://arxiv.org/abs/2105.03075v1

    • [cs.CL]AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection Dataset
    Mohamed Seghir Hadj Ameur, Hassina Aliane
    http://arxiv.org/abs/2105.03143v1

    • [cs.CL]Are Pre-trained Convolutions Better than Pre-trained Transformers?
    Yi Tay, Mostafa Dehghani, Jai Gupta, Dara Bahri, Vamsi Aribandi, Zhen Qin, Donald Metzler
    http://arxiv.org/abs/2105.03322v1

    • [cs.CL]Do language models learn typicality judgments from text?
    Kanishka Misra, Allyson Ettinger, Julia Taylor Rayz
    http://arxiv.org/abs/2105.02987v1

    • [cs.CL]Efficient Weight factorization for Multilingual Speech Recognition
    Ngoc-Quan Pham, Tuan-Nam Nguyen, Sebastian Stueker, Alexander Waibel
    http://arxiv.org/abs/2105.03010v1

    • [cs.CL]Graph-based Multilingual Product Retrieval in E-commerce Search
    Hanqing Lu, Youna Hu, Tong Zhao, Tony Wu, Yiwei Song, Bing Yin
    http://arxiv.org/abs/2105.02978v1

    • [cs.CL]Hone as You Read: A Practical Type of Interactive Summarization
    Tanner Bohn, Charles X. Ling
    http://arxiv.org/abs/2105.02923v1

    • [cs.CL]Identity Signals in Emoji Do not Influence Perception of Factual Truth on Twitter
    Alexander Robertson, Walid Magdy, Sharon Goldwater
    http://arxiv.org/abs/2105.03160v1

    • [cs.CL]On the logistical difficulties and findings of Jopara Sentiment Analysis
    Marvin M. Agüero-Torales, David Vilares, Antonio G. López-Herrera
    http://arxiv.org/abs/2105.02947v1

    • [cs.CL]On-the-Fly Controlled Text Generation with Experts and Anti-Experts
    Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, Yejin Choi
    http://arxiv.org/abs/2105.03023v1

    • [cs.CL]Regression Bugs Are In Your Model! Measuring, Reducing and Analyzing Regressions In NLP Model Updates
    Yuqing Xie, Yi-an Lai, Yuanjun Xiong, Yi Zhang, Stefano Soatto
    http://arxiv.org/abs/2105.03048v1

    • [cs.CL]SpeechNet: A Universal Modularized Model for Speech Processing Tasks
    Yi-Chen Chen, Po-Han Chi, Shu-wen Yang, Kai-Wei Chang, Jheng-hao Lin, Sung-Feng Huang, Da-Rong Liu, Chi-Liang Liu, Cheng-Kuang Lee, Hung-yi Lee
    http://arxiv.org/abs/2105.03070v1

    • [cs.CL]The Shadowy Lives of Emojis: An Analysis of a Hacktivist Collective’s Use of Emojis on Twitter
    Keenan Jones, Jason R. C. Nurse, Shujun Li
    http://arxiv.org/abs/2105.03168v1

    • [cs.CL]VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension
    Haoyang Wen, Anthony Ferritto, Heng Ji, Radu Florian, Avirup Sil
    http://arxiv.org/abs/2105.03229v1

    • [cs.CR]A Cybersecurity Guide for Using Fitness Devices
    Maria Bada, Basie von Solms
    http://arxiv.org/abs/2105.02933v1

    • [cs.CR]A DLT-based Smart Contract Architecture for Atomic and Scalable Trading
    J. Kalbantner, K. Markantonakis, D. Hurley-Smith, C. Shepherd, B. Semal
    http://arxiv.org/abs/2105.02937v1

    • [cs.CV]A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: from Traditional Image Processing and Classical Machine Learning to Current Deep Convolutional Neural Networks and Potential Visual Transformers
    Chen Li, Pingli Ma, Md Mamunur Rahaman, Yudong Yao, Jiawei Zhang, Shuojia Zou, Xin Zhao, Marcin Grzegorzek
    http://arxiv.org/abs/2105.03148v1

    • [cs.CV]A^2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentation
    Miao Hu, Yali Li, Lu Fang, Shengjin Wang
    http://arxiv.org/abs/2105.03186v1

    • [cs.CV]Adaptive Domain-Specific Normalization for Generalizable Person Re-Identification
    Jiawei Liu, Zhipeng Huang, Kecheng Zheng, Dong Liu, Xiaoyan Sun, Zheng-Jun Zha
    http://arxiv.org/abs/2105.03042v1

    • [cs.CV]Adaptive Focus for Efficient Video Recognition
    Yulin Wang, Zhaoxi Chen, Haojun Jiang, Shiji Song, Yizeng Han, Gao Huang
    http://arxiv.org/abs/2105.03245v1

    • [cs.CV]Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition
    Bangjie Yin, Wenxuan Wang, Taiping Yao, Junfeng Guo, Zelun Kong, Shouhong Ding, Jilin Li, Cong Liu
    http://arxiv.org/abs/2105.03162v1

    • [cs.CV]An Intelligent Passive Food Intake Assessment System with Egocentric Cameras
    Frank Po Wen Lo, Modou L Jobarteh, Yingnan Sun, Jianing Qiu, Shuo Jiang, Gary Frost, Benny Lo
    http://arxiv.org/abs/2105.03142v1

    • [cs.CV]Autoencoder Based Inter-Vehicle Generalization for In-Cabin Occupant Classification
    Steve Dias Da Cruz, Bertram Taetz, Oliver Wasenmüller, Thomas Stifter, Didier Stricker
    http://arxiv.org/abs/2105.03164v1

    • [cs.CV]Contrastive Learning for Unsupervised Image-to-Image Translation
    Hanbit Lee, Jinseok Seol, Sang-goo Lee
    http://arxiv.org/abs/2105.03117v1

    • [cs.CV]Efficient Masked Face Recognition Method during the COVID-19 Pandemic
    Walid Hariri
    http://arxiv.org/abs/2105.03026v1

    • [cs.CV]Exploring Instance Relations for Unsupervised Feature Embedding
    Yifei Zhang, Yu Zhou, Weiping Wang
    http://arxiv.org/abs/2105.03341v1

    • [cs.CV]Faster and Simpler Siamese Network for Single Object Tracking
    Shaokui Jiang, Baile Xu, Jian Zhao, Furao Shen
    http://arxiv.org/abs/2105.03049v1

    • [cs.CV]Few-Shot Learning for Image Classification of Common Flora
    Joshua Ball
    http://arxiv.org/abs/2105.03056v1

    • [cs.CV]Foreground-guided Facial Inpainting with Fidelity Preservation
    Jireh Jam, Connah Kendrick, Vincent Drouard, Kevin Walker, Moi Hoon Yap
    http://arxiv.org/abs/2105.03342v1

    • [cs.CV]Human Object Interaction Detection using Two-Direction Spatial Enhancement and Exclusive Object Prior
    Lu Liu, Robby T. Tan
    http://arxiv.org/abs/2105.03089v1

    • [cs.CV]Interpretable Social Anchors for Human Trajectory Forecasting in Crowds
    Parth Kothari, Brian Sifringer, Alexandre Alahi
    http://arxiv.org/abs/2105.03136v1

    • [cs.CV]MOTR: End-to-End Multiple-Object Tracking with TRansformer
    Fangao Zeng, Bin Dong, Tiancai Wang, Cheng Chen, Xiangyu Zhang, Yichen Wei
    http://arxiv.org/abs/2105.03247v1

    • [cs.CV]More Separable and Easier to Segment: A Cluster Alignment Method for Cross-Domain Semantic Segmentation
    Shuang Wang, Dong Zhao, Yi Li, Chi Zhang, Yuwei Guo, Qi Zang, Biao Hou, Licheng Jiao
    http://arxiv.org/abs/2105.03151v1

    • [cs.CV]Neural 3D Scene Compression via Model Compression
    Berivan Isik
    http://arxiv.org/abs/2105.03120v1

    • [cs.CV]Probabilistic Ranking-Aware Ensembles for Enhanced Object Detections
    Mingyuan Mao, Baochang Zhang, David Doermann, Jie Guo, Shumin Han, Yuan Feng, Xiaodi Wang, Errui Ding
    http://arxiv.org/abs/2105.03139v1

    • [cs.CV]Probabilistic Visual Place Recognition for Hierarchical Localization
    Ming Xu, Niko Sünderhauf, Michael Milford
    http://arxiv.org/abs/2105.03091v1

    • [cs.CV]ResMLP: Feedforward networks for image classification with data-efficient training
    Hugo Touvron, Piotr Bojanowski, Mathilde Caron, Matthieu Cord, Alaaeldin El-Nouby, Edouard Grave, Armand Joulin, Gabriel Synnaeve, Jakob Verbeek, Hervé Jégou
    http://arxiv.org/abs/2105.03404v1

    • [cs.CV]Salient Objects in Clutter
    Deng-Ping Fan, Jing Zhang, Gang Xu, Ming-Ming Cheng, Ling Shao
    http://arxiv.org/abs/2105.03053v1

    • [cs.CV]Self-paced Resistance Learning against Overfitting on Noisy Labels
    Xiaoshuang Shi, Zhenhua Guo, Fuyong Xing, Yun Liang, Xiaofeng Zhu
    http://arxiv.org/abs/2105.03059v1

    • [cs.CV]Toward Interactive Modulation for Photo-Realistic Image Restoration
    Haoming Cai, Jingwen He, Qiao Yu, Chao Dong
    http://arxiv.org/abs/2105.03085v1

    • [cs.CV]Towards Real-World Category-level Articulation Pose Estimation
    Liu Liu, Han Xue, Wenqiang Xu, Haoyuan Fu, Cewu Lu
    http://arxiv.org/abs/2105.03260v1

    • [cs.CY]Digital Voodoo Dolls
    Marija Slavkovik, Clemens Stachl, Caroline Pitman, Jonathan Askonas
    http://arxiv.org/abs/2105.02738v2

    • [cs.CY]Profiling the Cybercriminal: A Systematic Review of Research
    Maria Bada, Jason R. C. Nurse
    http://arxiv.org/abs/2105.02930v1

    • [cs.CY]fAshIon after fashion: A Report of AI in Fashion
    Xingxing Zou, Waikeung Wong
    http://arxiv.org/abs/2105.03050v1

    • [cs.DC]Autonomic Management of Power Consumption with IoT and Fog Computing
    Hugo Vaz Sampaio, Fernando Koch, Carlos Becker Westphall, Ricardo do Nascimento Boing, Rene Nolio Santa Cruz
    http://arxiv.org/abs/2105.03009v1

    • [cs.DC]Clock Synchronization in Virtualized Distributed Real-Time Systems using IEEE 802.1AS and ACRN
    Jan Ruh, Wilfried Steiner, Gerhard Fohler
    http://arxiv.org/abs/2105.03374v1

    • [cs.DC]Data-driven scheduling in serverless computing to reduce response time
    Bartłomiej Przybylski, Paweł Żuk, Krzysztof Rzadca
    http://arxiv.org/abs/2105.03217v1

    • [cs.DC]Leader Election in Arbitrarily Connected Networks with Process Crashes and Weak Channel Reliability
    Carlos López, Sergio Rajsbaum, Michel Raynal, Karla Vargas
    http://arxiv.org/abs/2105.02972v1

    • [cs.DC]Simulation and evaluation of cloud storage caching for data intensive science
    Tobias Wegner, Mario Lassnig, Peer Ueberholz, Christian Zeitnitz
    http://arxiv.org/abs/2105.03201v1

    • [cs.FL]Executable Interval Temporal Logic Specifications
    Antonio Cau, Stefan Kuhn, James Hoey
    http://arxiv.org/abs/2105.03375v1

    • [cs.HC]Everyday algorithm auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviors
    Hong Shen, Alicia DeVos, Motahhare Eslami, Kenneth Holstein
    http://arxiv.org/abs/2105.02980v1

    • [cs.IR]A Multi-Objective Optimization Method for Achieving Two-sided Fairness in E-commerce Recommendation
    Haolun Wu, Chen Ma, Bhaskar Mitra, Fernando Diaz, Xue Liu
    http://arxiv.org/abs/2105.02951v1

    • [cs.IR]DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation
    Lei Guo, Li Tang, Tong Chen, Lei Zhu, Quoc Viet Hung Nguyen, Hongzhi Yin
    http://arxiv.org/abs/2105.03300v1

    • [cs.IR]Users’ Perception of Search Engine Biases and Satisfaction
    Bin Han, Chirag Shah, Daniel Saelid
    http://arxiv.org/abs/2105.02898v1

    • [cs.IT]Achievable Physical-Layer Secrecy in Multi-Mode Fiber Channels using Artificial Noise
    Eduard Jorswieck, Andrew Lonnstrom, Karl-Ludwig Besser, Stefan Rothe, Juergen W. Czarske
    http://arxiv.org/abs/2105.03137v1

    • [cs.IT]Coded Gradient Aggregation: A Tradeoff Between Communication Costs at Edge Nodes and at Helper Nodes
    Birenjith Sasidharan, Anoop Thomas
    http://arxiv.org/abs/2105.02919v1

    • [cs.IT]Communication With Adversary Identification in Byzantine Multiple Access Channels
    Neha Sangwan, Mayank Bakshi, Bikash Kumar Dey, Vinod M. Prabhakaran
    http://arxiv.org/abs/2105.03380v1

    • [cs.IT]Compound Arbitrarily Varying Channels
    Syomantak Chaudhuri, Neha Sangwan, Mayank Bakshi, Bikash Kumar Dey, Vinod M. Prabhakaran
    http://arxiv.org/abs/2105.03420v1

    • [cs.IT]Content Caching for Shared Medium Networks Under Heterogeneous Users’ Behaviours
    Abdollah Ghaffari Sheshjavani, Ahmad Khonsari, Seyed Pooya Shariatpanahi, Masoumeh Moradian
    http://arxiv.org/abs/2105.03220v1

    • [cs.IT]Hierarchical sparse recovery from hierarchically structured measurements with application to massive random access
    Benedikt Groß, Axel Flinth, Ingo Roth, Jens Eisert, Gerhard Wunder
    http://arxiv.org/abs/2105.03169v1

    • [cs.IT]Integrated Sensing and Communication with Multi-Domain Cooperation
    Jie Yang, Xi Yang, Chao-Kai Wen, Shi Jin
    http://arxiv.org/abs/2105.03065v1

    • [cs.IT]Leakage-Resilient Secret Sharing with Constant Share Size
    Ivan Tjuawinata, Chaoping Xing
    http://arxiv.org/abs/2105.03074v1

    • [cs.IT]Maximally Recoverable Codes with Hierarchical Locality: Constructions and Field-Size Bounds
    D. Shivakrishna, Aaditya M. Nair, V. Lalitha
    http://arxiv.org/abs/2105.03328v1

    • [cs.IT]On interpolation-based decoding of a class of maximum rank distance codes
    Wrya K. Kadir, Chunlei Li, Ferdinando Zullo
    http://arxiv.org/abs/2105.03115v1

    • [cs.IT]Online Multi-Cell Coordinated MIMO Wireless Network Virtualization with Imperfect CSI
    Juncheng Wang, Ben Liang, Min Dong, Gary Boudreau
    http://arxiv.org/abs/2105.03306v1

    • [cs.IT]RIS-Aided Cell-Free Massive MIMO: Performance Analysis and Competitiveness
    Bayan Al-Nahhas, Mohannad Obeed, Anas Chaaban, Md. Jahangir Hossain
    http://arxiv.org/abs/2105.02986v1

    • [cs.IT]Retrieving Data Permutations from Noisy Observations: High and Low Noise Asymptotics
    Minoh Jeong, Alex Dytso, Martina Cardone
    http://arxiv.org/abs/2105.03015v1

    • [cs.IT]When an Energy-Efficient Scheduling is Optimal for Half-Duplex Relay Networks?
    Sarthak Jain, Martina Cardone, Soheil Mohajer
    http://arxiv.org/abs/2105.03064v1

    • [cs.LG]A Family of Hybrid Federated and Centralized Learning Architectures in Machine Learning
    Ahmet M. Elbir, Sinem Coleri
    http://arxiv.org/abs/2105.03288v1

    • [cs.LG]A Survey of Applied Machine Learning Techniques for Optical OFDM based Networks
    Hichem Mrabet, Elias Giaccoumidis, Iyad Dayoub
    http://arxiv.org/abs/2105.03289v1

    • [cs.LG]ANNETTE: Accurate Neural Network Execution Time Estimation with Stacked Models
    Matthias Wess, Matvey Ivanov, Anvesh Nookala, Christoph Unger, Alexander Wendt, Axel Jantsch
    http://arxiv.org/abs/2105.03176v1

    • [cs.LG]Adapting by Pruning: A Case Study on BERT
    Yang Gao, Nicolo Colombo, Wei Wang
    http://arxiv.org/abs/2105.03343v1

    • [cs.LG]An Influence-based Approach for Root Cause Alarm Discovery in Telecom Networks
    Keli Zhang, Marcus Kalander, Min Zhou, Xi Zhang, Junjian Ye
    http://arxiv.org/abs/2105.03092v1

    • [cs.LG]ConCAD: Contrastive Learning-based Cross Attention for Sleep Apnea Detection
    Guanjie Huang, Fenglong Ma
    http://arxiv.org/abs/2105.03037v1

    • [cs.LG]Context-Based Soft Actor Critic for Environments with Non-stationary Dynamics
    Yuan Pu, Shaochen Wang, Xin Yao, Bin Li
    http://arxiv.org/abs/2105.03310v1

    • [cs.LG]Diff-ResNets for Few-shot Learning — an ODE Perspective
    Tangjun Wang, Zehao Dou, Chenglong Bao, Zuoqiang Shi
    http://arxiv.org/abs/2105.03155v1

    • [cs.LG]Differential Privacy for Pairwise Learning: Non-convex Analysis
    Yilin Kang, Yong Liu, Jian Li, Weiping Wang
    http://arxiv.org/abs/2105.03033v1

    • [cs.LG]Energy-Based Anomaly Detection and Localization
    Ergin Utku Genc, Nilesh Ahuja, Ibrahima J Ndiour, Omesh Tickoo
    http://arxiv.org/abs/2105.03270v1

    • [cs.LG]Error-Robust Multi-View Clustering: Progress, Challenges and Opportunities
    Mehrnaz Najafi, Lifang He, Philip S. Yu
    http://arxiv.org/abs/2105.03058v1

    • [cs.LG]Exact Acceleration of K-Means++ and K-Means
    Edward Raff
    http://arxiv.org/abs/2105.02936v1

    • [cs.LG]FVM Network to Reduce Computational Cost of CFD Simulation
    Joongoo Jeon, Sung Joong Kim
    http://arxiv.org/abs/2105.03332v1

    • [cs.LG]FedGL: Federated Graph Learning Framework with Global Self-Supervision
    Chuan Chen, Weibo Hu, Ziyue Xu, Zibin Zheng
    http://arxiv.org/abs/2105.03170v1

    • [cs.LG]GANTL: Towards Practical and Real-Time Topology Optimization with Conditional GANs and Transfer Learning
    Mohammad Mahdi Behzadi, Horea T. Ilies
    http://arxiv.org/abs/2105.03045v1

    • [cs.LG]Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks
    Gongxu Luo, Jianxin Li, Hao Peng, Carl Yang, Lichao Sun, Philip S. Yu, Lifang He
    http://arxiv.org/abs/2105.03178v1

    • [cs.LG]Hierarchical Graph Neural Networks
    Stanislav Sobolevsky
    http://arxiv.org/abs/2105.03388v1

    • [cs.LG]Laplace Matching for fast Approximate Inference in Generalized Linear Models
    Marius Hobbhahn, Philipp Hennig
    http://arxiv.org/abs/2105.03109v1

    • [cs.LG]Learning Controllable Content Generators
    Sam Earle, Maria Edwards, Ahmed Khalifa, Philip Bontrager, Julian Togelius
    http://arxiv.org/abs/2105.02993v1

    • [cs.LG]Leveraging Multiple Relations for Fashion TrendForecasting Based on Social Media
    Yujuan Ding, Yunshan Ma, Lizi Liao, Wai Keung Wong, Tat-Seng Chua
    http://arxiv.org/abs/2105.03299v1

    • [cs.LG]Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts
    Weinan Zhang, Xihuai Wang, Jian Shen, Ming Zhou
    http://arxiv.org/abs/2105.03363v1

    • [cs.LG]Network Pruning That Matters: A Case Study on Retraining Variants
    Duong H. Le, Binh-Son Hua
    http://arxiv.org/abs/2105.03193v1

    • [cs.LG]Order in the Court: Explainable AI Methods Prone to Disagreement
    Michael Neely, Stefan F. Schouten, Maurits J. R. Bleeker, Ana Lucic
    http://arxiv.org/abs/2105.03287v1

    • [cs.LG]PEMNET: A Transfer Learning-based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems
    Luis A. Briceno-Mena, Christopher G. Arges, Jose A. Romagnoli
    http://arxiv.org/abs/2105.03057v1

    • [cs.LG]Reward prediction for representation learning and reward shaping
    Hlynur Davíð Hlynsson, Laurenz Wiskott
    http://arxiv.org/abs/2105.03172v1

    • [cs.LG]Text similarity analysis for evaluation of descriptive answers
    Vedant Bahel, Achamma Thomas
    http://arxiv.org/abs/2105.02935v1

    • [cs.LG]Utilizing Skipped Frames in Action Repeats via Pseudo-Actions
    Taisei Hashimoto, Yoshimasa Tsuruoka
    http://arxiv.org/abs/2105.03041v1

    • [cs.LG]Weather impact on daily cases of COVID-19 in Saudi Arabia using machine learning
    Abdullah Alsuhaibani, Abdulrahman Alhaidari
    http://arxiv.org/abs/2105.03027v1

    • [cs.MA]Informational Design of Dynamic Multi-Agent System
    Tao Zhang, Quanyan Zhu
    http://arxiv.org/abs/2105.03052v1

    • [cs.NE]An Extended Jump Function Benchmark for the Analysis of Randomized Search Heuristics
    Henry Bambury, Antoine Bultel, Benjamin Doerr
    http://arxiv.org/abs/2105.03090v1

    • [cs.NE]Semantics in Multi-objective Genetic Programming
    Edgar Galván, Leonardo Trujillo, Fergal Stapleton
    http://arxiv.org/abs/2105.02944v1

    • [cs.RO]CoDE: Collocation for Demonstration Encoding
    Mandy Xie, Anqi Li, Karl Van Wyk, Frank Dellaert, Byron Boots, Nathan Ratliff
    http://arxiv.org/abs/2105.03019v1

    • [cs.RO]LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping
    Ozan Çatal, Wouter Jansen, Tim Verbelen, Bart Dhoedt, Jan Steckel
    http://arxiv.org/abs/2105.03265v1

    • [cs.RO]Sobi: An Interactive Social Service Robot for Long-Term Autonomy in Open Environments
    Marvin Stuede, Konrad Westermann, Moritz Schappler, Svenja Spindeldreier
    http://arxiv.org/abs/2105.03242v1

    • [cs.RO]VIRAL SLAM: Tightly Coupled Camera-IMU-UWB-Lidar SLAM
    Thien-Minh Nguyen, Shenghai Yuan, Muqing Cao, Thien Hoang Nguyen, Lihua Xie
    http://arxiv.org/abs/2105.03296v1

    • [cs.RO]iCub
    Lorenzo Natale, Chiara Bartolozzi, Francesco Nori, Giulio Sandini, Giorgio Metta
    http://arxiv.org/abs/2105.02313v2

    • [cs.SD]SpeechMoE: Scaling to Large Acoustic Models with Dynamic Routing Mixture of Experts
    Zhao You, Shulin Feng, Dan Su, Dong Yu
    http://arxiv.org/abs/2105.03036v1

    • [cs.SE]Code2Image: Intelligent Code Analysis by Computer Vision Techniques and Application to Vulnerability Prediction
    Zeki Bilgin
    http://arxiv.org/abs/2105.03131v1

    • [cs.SE]Detecting Security Fixes in Open-Source Repositories using Static Code Analyzers
    Therese Fehrer, Rocío Cabrera Lozoya, Antonino Sabetta, Dario Di Nucci, Damian A. Tamburri
    http://arxiv.org/abs/2105.03346v1

    • [cs.SI]An Axiom System for Feedback Centralities
    Tomasz Wąs, Oskar Skibski
    http://arxiv.org/abs/2105.03146v1

    • [cs.SI]Comparison of Traditional and Hybrid Time Series Models for Forecasting COVID-19 Cases
    Samyak Prajapati, Aman Swaraj, Ronak Lalwani, Akhil Narwal, Karan Verma, Ghanshyam Singh, Ashok Kumar
    http://arxiv.org/abs/2105.03266v1

    • [cs.SI]Identifying critical higher-order interactions in complex networks
    Mehmet Emin Aktas, Thu Nguyen, Sidra Jawaid, Rakin Riza, Esra Akbas
    http://arxiv.org/abs/2105.02763v2

    • [eess.IV]DeepRF: Deep Reinforcement Learning Designed RadioFrequency Waveform in MRI
    Dongmyung Shin, Younghoon Kim, Chungseok Oh, Hongjun An, Juhyung Park, Jiye Kim, Jongho Lee
    http://arxiv.org/abs/2105.03061v1

    • [eess.IV]LINN: Lifting Inspired Invertible Neural Network for Image Denoising
    Jun-Jie Huang, Pier Luigi Dragotti
    http://arxiv.org/abs/2105.03303v1

    • [eess.IV]NTIRE 2021 Challenge on Perceptual Image Quality Assessment
    Jinjin Gu, Haoming Cai, Chao Dong, Jimmy S. Ren, Yu Qiao, Shuhang Gu, Radu Timofte, Manri Cheon, Sungjun Yoon, Byungyeon Kangg Kang, Junwoo Lee, Qing Zhang, Haiyang Guo, Yi Bin, Yuqing Hou, Hengliang Luo, Jingyu Guo, Zirui Wang, Hai Wang, Wenming Yang, Qingyan Bai, Shuwei Shi, Weihao Xia, Mingdeng Cao, Jiahao Wang, Yifan Chen, Yujiu Yang, Yang Li, Tao Zhang, Longtao Feng, Yiting Liao, Junlin Li, William Thong, Jose Costa Pereira, Ales Leonardis, Steven McDonagh, Kele Xu, Lehan Yang, Hengxing Cai, Pengfei Sun, Seyed Mehdi Ayyoubzadeh, Ali Royat, Sid Ahmed Fezza, Dounia Hammou, Wassim Hamidouche, Sewoong Ahn, Gwangjin Yoon, Koki Tsubota, Hiroaki Akutsu, Kiyoharu Aizawa
    http://arxiv.org/abs/2105.03072v1

    • [eess.IV]Self-Adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images
    Yiming Bao, Jun Wang, Tong Li, Linyan Wang, Jianwei Xu, Juan Ye, Dahong Qian
    http://arxiv.org/abs/2105.03068v1

    • [eess.IV]Structured dataset documentation: a datasheet for CheXpert
    Christian Garbin, Pranav Rajpurkar, Jeremy Irvin, Matthew P. Lungren, Oge Marques
    http://arxiv.org/abs/2105.03020v1

    • [eess.SY]A Multivariate Density Forecast Approach for Online Power System Security Assessment
    Zichao Meng, Ye Guo, Wenjun Tang, Hongbin Sun, Wenqi Huang
    http://arxiv.org/abs/2105.03047v1

    • [eess.SY]Learning-enhanced robust controller synthesis with rigorous statistical and control-theoretic guarantees
    Christian Fiedler, Carsten W. Scherer, Sebastian Trimpe
    http://arxiv.org/abs/2105.03397v1

    • [hep-ex]Building a Distributed Computing System for LDMX: Challenges of creating and operating a lightweight e-infrastructure for small-to-medium size accelerator experiments
    Lene Kristian Bryngemark, David Cameron, Valentina Dutta, Thomas Eichlersmith, Balazs Konya, Omar Moreno, Geoffrey Mullier, Florido Paganelli, Ruth Pöttgen, Fuzzy Rogers, Andrii Salnikov, Paul Weakliem
    http://arxiv.org/abs/2105.02977v1

    • [hep-lat]Deep Learning Hamiltonian Monte Carlo
    Sam Foreman, Xiao-Yong Jin, James C. Osborn
    http://arxiv.org/abs/2105.03418v1

    • [math.CT]Lambek pregroups are Frobenius spiders in preorders
    Dusko Pavlovic
    http://arxiv.org/abs/2105.03038v1

    • [math.NA]Estimate the spectrum of affine dynamical systems from partial observations of a single trajectory data
    Jiahui Cheng, Sui Tang
    http://arxiv.org/abs/2105.02945v1

    • [math.OC]Neural network architectures using min plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs
    Jérôme Darbon, Peter M. Dower, Tingwei Meng
    http://arxiv.org/abs/2105.03336v1

    • [math.ST]Circuit bases for randomisation
    Elena Pesce, Fabio Rapallo, Eva Riccomagno, Henry P. Wynn
    http://arxiv.org/abs/2105.03102v1

    • [math.ST]Consistent estimation of distribution functions under increasing concave and convex stochastic ordering
    Alexander Henzi
    http://arxiv.org/abs/2105.03101v1

    • [math.ST]From Graph Centrality to Data Depth
    Eddie Aamari, Ery Arias-Castro, Clément Berenfeld
    http://arxiv.org/abs/2105.03122v1

    • [physics.soc-ph]Meta-validation of bipartite network projections
    Giulio Cimini, Alessandro Carra, Luca Didomenicantonio, Andrea Zaccaria
    http://arxiv.org/abs/2105.03391v1

    • [physics.soc-ph]The Dynamics of Faculty Hiring Networks
    Eun Lee, Aaron Clauset, Daniel B. Larremore
    http://arxiv.org/abs/2105.02949v1

    • [q-bio.QM]Interpretable machine learning for high-dimensional trajectories of aging health
    Spencer Farrell, Arnold Mitnitski, Kenneth Rockwood, Andrew Rutenberg
    http://arxiv.org/abs/2105.03410v1

    • [stat.AP]A Non-Compensatory Random Utility Choice Model based on Choquet Integral
    Subodh Dubey, Oded Cats, Serge Hoogendoorn, Prateek Bansal
    http://arxiv.org/abs/2105.03275v1

    • [stat.AP]Calibration of Spatial Forecasts from Citizen Science Urban Air Pollution Data with Sparse Recurrent Neural Networks
    Matthew Bonas, Stefano Castruccio
    http://arxiv.org/abs/2105.02971v1

    • [stat.AP]Primary analysis method for incomplete CD4 count data from IMPI trial and other trials with similar setting
    Abdul-Karim Iddrisu, Abukari Alhassan
    http://arxiv.org/abs/2105.03197v1

    • [stat.CO]SEAGLE: A Scalable Exact Algorithm for Large-Scale Set-based GxE Tests in Biobank Data
    Jocelyn T. Chi, Ilse C. F. Ipsen, Tzu-Hung Hsiao, Ching-Heng Lin, Li-San Wang, Wan-Ping Lee, Tzu-Pin Lu, Jung-Ying Tzeng
    http://arxiv.org/abs/2105.03228v1

    • [stat.ME]An Objective Prior from a Scoring Rule
    Stephen G. Walker, Cristiano Villa
    http://arxiv.org/abs/2105.03241v1

    • [stat.ME]Bayesian spatio-temporal model for high-resolution short-term forecasting of precipitation fields
    Stephen Richard Johnson, Sarah Elizabeth Heaps, Kevin James Wilson, Darren James Wilkinson
    http://arxiv.org/abs/2105.03269v1

    • [stat.ME]Double-matched matrix decomposition for multi-view data
    Dongbang Yuan, Irina Gaynanova
    http://arxiv.org/abs/2105.03396v1

    • [stat.ME]Estimating latent linear correlations from fuzzy frequency tables
    Antonio Calcagnì
    http://arxiv.org/abs/2105.03309v1

    • [stat.ME]Estimating the Design Operating Characteristics in Clinical Trials with the Ordinal Scale Disease Progression Endpoint
    Shirin Golchi
    http://arxiv.org/abs/2105.03022v1

    • [stat.ME]Granger Causality: A Review and Recent Advances
    Ali Shojaie, Emily B. Fox
    http://arxiv.org/abs/2105.02675v2

    • [stat.ME]Robust Estimation of Heterogeneous Treatment Effects using Electronic Health Record Data
    Ruohong Li, Honglang Wang, Wanzhu Tu
    http://arxiv.org/abs/2105.03325v1

    • [stat.ME]The -value: evaluating stability with respect to distributional shifts
    Suyash Gupta, Dominik Rothenhäusler
    http://arxiv.org/abs/2105.03067v1

    • [stat.ML]Geometric convergence of elliptical slice sampling
    Viacheslav Natarovskii, Daniel Rudolf, Björn Sprungk
    http://arxiv.org/abs/2105.03308v1

    • [stat.ML]Kernel MMD Two-Sample Tests for Manifold Data
    Xiuyuan Cheng, Yao Xie
    http://arxiv.org/abs/2105.03425v1

    • [stat.ML]Pairwise Fairness for Ordinal Regression
    Matthäus Kleindessner, Samira Samadi, Muhammad Bilal Zafar, Krishnaram Kenthapadi, Chris Russell
    http://arxiv.org/abs/2105.03153v1

    • [stat.ML]Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions
    Dan Geiger, David Heckerman
    http://arxiv.org/abs/2105.03248v1

    • [stat.ML]Use of High Dimensional Modeling for automatic variables selection: the best path algorithm
    Luigi Riso
    http://arxiv.org/abs/2105.03173v1

    • [stat.ML]What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory
    Rahul Parhi, Robert D. Nowak
    http://arxiv.org/abs/2105.03361v1