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