astro-ph.IM - 仪器仪表和天体物理学方法

    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.DC - 分布式、并行与集群计算 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.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 econ.EM - 计量经济学 econ.TH - 理论经济学 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.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 q-bio.PE - 人口与发展 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

    • [astro-ph.IM]Tails: Chasing Comets with the Zwicky Transient Facility and Deep Learning
    • [cs.AI]Information algebras of coherent sets of gambles
    • [cs.AI]Multi-Agent Path Planning based on MPC and DDPG
    • [cs.AI]New Techniques that Improve ENIGMA-style Clause Selection Guidance
    • [cs.AI]Potential Impacts of Smart Homes on Human Behavior: A Reinforcement Learning Approach
    • [cs.CL]A Meta-embedding-based Ensemble Approach for ICD Coding Prediction
    • [cs.CL]ANEA: Distant Supervision for Low-Resource Named Entity Recognition
    • [cs.CL]Automated essay scoring using efficient transformer-based language models
    • [cs.CL]DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections
    • [cs.CL]Evaluate On-the-job Learning Dialogue Systems and a Case Study for Natural Language Understanding
    • [cs.CL]Gradient-guided Loss Masking for Neural Machine Translation
    • [cs.CL]Learning Chess Blindfolded: Evaluating Language Models on State Tracking
    • [cs.CL]Methods for the Design and Evaluation of HCI+NLP Systems
    • [cs.CL]Multi-task transfer learning for finding actionable information from crisis-related messages on social media
    • [cs.CL]Natural Language Video Localization: A Revisit in Span-based Question Answering Framework
    • [cs.CL]PharmKE: Knowledge Extraction Platform for Pharmaceutical Texts using Transfer Learning
    • [cs.CL]Predicting gender and age categories in English conversations using lexical, non-lexical, and turn-taking features
    • [cs.CR]GraphSense: A General-Purpose Cryptoasset Analytics Platform
    • [cs.CR]IoTMalware: Android IoT Malware Detection based on Deep Neural Network and Blockchain Technology
    • [cs.CV]A Reconfigurable Winograd CNN Accelerator with Nesting Decomposition Algorithm for Computing Convolution with Large Filters
    • [cs.CV]A Universal Model for Cross Modality Mapping by Relational Reasoning
    • [cs.CV]ACDnet: An action detection network for real-time edge computing based on flow-guided feature approximation and memory aggregation
    • [cs.CV]Accurate Visual-Inertial SLAM by Feature Re-identification
    • [cs.CV]Boundary-induced and scene-aggregated network for monocular depth prediction
    • [cs.CV]Class Knowledge Overlay to Visual Feature Learning for Zero-Shot Image Classification
    • [cs.CV]Continuous Face Aging Generative Adversarial Networks
    • [cs.CV]Domain Adapting Ability of Self-Supervised Learning for Face Recognition
    • [cs.CV]Dual-MTGAN: Stochastic and Deterministic Motion Transfer for Image-to-Video Synthesis
    • [cs.CV]Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images
    • [cs.CV]Knowledge Distillation Circumvents Nonlinearity for Optical Convolutional Neural Networks
    • [cs.CV]Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification
    • [cs.CV]Mitigating Domain Mismatch in Face Recognition Using Style Matching
    • [cs.CV]MixSearch: Searching for Domain Generalized Medical Image Segmentation Architectures
    • [cs.CV]Nested-block self-attention for robust radiotherapy planning segmentation
    • [cs.CV]Point Cloud Upsampling and Normal Estimation using Deep Learning for Robust Surface Reconstruction
    • [cs.CV]Surgical Visual Domain Adaptation: Results from the MICCAI 2020 SurgVisDom Challenge
    • [cs.CV]Unifying Remote Sensing Image Retrieval and Classification with Robust Fine-tuning
    • [cs.CV]Using Deep Learning to Automate the Detection of Flaws in Nuclear Fuel Channel UT Scans
    • [cs.CV]Where to look at the movies : Analyzing visual attention to understand movie editing
    • [cs.CV]Zero-Shot Learning Based on Knowledge Sharing
    • [cs.DC]CausalEC: A Causally Consistent Data Storage Algorithm based on Cross-Object Erasure Coding
    • [cs.DC]Checkpointing with cp: the POSIX Shared Memory System
    • [cs.DC]MEDAL: An AI-driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence
    • [cs.DC]On Register Linearizability and Termination
    • [cs.DC]VPIC 2.0: Next Generation Particle-in-Cell Simulations
    • [cs.GT]Classifying Convergence Complexity of Nash Equilibria in Graphical Games Using Distributed Computing Theory
    • [cs.HC]Images, Emotions, and Credibility: Effect of Emotional Facial Images on Perceptions of News Content Bias and Source Credibility in Social Media
    • [cs.IR]Open-domain question classification and completion in conversational information search
    • [cs.IR]SAED: Edge-Based Intelligence for Privacy-Preserving Enterprise Search on the Clou
    • [cs.IR]Variation Control and Evaluation for Generative SlateRecommendations
    • [cs.IT]Average Rate and Error Probability Analysis in Short Packet Communications over RIS-aided URLLC Systems
    • [cs.IT]DoA-LF: A Location Fingerprint Positioning Algorithm with Millimeter-Wave
    • [cs.IT]Double-IRS Aided MIMO Communication under LoS Channels: Capacity Maximization and Scaling
    • [cs.IT]Energy Efficiency Maximization in the Uplink Delta-OMA Networks
    • [cs.IT]Exact recovery of functions in refinable shift-invariant space by single-angle Radon samples
    • [cs.IT]Federated Edge Learning with Misaligned Over-The-Air Computation
    • [cs.IT]Oversampled Adaptive Sensing via a Predefined Codebook
    • [cs.IT]The Magic of Superposition: A Survey on the Simultaneous Transmission Based Wireless Systems
    • [cs.LG]今日学术视野(2021.3.2) - 图1: Explanations and Interactions from Conditional Expectations
    • [cs.LG]A Regret Minimization Approach to Iterative Learning Control
    • [cs.LG]Active Selection of Classification Features
    • [cs.LG]Adapting to misspecification in contextual bandits with offline regression oracles
    • [cs.LG]An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization
    • [cs.LG]Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion
    • [cs.LG]Doubly-Adaptive Thompson Sampling for Multi-Armed and Contextual Bandits
    • [cs.LG]Efficient Client Contribution Evaluation for Horizontal Federated Learning
    • [cs.LG]Experiments with Rich Regime Training for Deep Learning
    • [cs.LG]FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
    • [cs.LG]Graph-based Semi-supervised Learning: A Comprehensive Review
    • [cs.LG]History-Augmented Collaborative Filtering for Financial Recommendations
    • [cs.LG]Iterative SE(3)-Transformers
    • [cs.LG]Layer-Wise Interpretation of Deep Neural Networks Using Identity Initialization
    • [cs.LG]Low-Precision Reinforcement Learning
    • [cs.LG]Machine Biometrics — Towards Identifying Machines in a Smart City Environment
    • [cs.LG]Machine Unlearning via Algorithmic Stability
    • [cs.LG]Moreau-Yosida 今日学术视野(2021.3.2) - 图2-divergences
    • [cs.LG]NOMU: Neural Optimization-based Model Uncertainty
    • [cs.LG]Named Tensor Notation
    • [cs.LG]Neural Generalization of Multiple Kernel Learning
    • [cs.LG]Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks
    • [cs.LG]On the Generalization of Stochastic Gradient Descent with Momentum
    • [cs.LG]On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
    • [cs.LG]Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling
    • [cs.LG]Private and Utility Enhanced Recommendations with Local Differential Privacy and Gaussian Mixture Model
    • [cs.LG]Rip van Winkle’s Razor: A Simple Estimate of Overfit to Test Data
    • [cs.LG]Safe Distributional Reinforcement Learning
    • [cs.LG]Sparse approximation in learning via neural ODEs
    • [cs.LG]Swift for TensorFlow: A portable, flexible platform for deep learning
    • [cs.LG]Towards Robust and Reliable Algorithmic Recourse
    • [cs.LG]What Doesn’t Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors
    • [cs.NE]A Framework For Pruning Deep Neural Networks Using Energy-Based Models
    • [cs.NE]Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules
    • [cs.RO]Autonomous Quadrotor Flight despite Rotor Failure with Onboard Vision Sensors: Frames vs. Events
    • [cs.RO]CollisionIK: A Per-Instant Pose Optimization Method for Generating Robot Motions with Environment Collision Avoidance
    • [cs.RO]Efficient and Interpretable Robot Manipulation with Graph Neural Networks
    • [cs.RO]Learning Controller Gains on Bipedal Walking Robots via User Preferences
    • [cs.RO]Motion Planning for a Pair of Tethered Robots
    • [cs.RO]On the Visual-based Safe Landing of UAVs in Populated Areas: a Crucial Aspect for Urban Deployment
    • [cs.RO]Panoramic annular SLAM with loop closure and global optimization
    • [cs.RO]Robot Navigation in a Crowd by Integrating Deep Reinforcement Learning and Online Planning
    • [cs.RO]V-RVO: Decentralized Multi-Agent Collision Avoidance using Voronoi Diagrams and Reciprocal Velocity Obstacles
    1000
    • [cs.RO]Where to go next: Learning a Subgoal Recommendation Policy for Navigation Among Pedestrians
    • [cs.SD]The NPU System for the 2020 Personalized Voice Trigger Challenge
    • [cs.SD]Towards Explaining Expressive Qualities in Piano Recordings: Transfer of Explanatory Features via Acoustic Domain Adaptation
    • [cs.SE]Distribution-Aware Testing of Neural Networks Using Generative Models
    • [cs.SI]An organized review of key factors for fake news detection
    • [cs.SI]Contact Tracing: Computational Bounds, Limitations and Implications
    • [cs.SI]Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding
    • [econ.EM]General Bayesian time-varying parameter VARs for predicting government bond yields
    • [econ.EM]Permutation Tests at Nonparametric Rates
    • [econ.TH]Discord and Harmony in Networks
    • [eess.AS]Underwater Acoustic Communication Receiver Using Deep Belief Network
    • [eess.IV]3D Vessel Reconstruction in OCT-Angiography via Depth Map Estimation
    • [eess.IV]Convolution-Free Medical Image Segmentation using Transformers
    • [eess.IV]Robust Rational Polynomial Camera Modelling for SAR and Pushbroom Imaging
    • [eess.IV]Texture-aware Video Frame Interpolation
    • [eess.SP]NCH Sleep DataBank: A Large Collection of Real-world Pediatric Sleep Studies
    • [eess.SY]ECO: Enabling Energy-Neutral IoT Devices through Runtime Allocation of Harvested Energy
    • [math.NA]Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities
    • [math.OC]Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
    • [math.ST]Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
    • [math.ST]Nonparametric calibration for stochastic reaction-diffusion equations based on discrete observations
    • [math.ST]Semiparametric empirical likelihood inference with estimating equations under density ratio models
    • [q-bio.PE]Bioenergetics modelling to analyse and predict the joint effects of multiple stressors: Meta-analysis and model corroboration
    • [stat.AP]Coupling physical understanding and statistical modeling to estimate ice jam flood frequency in the northern Peace-Athabasca Delta under climate change
    • [stat.AP]Estimating Vaccine Efficacy Over Time After a Randomized Study is Unblinded
    • [stat.AP]Integrated Dataset of Brazilian Flights
    • [stat.AP]State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data
    • [stat.CO]Data-Free Likelihood-Informed Dimension Reduction of Bayesian Inverse Problems
    • [stat.ME]A multistate approach for mediation analysis in the presence of semi-competing risks with application in cancer survival disparities
    • [stat.ME]An introduction to the determination of the probability of a successful trial: Frequentist and Bayesian approaches
    • [stat.ME]Cholesky-based multivariate Gaussian regression
    • [stat.ME]Ensemble Conditional Variance Estimator for Sufficient Dimension Reduction
    • [stat.ME]Exploring the space-time pattern of log-transformed infectious count of COVID-19: a clustering-segmented autoregressive sigmoid model
    • [stat.ME]Fast and frugal time series forecasting
    • [stat.ME]Interpretable Sensitivity Analysis for Balancing Weights
    • [stat.ME]Reverse-Bayes methods: a review of recent technical advances
    • [stat.ME]Sparse Cholesky matrices in spatial statistics
    • [stat.ME]Variational Full Bayes Lasso: Knots Selection in Regression Splines
    • [stat.ME]Why did the distribution change?
    • [stat.ML]Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels
    • [stat.ML]Beware of the Simulated DAG! Varsortability in Additive Noise Models
    • [stat.ML]Consistent Sparse Deep Learning: Theory and Computation
    • [stat.ML]Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach
    • [stat.ML]Learning Prediction Intervals for Regression: Generalization and Calibration
    • [stat.ML]Learning with invariances in random features and kernel models
    • [stat.ML]MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA
    • [stat.ML]Spectral Top-Down Recovery of Latent Tree Models
    • [stat.ML]Streaming computation of optimal weak transport barycenters
    • [stat.ML]Zoetrope Genetic Programming for Regression
    • [stat.ML]sJIVE: Supervised Joint and Individual Variation Explained

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

    • [astro-ph.IM]Tails: Chasing Comets with the Zwicky Transient Facility and Deep Learning
    Dmitry A. Duev, Bryce T. Bolin, Matthew J. Graham, Michael S. P. Kelley, Ashish Mahabal, Eric C. Bellm, Michael W. Coughlin, Richard Dekany, George Helou, Shrinivas R. Kulkarni, Frank J. Masci, Thomas A. Prince, Reed Riddle, Maayane T. Soumagnac, Stéfan J. van der Walt
    http://arxiv.org/abs/2102.13352v1

    • [cs.AI]Information algebras of coherent sets of gambles
    Juerg Kohlas, Arianna Casanova, Marco Zaffalon
    http://arxiv.org/abs/2102.13368v1

    • [cs.AI]Multi-Agent Path Planning based on MPC and DDPG
    Junxiao Xue, Xiangyan Kong, Bowei Dong, Mingliang Xu
    http://arxiv.org/abs/2102.13283v1

    • [cs.AI]New Techniques that Improve ENIGMA-style Clause Selection Guidance
    Martin Suda
    http://arxiv.org/abs/2102.13564v1

    • [cs.AI]Potential Impacts of Smart Homes on Human Behavior: A Reinforcement Learning Approach
    Shashi Suman, Ali Etemad, Francois Rivest
    http://arxiv.org/abs/2102.13307v1

    • [cs.CL]A Meta-embedding-based Ensemble Approach for ICD Coding Prediction
    Pavithra Rajendran, Alexandros Zenonos, Josh Spear, Rebecca Pope
    http://arxiv.org/abs/2102.13622v1

    • [cs.CL]ANEA: Distant Supervision for Low-Resource Named Entity Recognition
    Michael A. Hedderich, Lukas Lange, Dietrich Klakow
    http://arxiv.org/abs/2102.13129v1

    • [cs.CL]Automated essay scoring using efficient transformer-based language models
    Christopher M Ormerod, Akanksha Malhotra, Amir Jafari
    http://arxiv.org/abs/2102.13136v1

    • [cs.CL]DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections
    Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, Ilya Eckstein
    http://arxiv.org/abs/2102.13247v1

    • [cs.CL]Evaluate On-the-job Learning Dialogue Systems and a Case Study for Natural Language Understanding
    Mathilde Veron, Sophie Rosset, Olivier Galibert, Guillaume Bernard
    http://arxiv.org/abs/2102.13589v1

    • [cs.CL]Gradient-guided Loss Masking for Neural Machine Translation
    Xinyi Wang, Ankur Bapna, Melvin Johnson, Orhan Firat
    http://arxiv.org/abs/2102.13549v1

    • [cs.CL]Learning Chess Blindfolded: Evaluating Language Models on State Tracking
    Shubham Toshniwal, Sam Wiseman, Karen Livescu, Kevin Gimpel
    http://arxiv.org/abs/2102.13249v1

    • [cs.CL]Methods for the Design and Evaluation of HCI+NLP Systems
    Hendrik Heuer, Daniel Buschek
    http://arxiv.org/abs/2102.13461v1

    • [cs.CL]Multi-task transfer learning for finding actionable information from crisis-related messages on social media
    Congcong Wang, David Lillis
    http://arxiv.org/abs/2102.13395v1

    • [cs.CL]Natural Language Video Localization: A Revisit in Span-based Question Answering Framework
    Hao Zhang, Aixin Sun, Wei Jing, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh
    http://arxiv.org/abs/2102.13558v1

    • [cs.CL]PharmKE: Knowledge Extraction Platform for Pharmaceutical Texts using Transfer Learning
    Nasi Jofche, Kostadin Mishev, Riste Stojanov, Milos Jovanovik, Dimitar Trajanov
    http://arxiv.org/abs/2102.13139v1

    • [cs.CL]Predicting gender and age categories in English conversations using lexical, non-lexical, and turn-taking features
    Andreas Liesenfeld, Gábor Parti, Yu-Yin Hsu, Chu-Ren Huang
    http://arxiv.org/abs/2102.13355v1

    • [cs.CR]GraphSense: A General-Purpose Cryptoasset Analytics Platform
    Bernhard Haslhofer, Rainer Stütz, Matteo Romiti, Ross King
    http://arxiv.org/abs/2102.13613v1

    • [cs.CR]IoTMalware: Android IoT Malware Detection based on Deep Neural Network and Blockchain Technology
    Rajesh Kumar, WenYong Wang, Jay Kumar, Zakria, Ting Yang, Waqar Ali, Abubackar Sharif
    http://arxiv.org/abs/2102.13376v1

    • [cs.CV]A Reconfigurable Winograd CNN Accelerator with Nesting Decomposition Algorithm for Computing Convolution with Large Filters
    Jingbo Jiang, Xizi Chen, Chi-Ying Tsui
    http://arxiv.org/abs/2102.13272v1

    • [cs.CV]A Universal Model for Cross Modality Mapping by Relational Reasoning
    Zun Li, Congyan Lang, Liqian Liang, Tao Wang, Songhe Feng, Jun Wu, Yidong Li
    http://arxiv.org/abs/2102.13360v1

    • [cs.CV]ACDnet: An action detection network for real-time edge computing based on flow-guided feature approximation and memory aggregation
    Yu Liu, Fan Yang, Dominique Ginhac
    http://arxiv.org/abs/2102.13493v1

    • [cs.CV]Accurate Visual-Inertial SLAM by Feature Re-identification
    Xiongfeng Peng, Zhihua Liu, Qiang Wang, Yun-Tae Kim, Myungjae Jeon
    http://arxiv.org/abs/2102.13438v1

    • [cs.CV]Boundary-induced and scene-aggregated network for monocular depth prediction
    Feng Xue, Junfeng Cao, Yu Zhou, Fei Sheng, Yankai Wang, Anlong Ming
    http://arxiv.org/abs/2102.13258v1

    • [cs.CV]Class Knowledge Overlay to Visual Feature Learning for Zero-Shot Image Classification
    Cheng Xie, Ting Zeng, Hongxin Xiang, Keqin Li, Yun Yang, Qing Liu
    http://arxiv.org/abs/2102.13322v1

    • [cs.CV]Continuous Face Aging Generative Adversarial Networks
    Seogkyu Jeon, Pilhyeon Lee, Kibeom Hong, Hyeran Byun
    http://arxiv.org/abs/2102.13318v1

    • [cs.CV]Domain Adapting Ability of Self-Supervised Learning for Face Recognition
    Chun-Hsien Lin, Bing-Fei Wu
    http://arxiv.org/abs/2102.13319v1

    • [cs.CV]Dual-MTGAN: Stochastic and Deterministic Motion Transfer for Image-to-Video Synthesis
    Fu-En Yang, Jing-Cheng Chang, Yuan-Hao Lee, Yu-Chiang Frank Wang
    http://arxiv.org/abs/2102.13329v1

    • [cs.CV]Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images
    Yu Shen, Laura Zheng, Manli Shu, Weizi Li, Tom Goldstein, Ming C. Lin
    http://arxiv.org/abs/2102.13262v1

    • [cs.CV]Knowledge Distillation Circumvents Nonlinearity for Optical Convolutional Neural Networks
    Jinlin Xiang, Shane Colburn, Arka Majumdar, Eli Shlizerman
    http://arxiv.org/abs/2102.13323v1

    • [cs.CV]Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification
    Yi Zhou, Lei Huang, Tianfei Zhou, Ling Shao
    http://arxiv.org/abs/2102.13269v1

    • [cs.CV]Mitigating Domain Mismatch in Face Recognition Using Style Matching
    Chun-Hsien Lin, Bing-Fei Wu
    http://arxiv.org/abs/2102.13327v1

    • [cs.CV]MixSearch: Searching for Domain Generalized Medical Image Segmentation Architectures
    Luyan Liu, Zhiwei Wen, Songwei Liu, Hong-Yu Zhou, Hongwei Zhu, Weicheng Xie, Linlin Shen, Kai Ma, Yefeng Zheng
    http://arxiv.org/abs/2102.13280v1

    • [cs.CV]Nested-block self-attention for robust radiotherapy planning segmentation
    Harini Veeraraghavan, Jue Jiang, Sharif Elguindi, Sean L. Berry, Ifeanyirochukwu Onochie, Aditya Apte, Laura Cervino, Joseph O. Deasy
    http://arxiv.org/abs/2102.13541v1

    • [cs.CV]Point Cloud Upsampling and Normal Estimation using Deep Learning for Robust Surface Reconstruction
    Rajat Sharma, Tobias Schwandt, Christian Kunert, Steffen Urban, Wolfgang Broll
    http://arxiv.org/abs/2102.13391v1

    • [cs.CV]Surgical Visual Domain Adaptation: Results from the MICCAI 2020 SurgVisDom Challenge
    Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Ziheng Wang, Satoshi Kondo, Emanuele Colleoni, Beatrice van Amsterdam, Razeen Hussain, Raabid Hussain, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony Jarc
    http://arxiv.org/abs/2102.13644v1

    • [cs.CV]Unifying Remote Sensing Image Retrieval and Classification with Robust Fine-tuning
    Dimitri Gominski, Valérie Gouet-Brunet, Liming Chen
    http://arxiv.org/abs/2102.13392v1

    • [cs.CV]Using Deep Learning to Automate the Detection of Flaws in Nuclear Fuel Channel UT Scans
    Issam Hammad, Ryan Simpson, Hippolyte Djonon Tsague, Sarah Hall
    http://arxiv.org/abs/2102.13635v1

    • [cs.CV]Where to look at the movies : Analyzing visual attention to understand movie editing
    Alexandre Bruckert, Marc Christie, Olivier Le Meur
    http://arxiv.org/abs/2102.13378v1

    • [cs.CV]Zero-Shot Learning Based on Knowledge Sharing
    Zeng Ting, Xiang Hongxin, Xie Cheng, Yang Yun, Liu Qing
    http://arxiv.org/abs/2102.13326v1

    • [cs.DC]CausalEC: A Causally Consistent Data Storage Algorithm based on Cross-Object Erasure Coding
    Viveck R. Cadambe, Shihang Lyu
    http://arxiv.org/abs/2102.13310v1

    • [cs.DC]Checkpointing with cp: the POSIX Shared Memory System
    Lehman H. Garrison, Daniel J. Eisenstein, Nina A. Maksimova
    http://arxiv.org/abs/2102.13140v1

    • [cs.DC]MEDAL: An AI-driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence
    Vasileios Theodorou, Ilias Gerostathopoulos, Iyad Alshabani, Alberto Abello, David Breitgand
    http://arxiv.org/abs/2102.13125v1

    • [cs.DC]On Register Linearizability and Termination
    Vassos Hadzilacos, Xing Hu, Sam Toueg
    http://arxiv.org/abs/2102.13242v1

    • [cs.DC]VPIC 2.0: Next Generation Particle-in-Cell Simulations
    Robert Bird, Nigel Tan, Scott V. Luedtke, Stephen Lien Harrell, Michela Taufer, Brian Albright
    http://arxiv.org/abs/2102.13133v1

    • [cs.GT]Classifying Convergence Complexity of Nash Equilibria in Graphical Games Using Distributed Computing Theory
    Juho Hirvonen, Laura Schmid, Krishnendu Chatterjee, Stefan Schmid
    http://arxiv.org/abs/2102.13457v1

    • [cs.HC]Images, Emotions, and Credibility: Effect of Emotional Facial Images on Perceptions of News Content Bias and Source Credibility in Social Media
    Alireza Karduni, Ryan Wesslen, Douglas Markant, Wenwen Dou
    http://arxiv.org/abs/2102.13167v1

    • [cs.IR]Open-domain question classification and completion in conversational information search
    Omid Mohammadi Kia, Mahmood Neshati, Mahsa Soudi Alamdari
    http://arxiv.org/abs/2102.13495v1

    • [cs.IR]SAED: Edge-Based Intelligence for Privacy-Preserving Enterprise Search on the Clou
    Sakib, Zobaed, Mohsen Amini Salehi, Rajkumar Buyya
    http://arxiv.org/abs/2102.13367v1

    • [cs.IR]Variation Control and Evaluation for Generative SlateRecommendations
    Shuchang Liu, Fei Sun, Yingqiang Ge, Changhua Pei, Yongfeng Zhang
    http://arxiv.org/abs/2102.13302v1

    • [cs.IT]Average Rate and Error Probability Analysis in Short Packet Communications over RIS-aided URLLC Systems
    Ramin Hashemi, Samad Ali, Nurul Huda Mahmood, Matti Latva-aho
    http://arxiv.org/abs/2102.13363v1

    • [cs.IT]DoA-LF: A Location Fingerprint Positioning Algorithm with Millimeter-Wave
    Zhiqing Wei, Yadong Zhao, Xinyi Liu, Zhiyong Feng
    http://arxiv.org/abs/2102.13297v1

    • [cs.IT]Double-IRS Aided MIMO Communication under LoS Channels: Capacity Maximization and Scaling
    Yitao Han, Shuowen Zhang, Lingjie Duan, Rui Zhang
    http://arxiv.org/abs/2102.13537v1

    • [cs.IT]Energy Efficiency Maximization in the Uplink Delta-OMA Networks
    Ramin Hashemi, Hamzeh Beyranvand, Mohammad Robat Mili, Hina Tabassum
    http://arxiv.org/abs/2102.13359v1

    • [cs.IT]Exact recovery of functions in refinable shift-invariant space by single-angle Radon samples
    Youfa Li, Shengli Fan, Yanfen Huang
    http://arxiv.org/abs/2102.13270v1

    • [cs.IT]Federated Edge Learning with Misaligned Over-The-Air Computation
    Yulin Shao, Deniz Gunduz, Soung Chang Liew
    http://arxiv.org/abs/2102.13604v1

    • [cs.IT]Oversampled Adaptive Sensing via a Predefined Codebook
    Ali Bereyhi, Saba Asaad, Ralf R. Müller
    http://arxiv.org/abs/2102.13366v1

    • [cs.IT]The Magic of Superposition: A Survey on the Simultaneous Transmission Based Wireless Systems
    Ufuk Altun, Gunes Kurt, Enver Ozdemir
    http://arxiv.org/abs/2102.13144v1

    • [cs.LG]今日学术视野(2021.3.2) - 图3: Explanations and Interactions from Conditional Expectations
    Stefan Blücher, Nils Strodthoff
    http://arxiv.org/abs/2102.13519v1

    • [cs.LG]A Regret Minimization Approach to Iterative Learning Control
    Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh
    http://arxiv.org/abs/2102.13478v1

    • [cs.LG]Active Selection of Classification Features
    Thomas T. Kok, Rachel M. Brouwer, Rene M. Mandl, Hugo G. Schnack, Georg Krempl
    http://arxiv.org/abs/2102.13636v1

    • [cs.LG]Adapting to misspecification in contextual bandits with offline regression oracles
    Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey
    http://arxiv.org/abs/2102.13240v1

    • [cs.LG]An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization
    Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski
    http://arxiv.org/abs/2102.13128v1

    • [cs.LG]Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion
    Zhaozhuo Xu, Aditya Desai, Menal Gupta, Anu Chandran, Antoine Vial-Aussavy, Anshumali Shrivastava
    http://arxiv.org/abs/2102.13631v1

    • [cs.LG]Doubly-Adaptive Thompson Sampling for Multi-Armed and Contextual Bandits
    Maria Dimakopoulou, Zhimei Ren, Zhengyuan Zhou
    http://arxiv.org/abs/2102.13202v1

    • [cs.LG]Efficient Client Contribution Evaluation for Horizontal Federated Learning
    Jie Zhao, Xinghua Zhu, Jianzong Wang, Jing Xiao
    http://arxiv.org/abs/2102.13314v1

    • [cs.LG]Experiments with Rich Regime Training for Deep Learning
    Xinyan Li, Arindam Banerjee
    http://arxiv.org/abs/2102.13522v1

    • [cs.LG]FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
    Samuel Horvath, Stefanos Laskaridis, Mario Almeida, Ilias Leondiadis, Stylianos I. Venieris, Nicholas D. Lane
    http://arxiv.org/abs/2102.13451v1

    • [cs.LG]Graph-based Semi-supervised Learning: A Comprehensive Review
    Zixing Song, Xiangli Yang, Zenglin Xu, Irwin King
    http://arxiv.org/abs/2102.13303v1

    • [cs.LG]History-Augmented Collaborative Filtering for Financial Recommendations
    Baptiste Barreau, Laurent Carlier
    http://arxiv.org/abs/2102.13503v1

    • [cs.LG]Iterative SE(3)-Transformers
    Fabian B. Fuchs, Edward Wagstaff, Justas Dauparas, Ingmar Posner
    http://arxiv.org/abs/2102.13419v1

    • [cs.LG]Layer-Wise Interpretation of Deep Neural Networks Using Identity Initialization
    Shohei Kubota, Hideaki Hayashi, Tomohiro Hayase, Seiichi Uchida
    http://arxiv.org/abs/2102.13333v1

    • [cs.LG]Low-Precision Reinforcement Learning
    Johan Bjorck, Xiangyu Chen, Christopher De Sa, Carla P. Gomes, Kilian Q. Weinberger
    http://arxiv.org/abs/2102.13565v1

    • [cs.LG]Machine Biometrics — Towards Identifying Machines in a Smart City Environment
    G. K. Sidiropoulos, G. A. Papakostas
    http://arxiv.org/abs/2102.13190v1

    • [cs.LG]Machine Unlearning via Algorithmic Stability
    Enayat Ullah, Tung Mai, Anup Rao, Ryan Rossi, Raman Arora
    http://arxiv.org/abs/2102.13179v1

    • [cs.LG]Moreau-Yosida 今日学术视野(2021.3.2) - 图4-divergences
    Dávid Terjék
    http://arxiv.org/abs/2102.13416v1

    • [cs.LG]NOMU: Neural Optimization-based Model Uncertainty
    Jakob Heiss, Jakob Weissteiner, Hanna Wutte, Sven Seuken, Josef Teichmann
    http://arxiv.org/abs/2102.13640v1

    • [cs.LG]Named Tensor Notation
    David Chiang, Alexander M. Rush, Boaz Barak
    http://arxiv.org/abs/2102.13196v1

    • [cs.LG]Neural Generalization of Multiple Kernel Learning
    Ahamad Navid Ghanizadeh, Kamaledin Ghiasi-Shirazi, Reza Monsefi, Mohammadreza Qaraei
    http://arxiv.org/abs/2102.13337v1

    • [cs.LG]Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks
    Huichen Li, Linyi Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, Bo Li
    http://arxiv.org/abs/2102.13184v1

    • [cs.LG]On the Generalization of Stochastic Gradient Descent with Momentum
    Ali Ramezani-Kebrya, Ashish Khisti, Ben Liang
    http://arxiv.org/abs/2102.13653v1

    • [cs.LG]On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
    Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra
    http://arxiv.org/abs/2102.13651v1

    • [cs.LG]Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling
    Naoya Takeishi, Alexandros Kalousis
    http://arxiv.org/abs/2102.13156v1

    • [cs.LG]Private and Utility Enhanced Recommendations with Local Differential Privacy and Gaussian Mixture Model
    Jeyamohan Neera, Xiaomin Chen, Nauman Aslam, Kezhi Wang, Zhan Shu
    http://arxiv.org/abs/2102.13453v1

    • [cs.LG]Rip van Winkle’s Razor: A Simple Estimate of Overfit to Test Data
    Sanjeev Arora, Yi Zhang
    http://arxiv.org/abs/2102.13189v1

    • [cs.LG]Safe Distributional Reinforcement Learning
    Jianyi Zhang, Paul Weng
    http://arxiv.org/abs/2102.13446v1

    • [cs.LG]Sparse approximation in learning via neural ODEs
    Carlos Esteve Yagüe, Borjan Geshkovski
    http://arxiv.org/abs/2102.13566v1

    • [cs.LG]Swift for TensorFlow: A portable, flexible platform for deep learning
    Brennan Saeta, Denys Shabalin, Marc Rasi, Brad Larson, Xihui Wu, Parker Schuh, Michelle Casbon, Daniel Zheng, Saleem Abdulrasool, Aleksandr Efremov, Dave Abrahams, Chris Lattner, Richard Wei
    http://arxiv.org/abs/2102.13243v1

    • [cs.LG]Towards Robust and Reliable Algorithmic Recourse
    Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju
    http://arxiv.org/abs/2102.13620v1

    • [cs.LG]What Doesn’t Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors
    Jonas Geiping, Liam Fowl, Gowthami Somepalli, Micah Goldblum, Michael Moeller, Tom Goldstein
    http://arxiv.org/abs/2102.13624v1

    • [cs.NE]A Framework For Pruning Deep Neural Networks Using Energy-Based Models
    Hojjat Salehinejad, Shahrokh Valaee
    http://arxiv.org/abs/2102.13188v1

    • [cs.NE]Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules
    Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
    http://arxiv.org/abs/2102.12905v2

    • [cs.RO]Autonomous Quadrotor Flight despite Rotor Failure with Onboard Vision Sensors: Frames vs. Events
    Sihao Sun, Giovanni Cioffi, Coen de Visser, Davide Scaramuzza
    http://arxiv.org/abs/2102.13406v1

    • [cs.RO]CollisionIK: A Per-Instant Pose Optimization Method for Generating Robot Motions with Environment Collision Avoidance
    Daniel Rakita, Haochen Shi, Bilge Mutlu, Michael Gleicher
    http://arxiv.org/abs/2102.13187v1

    • [cs.RO]Efficient and Interpretable Robot Manipulation with Graph Neural Networks
    Yixin Lin, Austin S. Wang, Akshara Rai
    http://arxiv.org/abs/2102.13177v1

    • [cs.RO]Learning Controller Gains on Bipedal Walking Robots via User Preferences
    Noel Csomay-Shanklin, Maegan Tucker, Min Dai, Jenna Reher, Aaron D. Ames
    http://arxiv.org/abs/2102.13201v1

    • [cs.RO]Motion Planning for a Pair of Tethered Robots
    Reza H. Teshnizi, Dylan A. Shell
    http://arxiv.org/abs/2102.13212v1

    • [cs.RO]On the Visual-based Safe Landing of UAVs in Populated Areas: a Crucial Aspect for Urban Deployment
    Javier González-Trejo, Diego Mercado-Ravell, Israel Becerra, Rafael Murrieta-Cid
    http://arxiv.org/abs/2102.13253v1

    • [cs.RO]Panoramic annular SLAM with loop closure and global optimization
    Hao Chen, Weijian Hu, Kailun Yang, Jian Bai, Kaiwei Wang
    http://arxiv.org/abs/2102.13400v1

    • [cs.RO]Robot Navigation in a Crowd by Integrating Deep Reinforcement Learning and Online Planning
    Zhiqian Zhou, Pengming Zhu, Zhiwen Zeng, Junhao Xiao, Huimin Lu, Zongtan Zhou
    http://arxiv.org/abs/2102.13265v1

    • [cs.RO]V-RVO: Decentralized Multi-Agent Collision Avoidance using Voronoi Diagrams and Reciprocal Velocity Obstacles
    1000
    Senthil Hariharan Arul, Dinesh Manocha
    http://arxiv.org/abs/2102.13281v1

    • [cs.RO]Where to go next: Learning a Subgoal Recommendation Policy for Navigation Among Pedestrians
    Bruno Brito, Michael Everett, Jonathan P. How, Javier Alonso-Mora
    http://arxiv.org/abs/2102.13073v2

    • [cs.SD]The NPU System for the 2020 Personalized Voice Trigger Challenge
    Jingyong Hou, Li Zhang, Yihui Fu, Qing Wang, Zhanheng Yang, Qijie Shao, Lei Xie
    http://arxiv.org/abs/2102.13552v1

    • [cs.SD]Towards Explaining Expressive Qualities in Piano Recordings: Transfer of Explanatory Features via Acoustic Domain Adaptation
    Shreyan Chowdhury, Gerhard Widmer
    http://arxiv.org/abs/2102.13479v1

    • [cs.SE]Distribution-Aware Testing of Neural Networks Using Generative Models
    Swaroopa Dola, Matthew B. Dwyer, Mary Lou Soffa
    http://arxiv.org/abs/2102.13602v1

    • [cs.SI]An organized review of key factors for fake news detection
    Nuno Guimarães, Álvaro Figueira, Luís Torgo
    http://arxiv.org/abs/2102.13433v1

    • [cs.SI]Contact Tracing: Computational Bounds, Limitations and Implications
    Quyu Kong, Manuel Garcia-Herranz, Ivan Dotu, Manuel Cebrian
    http://arxiv.org/abs/2102.13349v1

    • [cs.SI]Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding
    Jing Zhu, Xingyu Lu, Mark Heimann, Danai Koutra
    http://arxiv.org/abs/2102.13582v1

    • [econ.EM]General Bayesian time-varying parameter VARs for predicting government bond yields
    Manfred M. Fischer, Niko Hauzenberger, Florian Huber, Michael Pfarrhofer
    http://arxiv.org/abs/2102.13393v1

    • [econ.EM]Permutation Tests at Nonparametric Rates
    Marinho Bertanha, EunYi Chung
    http://arxiv.org/abs/2102.13638v1

    • [econ.TH]Discord and Harmony in Networks
    Andrea Galeotti, Benjamin Golub, Sanjeev Goyal, Rithvik Rao
    http://arxiv.org/abs/2102.13309v1

    • [eess.AS]Underwater Acoustic Communication Receiver Using Deep Belief Network
    Abigail Lee-Leon, Chau Yuen, Dorien Herremans
    http://arxiv.org/abs/2102.13397v1

    • [eess.IV]3D Vessel Reconstruction in OCT-Angiography via Depth Map Estimation
    Shuai Yu, Jianyang Xie, Jinkui Hao, Yalin Zheng, Jiong Zhang, Yan Hu, Jiang Liu, Yitian Zhao
    http://arxiv.org/abs/2102.13588v1

    • [eess.IV]Convolution-Free Medical Image Segmentation using Transformers
    Davood Karimi, Serge Vasylechko, Ali Gholipour
    http://arxiv.org/abs/2102.13645v1

    • [eess.IV]Robust Rational Polynomial Camera Modelling for SAR and Pushbroom Imaging
    Roland Akiki, Roger Marí, Carlo de Franchis, Jean-Michel Morel, Gabriele Facciolo
    http://arxiv.org/abs/2102.13423v1

    • [eess.IV]Texture-aware Video Frame Interpolation
    Duolikun Danier, David Bull
    http://arxiv.org/abs/2102.13520v1

    • [eess.SP]NCH Sleep DataBank: A Large Collection of Real-world Pediatric Sleep Studies
    Harlin Lee, Boyue Li, Shelly DeForte, Mark Splaingard, Yungui Huang, Yuejie Chi, Simon Lin
    http://arxiv.org/abs/2102.13284v1

    • [eess.SY]ECO: Enabling Energy-Neutral IoT Devices through Runtime Allocation of Harvested Energy
    Yigit Tuncel, Ganapati Bhat, Jaehyun Park, Umit Ogras
    http://arxiv.org/abs/2102.13605v1

    • [math.NA]Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities
    Mengwu Guo, Andrea Manzoni, Maurice Amendt, Paolo Conti, Jan S. Hesthaven
    http://arxiv.org/abs/2102.13403v1

    • [math.OC]Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
    Chaobing Song, Stephen J. Wright, Jelena Diakonikolas
    http://arxiv.org/abs/2102.13643v1

    • [math.ST]Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
    Nafiseh Ghoroghchian, Gautam Dasarathy, Stark C. Draper
    http://arxiv.org/abs/2102.13135v1

    • [math.ST]Nonparametric calibration for stochastic reaction-diffusion equations based on discrete observations
    Florian Hildebrandt, Mathias Trabs
    http://arxiv.org/abs/2102.13415v1

    • [math.ST]Semiparametric empirical likelihood inference with estimating equations under density ratio models
    Meng Yuan, Pengfei Li, Changbao Wu
    http://arxiv.org/abs/2102.13232v1

    • [q-bio.PE]Bioenergetics modelling to analyse and predict the joint effects of multiple stressors: Meta-analysis and model corroboration
    Benoit Goussen, Cecilie Rendal, David Sheffield, Emma Butler, Oliver R. Price, Roman Ashauer
    http://arxiv.org/abs/2102.13107v1

    • [stat.AP]Coupling physical understanding and statistical modeling to estimate ice jam flood frequency in the northern Peace-Athabasca Delta under climate change
    Jonathan R. Lamontagne, Martin Jasek, Jared D. Smith
    http://arxiv.org/abs/2102.13282v1

    • [stat.AP]Estimating Vaccine Efficacy Over Time After a Randomized Study is Unblinded
    Anastasios A. Tsiatis, Marie Davidian
    http://arxiv.org/abs/2102.13103v1

    • [stat.AP]Integrated Dataset of Brazilian Flights
    Claudio Teixeira, Lucas Giusti, Jorge Soares, Joel dos Santos, Glauco Amorim, Eduardo Ogasawara
    http://arxiv.org/abs/2102.13330v1

    • [stat.AP]State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data
    Dohyun Chun, Donggyu Kim
    http://arxiv.org/abs/2102.13404v1

    • [stat.CO]Data-Free Likelihood-Informed Dimension Reduction of Bayesian Inverse Problems
    Tiangang Cui, Olivier Zahm
    http://arxiv.org/abs/2102.13245v1

    • [stat.ME]A multistate approach for mediation analysis in the presence of semi-competing risks with application in cancer survival disparities
    Linda Valeri, Cécile Proust-Lima, Weijia Fan, Jarvis T. Chen, Hélène Jacqmin-Gadda
    http://arxiv.org/abs/2102.13252v1

    • [stat.ME]An introduction to the determination of the probability of a successful trial: Frequentist and Bayesian approaches
    Madan G. Kundu, Sandipan Samanta, Shoubhik Mondal
    http://arxiv.org/abs/2102.13550v1

    • [stat.ME]Cholesky-based multivariate Gaussian regression
    Thomas Muschinski, Georg J. Mayr, Thorsten Simon, Achim Zeileis
    http://arxiv.org/abs/2102.13518v1

    • [stat.ME]Ensemble Conditional Variance Estimator for Sufficient Dimension Reduction
    Lukas Fertl, Efstathia Bura
    http://arxiv.org/abs/2102.13435v1

    • [stat.ME]Exploring the space-time pattern of log-transformed infectious count of COVID-19: a clustering-segmented autoregressive sigmoid model
    Xiaoping Shi, Meiqian Chen, Yucheng Dong
    http://arxiv.org/abs/2102.13287v1

    • [stat.ME]Fast and frugal time series forecasting
    Fotios Petropoulos, Yael Grushka-Cockayne
    http://arxiv.org/abs/2102.13209v1

    • [stat.ME]Interpretable Sensitivity Analysis for Balancing Weights
    Dan Soriano, Eli Ben-Michael, Peter J. Bickel, Avi Feller, Samuel D. Pimentel
    http://arxiv.org/abs/2102.13218v1

    • [stat.ME]Reverse-Bayes methods: a review of recent technical advances
    Leonhard Held, Robert Matthews, Manuela Ott, Samuel Pawel
    http://arxiv.org/abs/2102.13443v1

    • [stat.ME]Sparse Cholesky matrices in spatial statistics
    Abhirup Datta
    http://arxiv.org/abs/2102.13299v1

    • [stat.ME]Variational Full Bayes Lasso: Knots Selection in Regression Splines
    Larissa Alves, Ronaldo Dias, Helio S. Migon
    http://arxiv.org/abs/2102.13548v1

    • [stat.ME]Why did the distribution change?
    Kailash Budhathoki, Dominik Janzing, Patrick Bloebaum, Hoiyi Ng
    http://arxiv.org/abs/2102.13384v1

    • [stat.ML]Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels
    Changyong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling
    http://arxiv.org/abs/2102.13382v1

    • [stat.ML]Beware of the Simulated DAG! Varsortability in Additive Noise Models
    Alexander G. Reisach, Christof Seiler, Sebastian Weichwald
    http://arxiv.org/abs/2102.13647v1

    • [stat.ML]Consistent Sparse Deep Learning: Theory and Computation
    Yan Sun, Qifan Song, Faming Liang
    http://arxiv.org/abs/2102.13229v1

    • [stat.ML]Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach
    Yves-Laurent Kom Samo
    http://arxiv.org/abs/2102.13182v1

    • [stat.ML]Learning Prediction Intervals for Regression: Generalization and Calibration
    Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang
    http://arxiv.org/abs/2102.13625v1

    • [stat.ML]Learning with invariances in random features and kernel models
    Song Mei, Theodor Misiakiewicz, Andrea Montanari
    http://arxiv.org/abs/2102.13219v1

    • [stat.ML]MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA
    Clément Bénard, Sébastien da Veiga, Erwan Scornet
    http://arxiv.org/abs/2102.13347v1

    • [stat.ML]Spectral Top-Down Recovery of Latent Tree Models
    Yariv Aizenbud, Ariel Jaffe, Meng Wang, Amber Hu, Noah Amsel, Boaz Nadler, Joseph T. Chang, Yuval Kluger
    http://arxiv.org/abs/2102.13276v1

    • [stat.ML]Streaming computation of optimal weak transport barycenters
    Elsa Cazelles, Felipe Tobar, Joaquin Fontbona
    http://arxiv.org/abs/2102.13380v1

    • [stat.ML]Zoetrope Genetic Programming for Regression
    Aurélie Boisbunon, Carlo Fanara, Ingrid Grenet, Jonathan Daeden, Alexis Vighi, Marc Schoenauer
    http://arxiv.org/abs/2102.13388v1

    • [stat.ML]sJIVE: Supervised Joint and Individual Variation Explained
    Elise F. Palzer, Christine Wendt, Russell Bowler, Craig P. Hersh, Sandra E. Safo, Eric F. Lock
    http://arxiv.org/abs/2102.13278v1