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.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.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.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 hep-ph - 高能物理现象学 math.OC - 优化与控制 math.ST - 统计理论 physics.med-ph - 医学物理学 q-bio.QM - 定量方法 quant-ph - 量子物理 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]Detection and Classification of Astronomical Targets with Deep Neural Networks in Wide Field Small Aperture Telescopes
    • [cs.AI]A Model-Based, Decision-Theoretic Perspective on Automated Cyber Response
    • [cs.AI]A Road Map to Strong Intelligence
    • [cs.AI]An Advance on Variable Elimination with Applications to Tensor-Based Computation
    • [cs.AI]Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration
    • [cs.AI]On The Reasons Behind Decisions
    • [cs.CL]Guider l’attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue
    • [cs.CL]Is Aligning Embedding Spaces a Challenging Task? An Analysis of the Existing Methods
    • [cs.CL]Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games
    • [cs.CL]On the impressive performance of randomly weighted encoders in summarization tasks
    • [cs.CL]Refinement of Unsupervised Cross-Lingual Word Embeddings
    • [cs.CR]Anonymizing Data for Privacy-Preserving Federated Learning
    • [cs.CV]3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution
    • [cs.CV]A Convolutional Neural Network into graph space
    • [cs.CV]Adapted Center and Scale Prediction: More Stable and More Accurate
    • [cs.CV]Affective Expression Analysis in-the-wild using Multi-Task Temporal Statistical Deep Learning Model
    • [cs.CV]Audio-video Emotion Recognition in the Wild using Deep Hybrid Networks
    • [cs.CV]BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images
    • [cs.CV]Brain Age Estimation Using LSTM on Children’s Brain MRI
    • [cs.CV]Complete Endomorphisms in Computer Vision
    • [cs.CV]Face Phylogeny Tree Using Basis Functions
    • [cs.CV]Fine-Grained Instance-Level Sketch-Based Video Retrieval
    • [cs.CV]Learning to Inpaint by Progressively Growing the Mask Regions
    • [cs.CV]Leveraging Photogrammetric Mesh Models for Aerial-Ground Feature Point Matching Toward Integrated 3D Reconstruction
    • [cs.CV]Robust Iris Presentation Attack Detection Fusing 2D and 3D Information
    • [cs.CV]Stochastic Latent Residual Video Prediction
    • [cs.CV]The Automated Inspection of Opaque Liquid Vaccines
    • [cs.CV]Unsupervised Enhancement of Soft-biometric Privacy with Negative Face Recognition
    • [cs.CV]Unsupervised Pre-trained, Texture Aware And Lightweight Model for Deep Learning-Based Iris Recognition Under Limited Annotated Data
    • [cs.CY]Snel: SQL Native Execution for LLVM
    • [cs.DB]Crowdsourced Collective Entity Resolution with Relational Match Propagation
    • [cs.DB]Graph4Code: A Machine Interpretable Knowledge Graph for Code
    • [cs.DC]Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing
    • [cs.DC]Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications
    • [cs.DS]A polynomial lower bound on adaptive complexity of submodular maximization
    • [cs.DS]Localized Flow-Based Clustering in Hypergraphs
    • [cs.DS]Locally Private Hypothesis Selection
    • [cs.DS]Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs
    • [cs.DS]Practical Estimation of Renyi Entropy
    • [cs.DS]Private Mean Estimation of Heavy-Tailed Distributions
    • [cs.DS]Privately Learning Markov Random Fields
    • [cs.GT]Heavy Tails Make Happy Buyers
    • [cs.HC]Designing Fair AI for Managing Employees in Organizations: A Review, Critique, and Design Agenda
    • [cs.IR]Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems
    • [cs.IT]Performance Evaluation of Adaptive Cooperative NOMA Protocol at Road Junctions
    • [cs.IT]Risk-Based Optimization of Virtual Reality over Terahertz Reconfigurable Intelligent Surfaces
    • [cs.LG]A Hybrid Algorithm Based Robust Big Data Clustering for Solving Unhealthy Initialization, Dynamic Centroid Selection and Empty clustering Problems with Analysis
    • [cs.LG]Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy
    • [cs.LG]Accessing Higher-level Representations in Sequential Transformers with Feedback Memory
    • [cs.LG]Adversarial Detection and Correction by Matching Prediction Distributions
    • [cs.LG]An Investigation of Interpretability Techniques for Deep Learning in Predictive Process Analytics
    • [cs.LG]An end-to-end approach for the verification problem: learning the right distance
    • [cs.LG]Bidirectional Generative Modeling Using Adversarial Gradient Estimation
    • [cs.LG]Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
    • [cs.LG]Calibrating Deep Neural Networks using Focal Loss
    • [cs.LG]Comparing Different Deep Learning Architectures for Classification of Chest Radiographs
    • [cs.LG]Convolutional Tensor-Train LSTM for Spatio-temporal Learning
    • [cs.LG]DSNAS: Direct Neural Architecture Search without Parameter Retraining
    • [cs.LG]Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning
    • [cs.LG]Distributed Mean Estimation with Optimal Error Bounds
    • [cs.LG]Double Explore-then-Commit: Asymptotic Optimality and Beyond
    • [cs.LG]Efficient Learning of Model Weights via Changing Features During Training
    • [cs.LG]Exploiting the Full Capacity of Deep Neural Networks while Avoiding Overfitting by Targeted Sparsity Regularization
    • [cs.LG]Few-Shot Learning via Learning the Representation, Provably
    • [cs.LG]Few-shot acoustic event detection via meta-learning
    • [cs.LG]GANs May Have No Nash Equilibria
    • [cs.LG]It’s Not What Machines Can Learn, It’s What We Cannot Teach
    • [cs.LG]Learning Fairness-aware Relational Structures
    • [cs.LG]Learning to Simulate Complex Physics with Graph Networks
    • [cs.LG]Leveraging Cross Feedback of User and Item Embeddings for Variational Autoencoder based Collaborative Filtering
    • [cs.LG]Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision
    • [cs.LG]Residual Knowledge Distillation
    • [cs.LG]Robust Optimization for Fairness with Noisy Protected Groups
    • [cs.LG]Robustness from Simple Classifiers
    • [cs.LG]Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
    • [cs.LG]Transformer Hawkes Process
    • [cs.LG]Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor
    • [cs.NE]An Evolutionary Deep Learning Method for Short-term Wind Speed Prediction: A Case Study of the Lillgrund Offshore Wind Farm
    • [cs.NE]Real-Time Optimal Guidance and Control for Interplanetary Transfers Using Deep Networks
    • [cs.NE]Recent Trends in the Use of Statistical Tests for Comparing Swarm and Evolutionary Computing Algorithms: Practical Guidelines and a Critical Review
    • [cs.RO]Contact-less manipulation of millimeter-scale objects via ultrasonic levitation
    • [cs.RO]Detailed Proofs of Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight
    • [cs.RO]Learning Precise 3D Manipulation from Multiple Uncalibrated Cameras
    • [cs.RO]Nonlinearity Compensation in a Multi-DoF Shoulder Sensing Exosuit for Real-Time Teleoperation
    • [cs.RO]Optimally Guarding Perimeters and Regions with Mobile Range Sensors
    • [cs.RO]SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances
    • [cs.RO]The Surprising Effectiveness of Linear Models for Visual Foresight in Object Pile Manipulation
    • [cs.RO]Upset Recovery Control for Quadrotors Subjected to a Complete Rotor Failure from Large Initial Disturbances
    • [cs.SE]How to Evaluate Solutions in Pareto-based Search-Based Software Engineering? A Critical Review and Methodological Guidance
    • [cs.SI]Curating Social Media Data
    • [cs.SI]Fast Evaluation of Link Prediction by Random Sampling of Unobserved Links
    • [eess.AS]Efficient Trainable Front-Ends for Neural Speech Enhancement
    • [eess.AS]Multi-label Sound Event Retrieval Using a Deep Learning-based Siamese Structure with a Pairwise Presence Matrix
    • [eess.IV]Binary Probability Model for Learning Based Image Compression
    • [eess.IV]Development of accurate human head models for personalized electromagnetic dosimetry using deep learning
    • [eess.SP]Massive MIMO Channel Measurements and Achievable Rates in a Residential Area
    • [hep-ph]Likelihood-free inference of experimental Neutrino Oscillations using Neural Spline Flows
    • [math.OC]Asynchronous parallel adaptive stochastic gradient methods
    • [math.OC]Sparsity in Optimal Randomized Classification Trees
    • [math.OC]Using Deep Learning to Improve Ensemble Smoother: Applications to Subsurface Characterization
    • [math.ST]Aggregation of Multiple Knockoffs
    • [math.ST]Central limit theorems for Markov chains based on their convergence rates in Wasserstein distance
    • [math.ST]Conditional Independence in Max-linear Bayesian Networks
    • [math.ST]Debiasing Stochastic Gradient Descent to handle missing values
    • [math.ST]Generalisation error in learning with random features and the hidden manifold model
    • [math.ST]Kernel Conditional Moment Test via Maximum Moment Restriction
    • [math.ST]Whittle estimation for stationary state space models with finite second moments
    • [physics.med-ph]Deep Learning System to Screen Coronavirus Disease 2019 Pneumonia
    • [q-bio.QM]NeuroQuery: comprehensive meta-analysis of human brain mapping
    • [quant-ph]Quantum secret sharing using GHZ state qubit positioning and selective qubits strategy for secret reconstruction
    • [stat.AP]A copula-based time series model for global horizontal irradiation
    • [stat.AP]Score-based likelihood ratios to evaluate forensic pattern evidence
    • [stat.CO]Split-BOLFI for for misspecification-robust likelihood free inference in high dimensions
    • [stat.ME]A Joint Bayesian Framework for Causal Inference and Bipartite Matching for Record Linkage
    • [stat.ME]Directed Acyclic Graphs and causal thinking in clinical risk prediction modeling
    • [stat.ME]Efficient model-based Bioequivalence Testing
    • [stat.ME]Estimation of conditional mixture Weibull distribution with right-censored data using neural network for time-to-event analysis
    • [stat.ME]Knockoff Boosted Tree for Model-Free Variable Selection
    • [stat.ME]Predictive Inference Is Free with the Jackknife+-after-Bootstrap
    • [stat.ME]Success-Odds: An improved Win-Ratio
    • [stat.ML]A Multiclass Classification Approach to Label Ranking
    • [stat.ML]Adaptive Covariate Acquisition for Minimizing Total Cost of Classification
    • [stat.ML]Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming
    • [stat.ML]Deep Sigma Point Processes
    • [stat.ML]Differentiable Likelihoods for Fast Inversion of ‘Likelihood-Free’ Dynamical Systems
    • [stat.ML]Efficiently sampling functions from Gaussian process posteriors
    • [stat.ML]Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation
    • [stat.ML]Inverted-File k-Means Clustering: Performance Analysis
    • [stat.ML]Learning Deep Kernels for Non-Parametric Two-Sample Tests
    • [stat.ML]Learning Optimal Classification Trees: Strong Max-Flow Formulations
    • [stat.ML]Online Batch Decision-Making with High-Dimensional Covariates
    • [stat.ML]PIANO: A Fast Parallel Iterative Algorithm for Multinomial and Sparse Multinomial Logistic Regression
    • [stat.ML]Sparse principal component regression via singular value decomposition approach

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    • [astro-ph.IM]Detection and Classification of Astronomical Targets with Deep Neural Networks in Wide Field Small Aperture Telescopes
    Peng Jia, Qiang Liu, Yongyang Sun
    http://arxiv.org/abs/2002.09211v1

    • [cs.AI]A Model-Based, Decision-Theoretic Perspective on Automated Cyber Response
    Lashon B. Booker, Scott A. Musman
    http://arxiv.org/abs/2002.08957v1

    • [cs.AI]A Road Map to Strong Intelligence
    Philip Paquette
    http://arxiv.org/abs/2002.09044v1

    • [cs.AI]An Advance on Variable Elimination with Applications to Tensor-Based Computation
    Adnan Darwiche
    http://arxiv.org/abs/2002.09320v1

    • [cs.AI]Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration
    Cédric Colas, Tristan Karch, Nicolas Lair, Jean-Michel Dussoux, Clément Moulin-Frier, Peter Ford Dominey, Pierre-Yves Oudeyer
    http://arxiv.org/abs/2002.09253v1

    • [cs.AI]On The Reasons Behind Decisions
    Adnan Darwiche, Auguste Hirth
    http://arxiv.org/abs/2002.09284v1

    • [cs.CL]Guider l’attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue
    Pierre Colombo, Emile Chapuis, Matteo Manica, Emmanuel Vignon, Giovanna Varni, Chloe Clavel
    http://arxiv.org/abs/2002.09419v1

    • [cs.CL]Is Aligning Embedding Spaces a Challenging Task? An Analysis of the Existing Methods
    Russa Biswas, Mehwish Alam, Harald Sack
    http://arxiv.org/abs/2002.09247v1

    • [cs.CL]Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games
    Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikuláš Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
    http://arxiv.org/abs/2002.09127v1

    • [cs.CL]On the impressive performance of randomly weighted encoders in summarization tasks
    Jonathan Pilault, Jaehong Park, Christopher Pal
    http://arxiv.org/abs/2002.09084v1

    • [cs.CL]Refinement of Unsupervised Cross-Lingual Word Embeddings
    Magdalena Biesialska, Marta R. Costa-jussà
    http://arxiv.org/abs/2002.09213v1

    • [cs.CR]Anonymizing Data for Privacy-Preserving Federated Learning
    Olivia Choudhury, Aris Gkoulalas-Divanis, Theodoros Salonidis, Issa Sylla, Yoonyoung Park, Grace Hsu, Amar Das
    http://arxiv.org/abs/2002.09096v1

    • [cs.CV]3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution
    Yi Zhao, Nils Wandel, Magdalena Landl, Andrea Schnepf, Sven Behnke
    http://arxiv.org/abs/2002.09317v1

    • [cs.CV]A Convolutional Neural Network into graph space
    Maxime Martineau, Romain Raveaux, Donatello Conte, Gilles Venturini
    http://arxiv.org/abs/2002.09285v1

    • [cs.CV]Adapted Center and Scale Prediction: More Stable and More Accurate
    Wenhao Wang
    http://arxiv.org/abs/2002.09053v1

    • [cs.CV]Affective Expression Analysis in-the-wild using Multi-Task Temporal Statistical Deep Learning Model
    Nhu-Tai Do, Soo-Hyung Kim
    http://arxiv.org/abs/2002.09120v1

    • [cs.CV]Audio-video Emotion Recognition in the Wild using Deep Hybrid Networks
    Xin Guo, Luisa F. Polanía, Kenneth E. Barner
    http://arxiv.org/abs/2002.09023v1

    • [cs.CV]BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images
    Thu Nguyen-Phuoc, Christian Richardt, Long Mai, Yong-Liang Yang, Niloy Mitra
    http://arxiv.org/abs/2002.08988v1

    • [cs.CV]Brain Age Estimation Using LSTM on Children’s Brain MRI
    Sheng He, Randy L. Gollub, Shawn N. Murphy, Juan David Perez, Sanjay Prabhu, Rudolph Pienaar, Richard L. Robertson, P. Ellen Grant, Yangming Ou
    http://arxiv.org/abs/2002.09045v1

    • [cs.CV]Complete Endomorphisms in Computer Vision
    Javier Finat, Francisco Delgado-del-Hoyo
    http://arxiv.org/abs/2002.09003v1

    • [cs.CV]Face Phylogeny Tree Using Basis Functions
    Sudipta Banerjee, Arun Ross
    http://arxiv.org/abs/2002.09068v1

    • [cs.CV]Fine-Grained Instance-Level Sketch-Based Video Retrieval
    Peng Xu, Kun Liu, Tao Xiang, Timothy M. Hospedales, Zhanyu Ma, Jun Guo, Yi-Zhe Song
    http://arxiv.org/abs/2002.09461v1

    • [cs.CV]Learning to Inpaint by Progressively Growing the Mask Regions
    Mohamed Abbas Hedjazi, Yakup Genc
    http://arxiv.org/abs/2002.09280v1

    • [cs.CV]Leveraging Photogrammetric Mesh Models for Aerial-Ground Feature Point Matching Toward Integrated 3D Reconstruction
    Qing Zhu, Zhendong Wang, Han Hu, Linfu Xie, Xuming Ge, Yeting Zhang
    http://arxiv.org/abs/2002.09085v1

    • [cs.CV]Robust Iris Presentation Attack Detection Fusing 2D and 3D Information
    Zhaoyuan Fang, Adam Czajka, Kevin W. Bowyer
    http://arxiv.org/abs/2002.09137v1

    • [cs.CV]Stochastic Latent Residual Video Prediction
    Jean-Yves Franceschi, Edouard Delasalles, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari
    http://arxiv.org/abs/2002.09219v1

    • [cs.CV]The Automated Inspection of Opaque Liquid Vaccines
    Gregory Palmer, Benjamin Schnieders, Rahul Savani, Karl Tuyls, Joscha-David Fossel, Harry Flore
    http://arxiv.org/abs/2002.09406v1

    • [cs.CV]Unsupervised Enhancement of Soft-biometric Privacy with Negative Face Recognition
    Philipp Terhörst, Marco Huber, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
    http://arxiv.org/abs/2002.09181v1

    • [cs.CV]Unsupervised Pre-trained, Texture Aware And Lightweight Model for Deep Learning-Based Iris Recognition Under Limited Annotated Data
    Manashi Chakraborty, Mayukh Roy, Prabir Kumar Biswas, Pabitra Mitra
    http://arxiv.org/abs/2002.09048v1

    • [cs.CY]Snel: SQL Native Execution for LLVM
    Marcelo Mottalli, Gustavo Ajzenman, Carlos Sarraute
    http://arxiv.org/abs/2002.09449v1

    • [cs.DB]Crowdsourced Collective Entity Resolution with Relational Match Propagation
    Jiacheng Huang, Wei Hu, Zhifeng Bao, Yuzhong Qu
    http://arxiv.org/abs/2002.09361v1

    • [cs.DB]Graph4Code: A Machine Interpretable Knowledge Graph for Code
    Kavitha Srinivas, Ibrahim Abdelaziz, Julian Dolby, James P. McCusker
    http://arxiv.org/abs/2002.09440v1

    • [cs.DC]Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing
    Simon Shillaker, Peter Pietzuch
    http://arxiv.org/abs/2002.09344v1

    • [cs.DC]Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications
    Andre Luckow, Shantenu Jha
    http://arxiv.org/abs/2002.09009v1

    • [cs.DS]A polynomial lower bound on adaptive complexity of submodular maximization
    Wenzheng Li, Paul Liu, Jan Vondrak
    http://arxiv.org/abs/2002.09130v1

    • [cs.DS]Localized Flow-Based Clustering in Hypergraphs
    Nate Veldt, Austin R. Benson, Jon Kleinberg
    http://arxiv.org/abs/2002.09441v1

    • [cs.DS]Locally Private Hypothesis Selection
    Sivakanth Gopi, Gautam Kamath, Janardhan Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang
    http://arxiv.org/abs/2002.09465v1

    • [cs.DS]Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs
    Nate Veldt, Anthony Wirth, David F. Gleich
    http://arxiv.org/abs/2002.09460v1

    • [cs.DS]Practical Estimation of Renyi Entropy
    Maciej Skorski
    http://arxiv.org/abs/2002.09264v1

    • [cs.DS]Private Mean Estimation of Heavy-Tailed Distributions
    Gautam Kamath, Vikrant Singhal, Jonathan Ullman
    http://arxiv.org/abs/2002.09464v1

    • [cs.DS]Privately Learning Markov Random Fields
    Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Zhiwei Steven Wu
    http://arxiv.org/abs/2002.09463v1

    • [cs.GT]Heavy Tails Make Happy Buyers
    Eric Bax
    http://arxiv.org/abs/2002.09014v1

    • [cs.HC]Designing Fair AI for Managing Employees in Organizations: A Review, Critique, and Design Agenda
    Lionel P. Robert, Casey Pierce, Liz Morris, Sangmi Kim, Rasha Alahmad
    http://arxiv.org/abs/2002.09054v1

    • [cs.IR]Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems
    Wenqiang Lei, Xiangnan He, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan, Tat-Seng Chua
    http://arxiv.org/abs/2002.09102v1

    • [cs.IT]Performance Evaluation of Adaptive Cooperative NOMA Protocol at Road Junctions
    Baha Eddine Youcef Belmekki, Abdelkrim Hamza, Benoît Escrig
    http://arxiv.org/abs/2002.09369v1

    • [cs.IT]Risk-Based Optimization of Virtual Reality over Terahertz Reconfigurable Intelligent Surfaces
    Christina Chaccour, Mehdi Naderi Soorki, Walid Saad, Mehdi Bennis, Petar Popovski
    http://arxiv.org/abs/2002.09052v1

    • [cs.LG]A Hybrid Algorithm Based Robust Big Data Clustering for Solving Unhealthy Initialization, Dynamic Centroid Selection and Empty clustering Problems with Analysis
    Y. A. Joarder, Mosabbir Ahmed
    http://arxiv.org/abs/2002.09380v1

    • [cs.LG]Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy
    Jiaxing Zhang, Hoang Tran, Guannan Zhang
    http://arxiv.org/abs/2002.09077v1

    • [cs.LG]Accessing Higher-level Representations in Sequential Transformers with Feedback Memory
    Angela Fan, Thibaut Lavril, Edouard Grave, Armand Joulin, Sainbayar Sukhbaatar
    http://arxiv.org/abs/2002.09402v1

    • [cs.LG]Adversarial Detection and Correction by Matching Prediction Distributions
    Giovanni Vacanti, Arnaud Van Looveren
    http://arxiv.org/abs/2002.09364v1

    • [cs.LG]An Investigation of Interpretability Techniques for Deep Learning in Predictive Process Analytics
    Catarina Moreira, Renuka Sindhgatta, Chun Ouyang, Peter Bruza, Andreas Wichert
    http://arxiv.org/abs/2002.09192v1

    • [cs.LG]An end-to-end approach for the verification problem: learning the right distance
    Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk
    http://arxiv.org/abs/2002.09469v1

    • [cs.LG]Bidirectional Generative Modeling Using Adversarial Gradient Estimation
    Xinwei Shen, Tong Zhang, Kani Chen
    http://arxiv.org/abs/2002.09161v1

    • [cs.LG]Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
    Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu
    http://arxiv.org/abs/2002.09169v1

    • [cs.LG]Calibrating Deep Neural Networks using Focal Loss
    Jishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip H. S. Torr, Puneet K. Dokania
    http://arxiv.org/abs/2002.09437v1

    • [cs.LG]Comparing Different Deep Learning Architectures for Classification of Chest Radiographs
    Keno K. Bressem, Lisa Adams, Christoph Erxleben, Bernd Hamm, Stefan Niehues, Janis Vahldiek
    http://arxiv.org/abs/2002.08991v1

    • [cs.LG]Convolutional Tensor-Train LSTM for Spatio-temporal Learning
    Jiahao Su, Wonmin Byeon, Furong Huang, Jan Kautz, Animashree Anandkumar
    http://arxiv.org/abs/2002.09131v1

    • [cs.LG]DSNAS: Direct Neural Architecture Search without Parameter Retraining
    Shoukang Hu, Sirui Xie, Hehui Zheng, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin
    http://arxiv.org/abs/2002.09128v1

    • [cs.LG]Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning
    Yuanyi Zhong, Alexander Schwing, Jian Peng
    http://arxiv.org/abs/2002.09136v1

    • [cs.LG]Distributed Mean Estimation with Optimal Error Bounds
    Dan Alistarh, Saleh Ashkboos, Peter Davies
    http://arxiv.org/abs/2002.09268v1

    • [cs.LG]Double Explore-then-Commit: Asymptotic Optimality and Beyond
    Tianyuan Jin, Pan Xu, Xiaokui Xiao, Quanquan Gu
    http://arxiv.org/abs/2002.09174v1

    • [cs.LG]Efficient Learning of Model Weights via Changing Features During Training
    Marcell Beregi-Kovács, Ágnes Baran, András Hajdu
    http://arxiv.org/abs/2002.09249v1

    • [cs.LG]Exploiting the Full Capacity of Deep Neural Networks while Avoiding Overfitting by Targeted Sparsity Regularization
    Karim Huesmann, Soeren Klemm, Lars Linsen, Benjamin Risse
    http://arxiv.org/abs/2002.09237v1

    • [cs.LG]Few-Shot Learning via Learning the Representation, Provably
    Simon S. Du, Wei Hu, Sham M. Kakade, Jason D. Lee, Qi Lei
    http://arxiv.org/abs/2002.09434v1

    • [cs.LG]Few-shot acoustic event detection via meta-learning
    Bowen Shi, Ming Sun, Krishna C. Puvvada, Chieh-Chi Kao, Spyros Matsoukas, Chao Wang
    http://arxiv.org/abs/2002.09143v1

    • [cs.LG]GANs May Have No Nash Equilibria
    Farzan Farnia, Asuman Ozdaglar
    http://arxiv.org/abs/2002.09124v1

    • [cs.LG]It’s Not What Machines Can Learn, It’s What We Cannot Teach
    Gal Yehuda, Moshe Gabel, Assaf Schuster
    http://arxiv.org/abs/2002.09398v1

    • [cs.LG]Learning Fairness-aware Relational Structures
    Yue Zhang, Arti Ramesh
    http://arxiv.org/abs/2002.09471v1

    • [cs.LG]Learning to Simulate Complex Physics with Graph Networks
    Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, Peter W. Battaglia
    http://arxiv.org/abs/2002.09405v1

    • [cs.LG]Leveraging Cross Feedback of User and Item Embeddings for Variational Autoencoder based Collaborative Filtering
    Yuan Jin, He Zhao, Ming Liu, Lan Du, Yunfeng Li, Ruohua Xu, Longxiang Gao
    http://arxiv.org/abs/2002.09145v1

    • [cs.LG]Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision
    Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu
    http://arxiv.org/abs/2002.09049v1

    • [cs.LG]Residual Knowledge Distillation
    Mengya Gao, Yujun Shen, Quanquan Li, Chen Change Loy
    http://arxiv.org/abs/2002.09168v1

    • [cs.LG]Robust Optimization for Fairness with Noisy Protected Groups
    Serena Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya Gupta, Michael I. Jordan
    http://arxiv.org/abs/2002.09343v1

    • [cs.LG]Robustness from Simple Classifiers
    Sharon Qian, Dimitris Kalimeris, Gal Kaplun, Yaron Singer
    http://arxiv.org/abs/2002.09422v1

    • [cs.LG]Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
    Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
    http://arxiv.org/abs/2002.09089v1

    • [cs.LG]Transformer Hawkes Process
    Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha
    http://arxiv.org/abs/2002.09291v1

    • [cs.LG]Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor
    Mher Safaryan, Egor Shulgin, Peter Richtárik
    http://arxiv.org/abs/2002.08958v1

    • [cs.NE]An Evolutionary Deep Learning Method for Short-term Wind Speed Prediction: A Case Study of the Lillgrund Offshore Wind Farm
    Mehdi Neshat, Meysam Majidi Nezhad, Ehsan Abbasnejad, Lina Bertling Tjernberg, Davide Astiaso Garcia, Bradley Alexander, Markus Wagner
    http://arxiv.org/abs/2002.09106v1

    • [cs.NE]Real-Time Optimal Guidance and Control for Interplanetary Transfers Using Deep Networks
    Dario Izzo, Ekin Öztürk
    http://arxiv.org/abs/2002.09063v1

    • [cs.NE]Recent Trends in the Use of Statistical Tests for Comparing Swarm and Evolutionary Computing Algorithms: Practical Guidelines and a Critical Review
    J. Carrasco, S. García, M. M. Rueda, S. Das, F. Herrera
    http://arxiv.org/abs/2002.09227v1

    • [cs.RO]Contact-less manipulation of millimeter-scale objects via ultrasonic levitation
    Jared Nakahara, Boling Yang, Joshua R. Smith
    http://arxiv.org/abs/2002.09056v1

    • [cs.RO]Detailed Proofs of Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight
    Zhepei Wang, Xin Zhou, Chao Xu, Fei Gao
    http://arxiv.org/abs/2002.09254v1

    • [cs.RO]Learning Precise 3D Manipulation from Multiple Uncalibrated Cameras
    Iretiayo Akinola, Jacob Varley, Dmitry Kalashnikov
    http://arxiv.org/abs/2002.09107v1

    • [cs.RO]Nonlinearity Compensation in a Multi-DoF Shoulder Sensing Exosuit for Real-Time Teleoperation
    Rejin John Varghese, Anh Nguyen, Etienne Burdet, Guang-Zhong Yang, Benny P L Lo
    http://arxiv.org/abs/2002.09195v1

    • [cs.RO]Optimally Guarding Perimeters and Regions with Mobile Range Sensors
    Si Wei Feng, Jingjin Yu
    http://arxiv.org/abs/2002.08477v2

    • [cs.RO]SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances
    Yancheng Pan, Biao Gao, Jilin Mei, Sibo Geng, Chengkun Li, Huijing Zhao
    http://arxiv.org/abs/2002.09147v1

    • [cs.RO]The Surprising Effectiveness of Linear Models for Visual Foresight in Object Pile Manipulation
    H. J. Terry Suh, Russ Tedrake
    http://arxiv.org/abs/2002.09093v1

    • [cs.RO]Upset Recovery Control for Quadrotors Subjected to a Complete Rotor Failure from Large Initial Disturbances
    Sihao Sun, Matthias Baert, Bram Adriaan Strack van Schijndel, Coen de Visser
    http://arxiv.org/abs/2002.09425v1

    • [cs.SE]How to Evaluate Solutions in Pareto-based Search-Based Software Engineering? A Critical Review and Methodological Guidance
    Tao Chen, Miqing Li, Xin Yao
    http://arxiv.org/abs/2002.09040v1

    • [cs.SI]Curating Social Media Data
    Kushal Vaghani
    http://arxiv.org/abs/2002.09202v1

    • [cs.SI]Fast Evaluation of Link Prediction by Random Sampling of Unobserved Links
    Jingwei Wang, Yunlong Ma, Zeyu Chen, Xuheng Wang, Yuan Yun, Weiming Shen, Min Liu
    http://arxiv.org/abs/2002.09165v1

    • [eess.AS]Efficient Trainable Front-Ends for Neural Speech Enhancement
    Jonah Casebeer, Umut Isik, Shrikant Venkataramani, Arvindh Krishnaswamy
    http://arxiv.org/abs/2002.09286v1

    • [eess.AS]Multi-label Sound Event Retrieval Using a Deep Learning-based Siamese Structure with a Pairwise Presence Matrix
    Jianyu Fan, Eric Nichols, Daniel Tompkins, Ana Elisa Mendez Mendez, Benjamin Elizalde, Philippe Pasquier
    http://arxiv.org/abs/2002.09026v1

    • [eess.IV]Binary Probability Model for Learning Based Image Compression
    Théo Ladune, Pierrick Philippe, Wassim Hamidouche, Lu Zhang, Olivier Deforges
    http://arxiv.org/abs/2002.09259v1

    • [eess.IV]Development of accurate human head models for personalized electromagnetic dosimetry using deep learning
    Essam A. Rashed, Jose Gomez-Tames, Akimasa Hirata
    http://arxiv.org/abs/2002.09080v1

    • [eess.SP]Massive MIMO Channel Measurements and Achievable Rates in a Residential Area
    Marc Gauger, Maximilian Arnold, Stephan ten Brink
    http://arxiv.org/abs/2002.09452v1

    • [hep-ph]Likelihood-free inference of experimental Neutrino Oscillations using Neural Spline Flows
    Sebastian Pina-Otey, Federico Sánchez, Vicens Gaitan
    http://arxiv.org/abs/2002.09436v1

    • [math.OC]Asynchronous parallel adaptive stochastic gradient methods
    Yangyang Xu, Colin Sutcher-Shepard, Yibo Xu, Jie Chen
    http://arxiv.org/abs/2002.09095v1

    • [math.OC]Sparsity in Optimal Randomized Classification Trees
    Rafael Blanquero, Emilio Carrizosa, Cristina Molero-Río, Dolores Romero Morales
    http://arxiv.org/abs/2002.09191v1

    • [math.OC]Using Deep Learning to Improve Ensemble Smoother: Applications to Subsurface Characterization
    Jiangjiang Zhang, Qiang Zheng, Laosheng Wu, Lingzao Zeng
    http://arxiv.org/abs/2002.09100v1

    • [math.ST]Aggregation of Multiple Knockoffs
    Binh T. Nguyen, Jérôme-Alexis Chevalier, Bertrand Thirion, Sylvain Arlot
    http://arxiv.org/abs/2002.09269v1

    • [math.ST]Central limit theorems for Markov chains based on their convergence rates in Wasserstein distance
    Rui Jin, Aixin Tan
    http://arxiv.org/abs/2002.09427v1

    • [math.ST]Conditional Independence in Max-linear Bayesian Networks
    Carlos Améndola, Claudia Klüppelberg, Steffen Lauritzen, Ngoc Tran
    http://arxiv.org/abs/2002.09233v1

    • [math.ST]Debiasing Stochastic Gradient Descent to handle missing values
    Aude Sportisse, Claire Boyer, Aymeric Dieuleveut, Julie Josse
    http://arxiv.org/abs/2002.09338v1

    • [math.ST]Generalisation error in learning with random features and the hidden manifold model
    Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mézard, Lenka Zdeborová
    http://arxiv.org/abs/2002.09339v1

    • [math.ST]Kernel Conditional Moment Test via Maximum Moment Restriction
    Krikamol Muandet, Wittawat Jitkrittum, Jonas Kübler
    http://arxiv.org/abs/2002.09225v1

    • [math.ST]Whittle estimation for stationary state space models with finite second moments
    Vicky Fasen-Hartmann, Celeste Mayer
    http://arxiv.org/abs/2002.09426v1

    • [physics.med-ph]Deep Learning System to Screen Coronavirus Disease 2019 Pneumonia
    Xiaowei Xu, Xiangao Jiang, Chunlian Ma, Peng Du, Xukun Li, Shuangzhi Lv, Liang Yu, Yanfei Chen, Junwei Su, Guanjing Lang, Yongtao Li, Hong Zhao, Kaijin Xu, Lingxiang Ruan, Wei Wu
    http://arxiv.org/abs/2002.09334v1

    • [q-bio.QM]NeuroQuery: comprehensive meta-analysis of human brain mapping
    Jérôme Dockès, Russell Poldrack, Romain Primet, Hande Gözükan, Tal Yarkoni, Fabian Suchanek, Bertrand Thirion, Gaël Varoquaux
    http://arxiv.org/abs/2002.09261v1

    • [quant-ph]Quantum secret sharing using GHZ state qubit positioning and selective qubits strategy for secret reconstruction
    Farhan Musanna, Sanjeev Kumar
    http://arxiv.org/abs/2002.09182v1

    • [stat.AP]A copula-based time series model for global horizontal irradiation
    Alfred Müller, Matthias Reuber
    http://arxiv.org/abs/2002.09267v1

    • [stat.AP]Score-based likelihood ratios to evaluate forensic pattern evidence
    Nathaniel Garton, Danica Ommen, Jarad Niemi, Alicia Carriquiry
    http://arxiv.org/abs/2002.09470v1

    • [stat.CO]Split-BOLFI for for misspecification-robust likelihood free inference in high dimensions
    Owen Thomas, Henri Pesonen, Raquel Sá-Leão, Hermínia de Lencastre, Samuel Kaski, Jukka Corander
    http://arxiv.org/abs/2002.09377v1

    • [stat.ME]A Joint Bayesian Framework for Causal Inference and Bipartite Matching for Record Linkage
    Sharmistha Guha, Jerome P. Reiter
    http://arxiv.org/abs/2002.09119v1

    • [stat.ME]Directed Acyclic Graphs and causal thinking in clinical risk prediction modeling
    Marco Piccininni, Stefan Konigorski, Jessica L Rohmann, Tobias Kurth
    http://arxiv.org/abs/2002.09414v1

    • [stat.ME]Efficient model-based Bioequivalence Testing
    Kathrin Möllenhoff, Florence Loingeville, Julie Bertrand, Thu Thuy Nguyen, Satish Sharan, Guoying Sun, Stella Grosser, Liang Zhao, Lanyan Fang, France Mentré, Holger Dette
    http://arxiv.org/abs/2002.09316v1

    • [stat.ME]Estimation of conditional mixture Weibull distribution with right-censored data using neural network for time-to-event analysis
    Achraf Bennis, Sandrine Mouysset, Mathieu Serrurier
    http://arxiv.org/abs/2002.09358v1

    • [stat.ME]Knockoff Boosted Tree for Model-Free Variable Selection
    Tao Jiang, Yuanyuan Li, Alison A. Motsinger-Reif
    http://arxiv.org/abs/2002.09032v1

    • [stat.ME]Predictive Inference Is Free with the Jackknife+-after-Bootstrap
    Byol Kim, Chen Xu, Rina Foygel Barber
    http://arxiv.org/abs/2002.09025v1

    • [stat.ME]Success-Odds: An improved Win-Ratio
    Edgar Brunner
    http://arxiv.org/abs/2002.09273v1

    • [stat.ML]A Multiclass Classification Approach to Label Ranking
    Stephan Clémençon, Robin Vogel
    http://arxiv.org/abs/2002.09420v1

    • [stat.ML]Adaptive Covariate Acquisition for Minimizing Total Cost of Classification
    Daniel Andrade, Yuzuru Okajima
    http://arxiv.org/abs/2002.09162v1

    • [stat.ML]Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming
    Vo Nguyen Le Duy, Hiroki Toda, Ryota Sugiyama, Ichiro Takeuchi
    http://arxiv.org/abs/2002.09132v1

    • [stat.ML]Deep Sigma Point Processes
    Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner
    http://arxiv.org/abs/2002.09112v1

    • [stat.ML]Differentiable Likelihoods for Fast Inversion of ‘Likelihood-Free’ Dynamical Systems
    Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig
    http://arxiv.org/abs/2002.09301v1

    • [stat.ML]Efficiently sampling functions from Gaussian process posteriors
    James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
    http://arxiv.org/abs/2002.09309v1

    • [stat.ML]Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation
    Dmitry Molchanov, Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Vetrov
    http://arxiv.org/abs/2002.09103v1

    • [stat.ML]Inverted-File k-Means Clustering: Performance Analysis
    Kazuo Aoyama, Kazumi Saito, Tetsuo Ikeda
    http://arxiv.org/abs/2002.09094v1

    • [stat.ML]Learning Deep Kernels for Non-Parametric Two-Sample Tests
    Feng Liu, Wenkai Xu, Jie Lu, Guangquan Zhang, Arthur Gretton, D. J. Sutherland
    http://arxiv.org/abs/2002.09116v1

    • [stat.ML]Learning Optimal Classification Trees: Strong Max-Flow Formulations
    Sina Aghaei, Andres Gomez, Phebe Vayanos
    http://arxiv.org/abs/2002.09142v1

    • [stat.ML]Online Batch Decision-Making with High-Dimensional Covariates
    Chi-Hua Wang, Guang Cheng
    http://arxiv.org/abs/2002.09438v1

    • [stat.ML]PIANO: A Fast Parallel Iterative Algorithm for Multinomial and Sparse Multinomial Logistic Regression
    R. Jyothi, P. Babu
    http://arxiv.org/abs/2002.09133v1

    • [stat.ML]Sparse principal component regression via singular value decomposition approach
    Shuichi Kawano
    http://arxiv.org/abs/2002.09188v1