cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    cs.NE - 神经与进化计算
    cs.NI - 网络和互联网体系结构
    cs.PL - 编程语言
    cs.RO - 机器人学
    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
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.ao-ph - 大气和海洋物理
    physics.comp-ph - 计算物理学
    physics.soc-ph - 物理学与社会
    q-bio.NC - 神经元与认知
    q-fin.ST - 统计金融学
    stat.AP - 应用统计
    stat.CO - 统计计算
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习


    • [cs.AI]Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning
    • [cs.AI]Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game
    • [cs.CL]CiwGAN and fiwGAN: Encoding information in acoustic data to model lexical learning with Generative Adversarial Networks
    • [cs.CL]End-to-End Speech-Translation with Knowledge Distillation: FBK@IWSLT2020
    • [cs.CL]Experiments on Paraphrase Identification Using Quora Question Pairs Dataset
    • [cs.CL]Extracting COVID-19 Events from Twitter
    • [cs.CL]Linguists Who Use Probabilistic Models Love Them: Quantification in Functional Distributional Semantics
    • [cs.CL]M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training
    • [cs.CL]Meta Dialogue Policy Learning
    • [cs.CL]Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1
    • [cs.CL]Response to LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts
    • [cs.CL]Self-Training for End-to-End Speech Translation
    • [cs.CL]Seq2Seq AI Chatbot with Attention Mechanism
    • [cs.CL]Syntactic Search by Example
    • [cs.CL]The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain
    • [cs.CL]Using Self-Training to Improve Back-Translation in Low Resource Neural Machine Translation
    • [cs.CR]A Distributed Trust Framework for Privacy-Preserving Machine Learning
    • [cs.CV]2D Image Features Detector And Descriptor Selection Expert System
    • [cs.CV]A Computational Model of Early Word Learning from the Infant’s Point of View
    • [cs.CV]A Siamese Neural Network with Modified Distance Loss For Transfer Learning in Speech Emotion Recognition
    • [cs.CV]Boundary-assisted Region Proposal Networks for Nucleus Segmentation
    • [cs.CV]CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser
    • [cs.CV]COMET: Context-Aware IoU-Guided Network for Small Object Tracking
    • [cs.CV]CircleNet: Anchor-free Detection with Circle Representation
    • [cs.CV]Efficient refinements on YOLOv3 for real-time detection and assessment of dia 902 betic foot Wagner grades
    • [cs.CV]Evaluation of Deep Segmentation Models for the Extraction of Retinal Lesions from Multi-modal Retinal Images
    • [cs.CV]FastReID: A Pytorch Toolbox for Real-world Person Re-identification
    • [cs.CV]GAN-Based Facial Attractiveness Enhancement
    • [cs.CV]Height estimation from single aerial images using a deep ordinal regression network
    • [cs.CV]Image Completion and Extrapolation with Contextual Cycle Consistency
    • [cs.CV]Info3D: Representation Learning on 3D Objects using Mutual Information Maximization and Contrastive Learning
    • [cs.CV]LRNNet: A Light-Weighted Network with Efficient Reduced Non-Local Operation for Real-Time Semantic Segmentation
    • [cs.CV]Look Locally Infer Globally: A Generalizable Face Anti-Spoofing Approach
    • [cs.CV]MFPP: Morphological Fragmental Perturbation Pyramid for Black-Box Model Explanations
    • [cs.CV]Multiple Generative Adversarial Networks Analysis for Predicting Photographers’ Retouching
    • [cs.CV]Phasic dopamine release identification using ensemble of AlexNet
    • [cs.CV]Problems of dataset creation for light source estimation
    • [cs.CV]RarePlanes: Synthetic Data Takes Flight
    • [cs.CV]Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
    • [cs.CV]Semi-supervised and Unsupervised Methods for Heart Sounds Classification in Restricted Data Environments
    • [cs.CV]Simple Unsupervised Multi-Object Tracking
    • [cs.CV]The Importance of Prior Knowledge in Precise Multimodal Prediction
    • [cs.CV]Unsupervised Depth Learning in Challenging Indoor Video: Weak Rectification to Rescue
    • [cs.CV]Visual Summarization of Lecture Video Segments for Enhanced Navigation
    • [cs.CV]Visually Guided Sound Source Separation using Cascaded Opponent Filter Network
    • [cs.CY]An optimizable scalar objective value cannot be objective and should not be the sole objective
    • [cs.CY]Countering hate on social media: Large scale classification of hate and counter speech
    • [cs.CY]Detecting Misinformation on WhatsApp without Breaking Encryption
    • [cs.CY]Digital Currency and the Economic Crisis: Helping States Respond
    • [cs.CY]SOS — Self-Organization for Survival: Introducing fairness in emergency communication to save lives
    • [cs.CY]Unionized Data Governance in Virtual Power Plants
    • [cs.DC]A Comparative Study of Data Storage and Processing Architectures for the Smart Grid
    • [cs.DC]An Automated Implementation of Hybrid Cloud for Performance Evaluation of Distributed Databases
    • [cs.DC]Boosting I/O and visualization for exascale era using Hercule: test case on RAMSES
    • [cs.DC]Is Blockchain Suitable for Data Freshness? — Age-of-Information Perspective
    • [cs.DC]MLOS: An Infrastructure for Automated Software Performance Engineering
    • [cs.DC]Multi-GPU Performance Optimization of a CFD Code using OpenACC on Different Platforms
    • [cs.DC]Scaling Distributed Training with Adaptive Summation
    • [cs.DC]Serving DNNs like Clockwork: Performance Predictability from the Bottom Up
    • [cs.DC]ToGCom: An Asymmetric Sybil Defense
    • [cs.DL]Characteristics of Dataset Retrieval Sessions: Experiences from a Real-life Digital Library
    • [cs.DL]Technological impact of biomedical research: the role of basicness and novelty
    • [cs.IR]Stopwords in Technical Language Processing
    • [cs.IR]Towards Personalized and Semantic Retrieval: An End-to-End Solution for E-commerce Search via Embedding Learning
    • [cs.IR]What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way
    • [cs.IT]Access-optimal Linear MDS Convertible Codes for All Parameters
    • [cs.IT]Asymmetric Leaky Private Information Retrieval
    • [cs.IT]Online Versus Offline Rate in Streaming Codes for Variable-Size Messages
    • [cs.IT]Robust Decoding from Binary Measurements with Cardinality Constraint Least Squares
    • [cs.IT]Strong Converse for Hypothesis Testing Against Independence Over A Noisy Channel
    • [cs.IT]Universal Graph Compression: Stochastic Block Models
    • [cs.IT]Wireless Communications for Collaborative Federated Learning in the Internet of Things
    • [cs.LG]A Polynomial Neural network with Controllable Precision and Human-Readable Topology II: Accelerated Approach Based on Expanded Layer
    • [cs.LG]Anomaly Detection with Tensor Networks
    • [cs.LG]Assessing Intelligence in Artificial Neural Networks
    • [cs.LG]Auto-decoding Graphs
    • [cs.LG]Bayesian optimization for modular black-box systems with switching costs
    • [cs.LG]Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains
    • [cs.LG]Characterizing the Weight Space for Different Learning Models
    • [cs.LG]Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty
    • [cs.LG]Differentiable Linear Bandit Algorithm
    • [cs.LG]Explaining The Behavior Of Black-Box Prediction Algorithms With Causal Learning
    • [cs.LG]Fast Unbalanced Optimal Transport on Tree
    • [cs.LG]Fuzzy c-Means Clustering for Persistence Diagrams
    • [cs.LG]Graphical Normalizing Flows
    • [cs.LG]Image Augmentations for GAN Training
    • [cs.LG]Learning across label confidence distributions using Filtered Transfer Learning
    • [cs.LG]MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning
    • [cs.LG]Meta-Model-Based Meta-Policy Optimization
    • [cs.LG]Network size and weights size for memorization with two-layers neural networks
    • [cs.LG]On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs
    • [cs.LG]Online mirror descent and dual averaging: keeping pace in the dynamic case
    • [cs.LG]Overcoming Overfitting and Large Weight Update Problem in Linear Rectifiers: Thresholded Exponential Rectified Linear Units
    • [cs.LG]Refined Continuous Control of DDPG Actors via Parametrised Activation
    • [cs.LG]Robust Sampling in Deep Learning
    • [cs.LG]Rényi Generative Adversarial Networks
    • [cs.LG]Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction
    • [cs.LG]Sample Efficient Graph-Based Optimization with Noisy Observations
    • [cs.LG]Some Theoretical Insights into Wasserstein GANs
    • [cs.LG]Sparsity in Reservoir Computing Neural Networks
    • [cs.LG]Towards Lower Bit Multiplication for Convolutional Neural Network Training
    • [cs.LG]Weight Pruning via Adaptive Sparsity Loss
    • [cs.LG]XGNN: Towards Model-Level Explanations of Graph Neural Networks
    • [cs.LO]Analogical Proportions
    • [cs.NE]A Novel Update Mechanism for Q-Networks Based On Extreme Learning Machines
    • [cs.NE]An Improved LSHADE-RSP Algorithm with the Cauchy Perturbation: iLSHADE-RSP
    • [cs.NE]Decomposition in Decision and Objective Space for Multi-Modal Multi-Objective Optimization
    • [cs.NE]Neural Network for Low-Memory IoT Devices and MNIST Image Recognition Using Kernels Based on Logistic Map
    • [cs.NE]Neuroevolutionary Transfer Learning of Deep Recurrent Neural Networks through Network-Aware Adaptation
    • [cs.NE]Stochastic-based Neural Network hardware acceleration for an efficient ligand-based virtual screening
    • [cs.NE]Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks
    • [cs.NI]Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
    • [cs.PL]Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference
    • [cs.RO]A Preliminary Study for a Quantum-like Robot Perception Model
    • [cs.RO]Autonomous Driving: Framework for Pedestrian Intention Estimationin a Real World Scenario
    • [cs.RO]Autonomous Vehicle Benchmarking using Unbiased Metrics
    • [cs.RO]Comment on “A Real-Time Approach for Chance-Constrained Motion Planning with Dynamic Obstacles”
    • [cs.RO]Distributed Localization without Direct Communication Inspired by Statistical Mechanics
    • [cs.RO]Fusion of Real Time Thermal Image and 1D/2D/3D Depth Laser Readings for Remote Thermal Sensing in Industrial Plants by Means of UAVs and/or Robots
    • [cs.RO]Manipulation with Shared Grasping
    • [cs.RO]Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor Maneuvers
    • [cs.RO]Risk-Aware Motion Planning for a Limbed Robot with Stochastic Gripping Forces Using Nonlinear Programming
    • [cs.SI]DASC: Towards A Road Damage-Aware Social-Media-Driven Car Sensing Framework for Disaster Response Applications
    • [cs.SI]Improving Speaker Identification using Network Knowledge in Criminal Conversational Data
    • [cs.SI]StationRank: Aggregate dynamics of the Swiss railway
    • [cs.SI]Structural balance in signed digraphs: considering transitivity to measure balance in graphs constructed by using different link signing methods
    • [cs.SI]The Impact of COVID-19 on Flight Networks
    • [cs.SI]The why, how, and when of representations for complex systems
    • [eess.AS]A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning
    • [eess.AS]CSTNet: Contrastive Speech Translation Network for Self-Supervised Speech Representation Learning
    • [eess.AS]Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR
    • [eess.IV]Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning
    • [eess.IV]DFR-TSD: A Deep Learning Based Framework for Robust Traffic Sign Detection Under Challenging Weather Conditions
    • [eess.IV]Deep Sequential Feature Learning in Clinical Image Classification of Infectious Keratitis
    • [eess.IV]Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images
    • [eess.IV]Pathological myopia classification with simultaneous lesion segmentation using deep learning
    • [eess.IV]Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet
    • [eess.SP]Cooperative Rate-Splitting for Secrecy Sum-Rate Enhancement in Multi-antenna Broadcast Channels
    • [eess.SP]Stochastic Graph Neural Networks
    • [math.OC]Local SGD With a Communication Overhead Depending Only on the Number of Workers
    • [math.OC]Optimization and passive flow control using single-step deep reinforcement learning
    • [math.ST]Asymptotics of Lower Dimensional Zero-Density Regions
    • [math.ST]Change-point tests for the tail parameter of Long Memory Stochastic Volatility time series
    • [math.ST]Entropic Optimal Transport between (Unbalanced) Gaussian Measures has a Closed Form
    • [math.ST]Estimation of Monotone Multi-Index Models
    • [math.ST]Non-lattice covering and quanitization of high dimensional sets
    • [math.ST]Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates
    • [math.ST]SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
    • [math.ST]Towards Asymptotic Optimality with Conditioned Stochastic Gradient Descent
    • [physics.ao-ph]Prediction of short and long-term droughts using artificial neural networks and hydro-meteorological variables
    • [physics.comp-ph]Autonomous Materials Discovery Driven by Gaussian Process Regression with Inhomogeneous Measurement Noise and Anisotropic Kernels
    • [physics.comp-ph]Integrating Machine Learning with Physics-Based Modeling
    • [physics.soc-ph]Severability of mesoscale components and local time scales in 8000 dynamical networks
    • [q-bio.NC]The growth and form of knowledge networks by kinesthetic curiosity
    • [q-fin.ST]A New Look to Three-Factor Fama-French Regression Model using Sample Innovations
    • [stat.AP]Time Series Methods and Ensemble Models to Nowcast Dengue at the State Level in Brazil
    • [stat.AP]Use Internet Search Data to Accurately Track State-Level Influenza Epidemics
    • [stat.CO]Median regression with differential privacy
    • [stat.ME]A note on the formulation of the Ensemble Adjustment Kalman Filter
    • [stat.ME]A statistical Testing Procedure for Validating Class Labels
    • [stat.ME]Bayesian clustering of high-dimensional data
    • [stat.ME]Classification with Valid and Adaptive Coverage
    • [stat.ME]Inferring food intake from multiple biomarkers using a latent variable model
    • [stat.ME]Model selection criteria for regression models with splines and the automatic localization of knots
    • [stat.ME]Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates
    • [stat.ME]Tensor Factor Model Estimation by Iterative Projection
    • [stat.ML]Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
    • [stat.ML]An efficient manifold density estimator for all recommendation systems
    • [stat.ML]Debiased Sinkhorn barycenters
    • [stat.ML]Double Generative Adversarial Networks for Conditional Independence Testing
    • [stat.ML]Generalized Penalty for Circular Coordinate Representation
    • [stat.ML]Handling missing data in model-based clustering
    • [stat.ML]Learning DAGs without imposing acyclicity
    • [stat.ML]Low-Rank Generalized Linear Bandit Problems
    • [stat.ML]On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
    • [stat.ML]Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits
    • [stat.ML]Quadruply Stochastic Gaussian Processes
    • [stat.ML]Shallow Neural Hawkes: Non-parametric kernel estimation for Hawkes processes
    • [stat.ML]Uncertainty quantification in medical image segmentation with Normalizing Flows
    ·····································
    • [cs.AI]Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning
    Dieqiao Feng, Carla P. Gomes, Bart Selman
    http://arxiv.org/abs/2006.02689v1
    • [cs.AI]Using Tabu Search Algorithm for Map Generation in the Terra Mystica Tabletop Game
    Alexandr Grichshenko, Luiz Jonata Pires de Araujo, Susanna Gimaeva, Joseph Alexander Brown
    http://arxiv.org/abs/2006.02716v1
    • [cs.CL]CiwGAN and fiwGAN: Encoding information in acoustic data to model lexical learning with Generative Adversarial Networks
    Gašper Beguš
    http://arxiv.org/abs/2006.02951v1
    • [cs.CL]End-to-End Speech-Translation with Knowledge Distillation: FBK@IWSLT2020
    Marco Gaido, Mattia Antonino Di Gangi, Matteo Negri, Marco Turchi
    http://arxiv.org/abs/2006.02965v1
    • [cs.CL]Experiments on Paraphrase Identification Using Quora Question Pairs Dataset
    Andreas Chandra, Ruben Stefanus
    http://arxiv.org/abs/2006.02648v1
    • [cs.CL]Extracting COVID-19 Events from Twitter
    Shi Zong, Ashutosh Baheti, Wei Xu, Alan Ritter
    http://arxiv.org/abs/2006.02567v1
    • [cs.CL]Linguists Who Use Probabilistic Models Love Them: Quantification in Functional Distributional Semantics
    Guy Emerson
    http://arxiv.org/abs/2006.03002v1
    • [cs.CL]M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training
    Haoyang Huang, Lin Su, Di Qi, Nan Duan, Edward Cui, Taroon Bharti, Lei Zhang, Lijuan Wang, Jianfeng Gao, Bei Liu, Jianlong Fu, Dongdong Zhang, Xin Liu, Ming Zhou
    http://arxiv.org/abs/2006.02635v1
    • [cs.CL]Meta Dialogue Policy Learning
    Yumo Xu, Chenguang Zhu, Baolin Peng, Michael Zeng
    http://arxiv.org/abs/2006.02588v1
    • [cs.CL]Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1
    Maria Nadejde, Joel Tetreault
    http://arxiv.org/abs/2006.02964v1
    • [cs.CL]Response to LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts
    Hao Wu, Gareth J. F. Jones, Francois Pitie
    http://arxiv.org/abs/2006.03022v1
    • [cs.CL]Self-Training for End-to-End Speech Translation
    Juan Pino, Qiantong Xu, Xutai Ma, Mohammad Javad Dousti, Yun Tang
    http://arxiv.org/abs/2006.02490v1
    • [cs.CL]Seq2Seq AI Chatbot with Attention Mechanism
    Abonia Sojasingarayar
    http://arxiv.org/abs/2006.02767v1
    • [cs.CL]Syntactic Search by Example
    Micah Shlain, Hillel Taub-Tabib, Shoval Sadde, Yoav Goldberg
    http://arxiv.org/abs/2006.03010v1
    • [cs.CL]The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain
    Annemarie Friedrich, Heike Adel, Federico Tomazic, Johannes Hingerl, Renou Benteau, Anika Maruscyk, Lukas Lange
    http://arxiv.org/abs/2006.03039v1
    • [cs.CL]Using Self-Training to Improve Back-Translation in Low Resource Neural Machine Translation
    Idris Abdulmumin, Bashir Shehu Galadanci, Abubakar Isa
    http://arxiv.org/abs/2006.02876v1
    • [cs.CR]A Distributed Trust Framework for Privacy-Preserving Machine Learning
    Will Abramson, Adam James Hall, Pavlos Papadopoulos, Nikolaos Pitropakis, William J Buchanan
    http://arxiv.org/abs/2006.02456v1
    • [cs.CV]2D Image Features Detector And Descriptor Selection Expert System
    Ibon Merino, Jon Azpiazu, Anthony Remazeilles, Basilio Sierra
    http://arxiv.org/abs/2006.02933v1
    • [cs.CV]A Computational Model of Early Word Learning from the Infant’s Point of View
    Satoshi Tsutsui, Arjun Chandrasekaran, Md Alimoor Reza, David Crandall, Chen Yu
    http://arxiv.org/abs/2006.02802v1
    • [cs.CV]A Siamese Neural Network with Modified Distance Loss For Transfer Learning in Speech Emotion Recognition
    Kexin Feng, Theodora Chaspari
    http://arxiv.org/abs/2006.03001v1
    • [cs.CV]Boundary-assisted Region Proposal Networks for Nucleus Segmentation
    Shengcong Chen, Changxing Ding, Dacheng Tao
    http://arxiv.org/abs/2006.02695v1
    • [cs.CV]CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser
    Julián Tachella, Junqi Tang, Mike Davies
    http://arxiv.org/abs/2006.02379v2
    • [cs.CV]COMET: Context-Aware IoU-Guided Network for Small Object Tracking
    Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Hossein Ghanei-Yakhdan, Shohreh Kasaei, Li Cheng
    http://arxiv.org/abs/2006.02597v1
    • [cs.CV]CircleNet: Anchor-free Detection with Circle Representation
    Haichun Yang, Ruining Deng, Yuzhe Lu, Zheyu Zhu, Ye Chen, Joseph T. Roland, Le Lu, Bennett A. Landman, Agnes B. Fogo, Yuankai Huo
    http://arxiv.org/abs/2006.02474v1
    • [cs.CV]Efficient refinements on YOLOv3 for real-time detection and assessment of dia 902 betic foot Wagner grades
    Aifu Han, Yongze Zhang, Ajuan Li, Changjin Li, Fengying Zhao, Qiujie Dong, Qin Liu, Yanting Liu, Ximei Shen, Sunjie Yan, Shengzong Zhou
    http://arxiv.org/abs/2006.02322v2
    • [cs.CV]Evaluation of Deep Segmentation Models for the Extraction of Retinal Lesions from Multi-modal Retinal Images
    Taimur Hassan, Muhammad Usman Akram, Naoufel Werghi
    http://arxiv.org/abs/2006.02662v1
    • [cs.CV]FastReID: A Pytorch Toolbox for Real-world Person Re-identification
    Lingxiao He, Xingyu Liao, Wu Liu, Xinchen Liu, Peng Cheng, Tao Mei
    http://arxiv.org/abs/2006.02631v1
    • [cs.CV]GAN-Based Facial Attractiveness Enhancement
    Yuhongze Zhou, Qinjie Xiao
    http://arxiv.org/abs/2006.02766v1
    • [cs.CV]Height estimation from single aerial images using a deep ordinal regression network
    Xiang Li, Mingyang Wang, Yi Fang
    http://arxiv.org/abs/2006.02801v1
    • [cs.CV]Image Completion and Extrapolation with Contextual Cycle Consistency
    Sai Hemanth Kasaraneni, Abhishek Mishra
    http://arxiv.org/abs/2006.02620v1
    • [cs.CV]Info3D: Representation Learning on 3D Objects using Mutual Information Maximization and Contrastive Learning
    Aditya Sanghi
    http://arxiv.org/abs/2006.02598v1
    • [cs.CV]LRNNet: A Light-Weighted Network with Efficient Reduced Non-Local Operation for Real-Time Semantic Segmentation
    Weihao Jiang, Zhaozhi Xie, Yaoyi Li, Chang Liu, Hongtao Lu
    http://arxiv.org/abs/2006.02706v1
    • [cs.CV]Look Locally Infer Globally: A Generalizable Face Anti-Spoofing Approach
    Debayan Deb, Anil K. Jain
    http://arxiv.org/abs/2006.02834v1
    • [cs.CV]MFPP: Morphological Fragmental Perturbation Pyramid for Black-Box Model Explanations
    Qing Yang, Xia Zhu, Yun Ye, Jong-Kae Fwu, Ganmei You, Yuan Zhu
    http://arxiv.org/abs/2006.02659v1
    • [cs.CV]Multiple Generative Adversarial Networks Analysis for Predicting Photographers’ Retouching
    Marc Bickel, Samuel Dubuis, Sébastien Gachoud
    http://arxiv.org/abs/2006.02921v1
    • [cs.CV]Phasic dopamine release identification using ensemble of AlexNet
    Luca Patarnello, Marco Celin, Loris Nanni
    http://arxiv.org/abs/2006.02536v1
    • [cs.CV]Problems of dataset creation for light source estimation
    E. I. Ershov, A. V. Belokopytov, A. V. Savchik
    http://arxiv.org/abs/2006.02692v1
    • [cs.CV]RarePlanes: Synthetic Data Takes Flight
    Jacob Shermeyer, Thomas Hossler, Adam Van Etten, Daniel Hogan, Ryan Lewis, Daeil Kim
    http://arxiv.org/abs/2006.02963v1
    • [cs.CV]Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
    Yixiao Ge, Dapeng Chen, Feng Zhu, Rui Zhao, Hongsheng Li
    http://arxiv.org/abs/2006.02713v1
    • [cs.CV]Semi-supervised and Unsupervised Methods for Heart Sounds Classification in Restricted Data Environments
    Balagopal Unnikrishnan, Pranshu Ranjan Singh, Xulei Yang, Matthew Chin Heng Chua
    http://arxiv.org/abs/2006.02610v1
    • [cs.CV]Simple Unsupervised Multi-Object Tracking
    Shyamgopal Karthik, Ameya Prabhu, Vineet Gandhi
    http://arxiv.org/abs/2006.02609v1
    • [cs.CV]The Importance of Prior Knowledge in Precise Multimodal Prediction
    Sergio Casas, Cole Gulino, Simon Suo, Raquel Urtasun
    http://arxiv.org/abs/2006.02636v1
    • [cs.CV]Unsupervised Depth Learning in Challenging Indoor Video: Weak Rectification to Rescue
    Jia-Wang Bian, Huangying Zhan, Naiyan Wang, Tat-Jun Chin, Chunhua Shen, Ian Reid
    http://arxiv.org/abs/2006.02708v1
    • [cs.CV]Visual Summarization of Lecture Video Segments for Enhanced Navigation
    Mohammad Rajiur Rahman, Jaspal Subhlok, Shishir Shah
    http://arxiv.org/abs/2006.02434v1
    • [cs.CV]Visually Guided Sound Source Separation using Cascaded Opponent Filter Network
    Lingyu Zhu, Esa Rahtu
    http://arxiv.org/abs/2006.03028v1
    • [cs.CY]An optimizable scalar objective value cannot be objective and should not be the sole objective
    Isabel Kloumann, Mark Tygert
    http://arxiv.org/abs/2006.02577v1
    • [cs.CY]Countering hate on social media: Large scale classification of hate and counter speech
    Joshua Garland, Keyan Ghazi-Zahedi, Jean-Gabriel Young, Laurent Hébert-Dufresne, Mirta Galesic
    http://arxiv.org/abs/2006.01974v2
    • [cs.CY]Detecting Misinformation on WhatsApp without Breaking Encryption
    Julio C. S. Reis, Philipe de Freitas Melo, Kiran Garimella, Fabrício Benevenuto
    http://arxiv.org/abs/2006.02471v1
    • [cs.CY]Digital Currency and the Economic Crisis: Helping States Respond
    Geoffrey Goodell, Hazem Danny Al-Nakib, Paolo Tasca
    http://arxiv.org/abs/2006.03023v1
    • [cs.CY]SOS — Self-Organization for Survival: Introducing fairness in emergency communication to save lives
    Indushree Banerjee, Martijn Warnier, Frances M. T. Brazier, Dirk Helbing
    http://arxiv.org/abs/2006.02825v1
    • [cs.CY]Unionized Data Governance in Virtual Power Plants
    Niels Ørbæk Chemnitz, Philippe Bonnet, Irina Shklovski, Sebastian Büttrich, Laura Watts
    http://arxiv.org/abs/2006.02709v1
    • [cs.DC]A Comparative Study of Data Storage and Processing Architectures for the Smart Grid
    Marıa Arenas-Martınez, Sergio Herrero-Lopez, Abel Sanchez, John R. Williams, Paul Roth, Paul Hofmann, Alexander Zeier
    http://arxiv.org/abs/2006.02515v1
    • [cs.DC]An Automated Implementation of Hybrid Cloud for Performance Evaluation of Distributed Databases
    Yaser Mansouri, Victor Prokhorenko, M. Ali Babar
    http://arxiv.org/abs/2006.02833v1
    • [cs.DC]Boosting I/O and visualization for exascale era using Hercule: test case on RAMSES
    Loic Strafella, Damien Chapon
    http://arxiv.org/abs/2006.02759v1
    • [cs.DC]Is Blockchain Suitable for Data Freshness? — Age-of-Information Perspective
    Sungho Lee, Minsu Kim, Jemin Lee, Ruei-Hau Hsu, Tony Q. S. Quek
    http://arxiv.org/abs/2006.02735v1
    • [cs.DC]MLOS: An Infrastructure for Automated Software Performance Engineering
    Carlo Curino, Neha Godwal, Brian Kroth, Sergiy Kuryata, Greg Lapinski, Siqi Liu, Slava Oks, Olga Poppe, Adam Smiechowski, Ed Thayer, Markus Weimer, Yiwen Zhu
    http://arxiv.org/abs/2006.02155v2
    • [cs.DC]Multi-GPU Performance Optimization of a CFD Code using OpenACC on Different Platforms
    Weicheng Xue, Christopher J. Roy
    http://arxiv.org/abs/2006.02602v1
    • [cs.DC]Scaling Distributed Training with Adaptive Summation
    Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Olli Saarikivi, Tianju Xu, Vadim Eksarevskiy, Jaliya Ekanayake, Emad Barsoum
    http://arxiv.org/abs/2006.02924v1
    • [cs.DC]Serving DNNs like Clockwork: Performance Predictability from the Bottom Up
    Arpan Gujarati, Reza Karimi, Safya Alzayat, Antoine Kaufmann, Ymir Vigfusson, Jonathan Mace
    http://arxiv.org/abs/2006.02464v1
    • [cs.DC]ToGCom: An Asymmetric Sybil Defense
    Diksha Gupta, Jared Saia, Maxwell Young
    http://arxiv.org/abs/2006.02893v1
    • [cs.DL]Characteristics of Dataset Retrieval Sessions: Experiences from a Real-life Digital Library
    Zeljko Carevic, Dwaipayan Roy, Philipp Mayr
    http://arxiv.org/abs/2006.02770v1
    • [cs.DL]Technological impact of biomedical research: the role of basicness and novelty
    Qing Ke
    http://arxiv.org/abs/2006.02472v1
    • [cs.IR]Stopwords in Technical Language Processing
    Serhad Sarica, Jianxi Luo
    http://arxiv.org/abs/2006.02633v1
    • [cs.IR]Towards Personalized and Semantic Retrieval: An End-to-End Solution for E-commerce Search via Embedding Learning
    Han Zhang, Songlin Wang, Kang Zhang, Zhiling Tang, Yunjiang Jiang, Yun Xiao, Weipeng Yan, Wen-Yun Yang
    http://arxiv.org/abs/2006.02282v2
    • [cs.IR]What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way
    Erik Faessler, Michel Oleynik, Udo Hahn
    http://arxiv.org/abs/2006.02785v1
    • [cs.IT]Access-optimal Linear MDS Convertible Codes for All Parameters
    Francisco Maturana, V. S. Chaitanya Mukka, K. V. Rashmi
    http://arxiv.org/abs/2006.03042v1
    • [cs.IT]Asymmetric Leaky Private Information Retrieval
    Islam Samy, Mohamed A. Attia, Ravi Tandon, Loukas Lazos
    http://arxiv.org/abs/2006.03048v1
    • [cs.IT]Online Versus Offline Rate in Streaming Codes for Variable-Size Messages
    Michael Rudow, K. V. Rashmi
    http://arxiv.org/abs/2006.03045v1
    • [cs.IT]Robust Decoding from Binary Measurements with Cardinality Constraint Least Squares
    Zhao Ding, Junjun Huang, Yuling Jiao, Xiliang Lu, Zhijian Yang
    http://arxiv.org/abs/2006.02890v1
    • [cs.IT]Strong Converse for Hypothesis Testing Against Independence Over A Noisy Channel
    Daming Cao, Lin Zhou
    http://arxiv.org/abs/2006.02869v1
    • [cs.IT]Universal Graph Compression: Stochastic Block Models
    Alankrita Bhatt, Chi Wang, Lele Wang, Ziao Wang
    http://arxiv.org/abs/2006.02643v1
    • [cs.IT]Wireless Communications for Collaborative Federated Learning in the Internet of Things
    Mingzhe Chen, H. Vincent Poor, Walid Saad, Shuguang Cui
    http://arxiv.org/abs/2006.02499v1
    • [cs.LG]A Polynomial Neural network with Controllable Precision and Human-Readable Topology II: Accelerated Approach Based on Expanded Layer
    Gang Liu, Jing Wang
    http://arxiv.org/abs/2006.02901v1
    • [cs.LG]Anomaly Detection with Tensor Networks
    Jinhui Wang, Chase Roberts, Guifre Vidal, Stefan Leichenauer
    http://arxiv.org/abs/2006.02516v1
    • [cs.LG]Assessing Intelligence in Artificial Neural Networks
    Nicholas J. Schaub, Nathan Hotaling
    http://arxiv.org/abs/2006.02909v1
    • [cs.LG]Auto-decoding Graphs
    Sohil Atul Shah, Vladlen Koltun
    http://arxiv.org/abs/2006.02879v1
    • [cs.LG]Bayesian optimization for modular black-box systems with switching costs
    Chi-Heng Lin, Joseph D. Miano, Eva L. Dyer
    http://arxiv.org/abs/2006.02624v1
    • [cs.LG]Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains
    James Bannon, Brad Windsor, Wenbo Song, Tao Li
    http://arxiv.org/abs/2006.02579v1
    • [cs.LG]Characterizing the Weight Space for Different Learning Models
    Saurav Musunuru, Jay N. Paranjape, Rahul Kumar Dubey, Vijendran G. Venkoparao
    http://arxiv.org/abs/2006.02724v1
    • [cs.LG]Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty
    Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Río Chanona
    http://arxiv.org/abs/2006.02750v1
    • [cs.LG]Differentiable Linear Bandit Algorithm
    Kaige Yang, Laura Toni
    http://arxiv.org/abs/2006.03000v1
    • [cs.LG]Explaining The Behavior Of Black-Box Prediction Algorithms With Causal Learning
    Numair Sani, Daniel Malinsky, Ilya Shpitser
    http://arxiv.org/abs/2006.02482v1
    • [cs.LG]Fast Unbalanced Optimal Transport on Tree
    Ryoma Sato, Makoto Yamada, Hisashi Kashima
    http://arxiv.org/abs/2006.02703v1
    • [cs.LG]Fuzzy c-Means Clustering for Persistence Diagrams
    Thomas O. M. Davies, Jack Aspinall, Bryan Wilder, Long Tran-Thanh
    http://arxiv.org/abs/2006.02796v1
    • [cs.LG]Graphical Normalizing Flows
    Antoine Wehenkel, Gilles Louppe
    http://arxiv.org/abs/2006.02548v1
    • [cs.LG]Image Augmentations for GAN Training
    Zhengli Zhao, Zizhao Zhang, Ting Chen, Sameer Singh, Han Zhang
    http://arxiv.org/abs/2006.02595v1
    • [cs.LG]Learning across label confidence distributions using Filtered Transfer Learning
    Seyed Ali Madani Tonekaboni, Andrew E. Brereton, Zhaleh Safikhani, Andreas Windemuth, Benjamin Haibe-Kains, Stephen MacKinnon
    http://arxiv.org/abs/2006.02528v1
    • [cs.LG]MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning
    Miguel Vasco, Francisco S. Melo, Ana Paiva
    http://arxiv.org/abs/2006.02991v1
    • [cs.LG]Meta-Model-Based Meta-Policy Optimization
    Takuya Hiraoka, Takahisa Imagawa, Voot Tangkaratt, Takayuki Osa, Takashi Onishi, Yoshimasa Tsuruoka
    http://arxiv.org/abs/2006.02608v1
    • [cs.LG]Network size and weights size for memorization with two-layers neural networks
    Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer
    http://arxiv.org/abs/2006.02855v1
    • [cs.LG]On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs
    Matilde Gargiani, Andrea Zanelli, Moritz Diehl, Frank Hutter
    http://arxiv.org/abs/2006.02409v2
    • [cs.LG]Online mirror descent and dual averaging: keeping pace in the dynamic case
    Huang Fang, Nicholas J. A. Harvey, Victor S. Portella, Michael P. Friedlander
    http://arxiv.org/abs/2006.02585v1
    • [cs.LG]Overcoming Overfitting and Large Weight Update Problem in Linear Rectifiers: Thresholded Exponential Rectified Linear Units
    Vijay Pandey
    http://arxiv.org/abs/2006.02797v1
    • [cs.LG]Refined Continuous Control of DDPG Actors via Parametrised Activation
    Mohammed Hossny, Julie Iskander, Mohammed Attia, Khaled Saleh
    http://arxiv.org/abs/2006.02818v1
    • [cs.LG]Robust Sampling in Deep Learning
    Aurora Cobo Aguilera, Antonio Artés-Rodríguez, Fernando Pérez-Cruz
    http://arxiv.org/abs/2006.02734v1
    • [cs.LG]Rényi Generative Adversarial Networks
    Himesh Bhatia, William Paul, Fady Alajaji, Bahman Gharesifard, Philippe Burlina
    http://arxiv.org/abs/2006.02479v1
    • [cs.LG]Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction
    Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen
    http://arxiv.org/abs/2006.03041v1
    • [cs.LG]Sample Efficient Graph-Based Optimization with Noisy Observations
    Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori, Anup Rao, Branislav Kveton
    http://arxiv.org/abs/2006.02672v1
    • [cs.LG]Some Theoretical Insights into Wasserstein GANs
    Gérard Biau, Maxime Sangnier, Ugo Tanielian
    http://arxiv.org/abs/2006.02682v1
    • [cs.LG]Sparsity in Reservoir Computing Neural Networks
    Claudio Gallicchio
    http://arxiv.org/abs/2006.02957v1
    • [cs.LG]Towards Lower Bit Multiplication for Convolutional Neural Network Training
    Kai Zhong, Tianchen Zhao, Xuefei Ning, Shulin Zeng, Kaiyuan Guo, Yu Wang, Huazhong Yang
    http://arxiv.org/abs/2006.02804v1
    • [cs.LG]Weight Pruning via Adaptive Sparsity Loss
    George Retsinas, Athena Elafrou, Georgios Goumas, Petros Maragos
    http://arxiv.org/abs/2006.02768v1
    • [cs.LG]XGNN: Towards Model-Level Explanations of Graph Neural Networks
    Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji
    http://arxiv.org/abs/2006.02587v1
    • [cs.LO]Analogical Proportions
    Christian Antić
    http://arxiv.org/abs/2006.02854v1
    • [cs.NE]A Novel Update Mechanism for Q-Networks Based On Extreme Learning Machines
    Callum Wilson, Annalisa Riccardi, Edmondo Minisci
    http://arxiv.org/abs/2006.02986v1
    • [cs.NE]An Improved LSHADE-RSP Algorithm with the Cauchy Perturbation: iLSHADE-RSP
    Tae Jong Choi, Chang Wook Ahn
    http://arxiv.org/abs/2006.02591v1
    • [cs.NE]Decomposition in Decision and Objective Space for Multi-Modal Multi-Objective Optimization
    Monalisa Pal, Sanghamitra Bandyopadhyay
    http://arxiv.org/abs/2006.02628v1
    • [cs.NE]Neural Network for Low-Memory IoT Devices and MNIST Image Recognition Using Kernels Based on Logistic Map
    Andrei Velichko
    http://arxiv.org/abs/2006.02824v1
    • [cs.NE]Neuroevolutionary Transfer Learning of Deep Recurrent Neural Networks through Network-Aware Adaptation
    AbdElRahman ElSaid, Joshua Karns, Alexander Ororbia II, Daniel Krutz, Zimeng Lyu, Travis Desell
    http://arxiv.org/abs/2006.02655v1
    • [cs.NE]Stochastic-based Neural Network hardware acceleration for an efficient ligand-based virtual screening
    Christian F. Frasser, Carola de Benito, Vincent Canals, Miquel Roca, Pedro J. Ballester, Josep L. Rossello
    http://arxiv.org/abs/2006.02505v1
    • [cs.NE]Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks
    Jinseok Kim, Kyungsu Kim, Jae-Joon Kim
    http://arxiv.org/abs/2006.02642v1
    • [cs.NI]Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
    Yi Liu, Xingliang Yuan, Zehui Xiong, Jiawen Kang, Xiaofei Wang, Dusit Niyato
    http://arxiv.org/abs/2006.02931v1
    • [cs.PL]Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference
    Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang
    http://arxiv.org/abs/2006.03031v1
    • [cs.RO]A Preliminary Study for a Quantum-like Robot Perception Model
    Davide Lanza, Paolo Solinas, Fulvio Mastrogiovanni
    http://arxiv.org/abs/2006.02771v1
    • [cs.RO]Autonomous Driving: Framework for Pedestrian Intention Estimationin a Real World Scenario
    Walter Morales Alvarez, Francisco Miguel Moreno, Oscar Sipele, Nikita Smirnov, Cristina Olaverri-Monreal
    http://arxiv.org/abs/2006.02711v1
    • [cs.RO]Autonomous Vehicle Benchmarking using Unbiased Metrics
    David Paz, Po-jung Lai, Nathan Chan, Yuqing Jiang, Henrik I. Christensen
    http://arxiv.org/abs/2006.02518v1
    • [cs.RO]Comment on “A Real-Time Approach for Chance-Constrained Motion Planning with Dynamic Obstacles”
    Hai Zhu, Javier Alonso-Mora
    http://arxiv.org/abs/2006.02747v1
    • [cs.RO]Distributed Localization without Direct Communication Inspired by Statistical Mechanics
    Jingxian Wang, Tianye Wang, Wei Wang, Xiwang Dong, Yandong Wang
    http://arxiv.org/abs/2006.02658v1
    • [cs.RO]Fusion of Real Time Thermal Image and 1D/2D/3D Depth Laser Readings for Remote Thermal Sensing in Industrial Plants by Means of UAVs and/or Robots
    Corneliu Arsene
    http://arxiv.org/abs/2006.01286v3
    • [cs.RO]Manipulation with Shared Grasping
    Yifan Hou, Zhenzhong Jia, Matthew T. Mason
    http://arxiv.org/abs/2006.02996v1
    • [cs.RO]Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor Maneuvers
    Gilhyun Ryou, Ezra Tal, Sertac Karaman
    http://arxiv.org/abs/2006.02513v1
    • [cs.RO]Risk-Aware Motion Planning for a Limbed Robot with Stochastic Gripping Forces Using Nonlinear Programming
    Yuki Shirai, Xuan Lin, Yusuke Tanaka, Ankur Mehta, Dennis Hong
    http://arxiv.org/abs/2006.02656v1
    • [cs.SI]DASC: Towards A Road Damage-Aware Social-Media-Driven Car Sensing Framework for Disaster Response Applications
    Md Tahmid Rashid, Daniel, Zhang, Dong Wang
    http://arxiv.org/abs/2006.02681v1
    • [cs.SI]Improving Speaker Identification using Network Knowledge in Criminal Conversational Data
    Mael Fabien, Seyyed Saeed Sarfjoo, Petr Motlicek, Srikanth Madikeri
    http://arxiv.org/abs/2006.02093v2
    • [cs.SI]StationRank: Aggregate dynamics of the Swiss railway
    Georg Anagnostopoulos, Vahid Moosavi
    http://arxiv.org/abs/2006.02781v1
    • [cs.SI]Structural balance in signed digraphs: considering transitivity to measure balance in graphs constructed by using different link signing methods
    Ly Dinh, Rezvaneh Rezapour, Lan Jiang, Jana Diesner
    http://arxiv.org/abs/2006.02565v1
    • [cs.SI]The Impact of COVID-19 on Flight Networks
    Toyotaro Suzumura, Hiroki Kanezashi, Mishal Dholakia, Euma Ishii, Sergio Alvarez Napagao, Raquel Pérez-Arnal, Dario Garcia-Gasulla
    http://arxiv.org/abs/2006.02950v1
    • [cs.SI]The why, how, and when of representations for complex systems
    Leo Torres, Ann S. Blevins, Danielle S. Bassett, Tina Eliassi-Rad
    http://arxiv.org/abs/2006.02870v1
    • [eess.AS]A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning
    Sameer Khurana, Antoine Laurent, Wei-Ning Hsu, Jan Chorowski, Adrian Lancucki, Ricard Marxer, James Glass
    http://arxiv.org/abs/2006.02547v1
    • [eess.AS]CSTNet: Contrastive Speech Translation Network for Self-Supervised Speech Representation Learning
    Sameer Khurana, Antoine Laurent, James Glass
    http://arxiv.org/abs/2006.02814v1
    • [eess.AS]Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR
    Thilo von Neumann, Christoph Boeddeker, Lukas Drude, Keisuke Kinoshita, Marc Delcroix, Tomohiro Nakatani, Reinhold Haeb-Umbach
    http://arxiv.org/abs/2006.02786v1
    • [eess.IV]Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning
    Yukun Guo, Tristan T. Hormel, Honglian Xiong, Jie Wang, Thomas S. Hwang, Yali Jia
    http://arxiv.org/abs/2006.02569v1
    • [eess.IV]DFR-TSD: A Deep Learning Based Framework for Robust Traffic Sign Detection Under Challenging Weather Conditions
    Sabbir Ahmed, Uday Kamal, Md. Kamrul Hasan
    http://arxiv.org/abs/2006.02578v1
    • [eess.IV]Deep Sequential Feature Learning in Clinical Image Classification of Infectious Keratitis
    Yesheng Xu, Ming Kong, Wenjia Xie, Runping Duan, Zhengqing Fang, Yuxiao Lin, Qiang Zhu, Siliang Tang, Fei Wu, Yu-Feng Yao
    http://arxiv.org/abs/2006.02666v1
    • [eess.IV]Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images
    Soumick Chatterjee, Fatima Saad, Chompunuch Sarasaen, Suhita Ghosh, Rupali Khatun, Petia Radeva, Georg Rose, Sebastian Stober, Oliver Speck, Andreas Nürnberger
    http://arxiv.org/abs/2006.02570v1
    • [eess.IV]Pathological myopia classification with simultaneous lesion segmentation using deep learning
    Ruben Hemelings, Bart Elen, Matthew B. Blaschko, Julie Jacob, Ingeborg Stalmans, Patrick De Boever
    http://arxiv.org/abs/2006.02813v1
    • [eess.IV]Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet
    Sara Ranjbar, Kyle W. Singleton, Lee Curtin, Cassandra R. Rickertsen, Lisa E. Paulson, Leland S. Hu, J. Ross Mitchell, Kristin R. Swanson
    http://arxiv.org/abs/2006.02627v1
    • [eess.SP]Cooperative Rate-Splitting for Secrecy Sum-Rate Enhancement in Multi-antenna Broadcast Channels
    Ping Li, Ming Chen, Yijie Mao, Zhaohui Yang, Bruno Clerckx, Mohammad Shikh-Bahaei
    http://arxiv.org/abs/2006.02555v1
    • [eess.SP]Stochastic Graph Neural Networks
    Zhan Gao, Elvin Isufi, Alejandro Ribeiro
    http://arxiv.org/abs/2006.02684v1
    • [math.OC]Local SGD With a Communication Overhead Depending Only on the Number of Workers
    Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis
    http://arxiv.org/abs/2006.02582v1
    • [math.OC]Optimization and passive flow control using single-step deep reinforcement learning
    H. Ghraieb, J. Viquerat, A. Larcher, P. Meliga, E. Hachem
    http://arxiv.org/abs/2006.02979v1
    • [math.ST]Asymptotics of Lower Dimensional Zero-Density Regions
    Hengrui Luo, Steve N. MacEachern, Mario Peruggia
    http://arxiv.org/abs/2006.02568v1
    • [math.ST]Change-point tests for the tail parameter of Long Memory Stochastic Volatility time series
    Annika Betken, Davide Giraudo, Rafał Kulik
    http://arxiv.org/abs/2006.02667v1
    • [math.ST]Entropic Optimal Transport between (Unbalanced) Gaussian Measures has a Closed Form
    Hicham Janati, Boris Muzellec, Gabriel Peyré, Marco Cuturi
    http://arxiv.org/abs/2006.02572v1
    • [math.ST]Estimation of Monotone Multi-Index Models
    David Gamarnik, Julia Gaudio
    http://arxiv.org/abs/2006.02806v1
    • [math.ST]Non-lattice covering and quanitization of high dimensional sets
    Jack Noonan, Anatoly Zhigljavsky
    http://arxiv.org/abs/2006.02705v1
    • [math.ST]Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates
    Jeff Calder, Dejan Slepčev, Matthew Thorpe
    http://arxiv.org/abs/2006.02765v1
    • [math.ST]SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
    Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet
    http://arxiv.org/abs/2006.02509v1
    • [math.ST]Towards Asymptotic Optimality with Conditioned Stochastic Gradient Descent
    Rémi Leluc, François Portier
    http://arxiv.org/abs/2006.02745v1
    • [physics.ao-ph]Prediction of short and long-term droughts using artificial neural networks and hydro-meteorological variables
    Yousef Hassanzadeh, Mohammadvaghef Ghazvinian, Amin Abdi, Saman Baharvand, Ali Jozaghi
    http://arxiv.org/abs/2006.02581v1
    • [physics.comp-ph]Autonomous Materials Discovery Driven by Gaussian Process Regression with Inhomogeneous Measurement Noise and Anisotropic Kernels
    Marcus M. Noack, Gregory S. Doerk, Ruipeng Li, Jason K. Streit, Richard A. Vaia, Kevin G. Yager, Masafumi Fukuto
    http://arxiv.org/abs/2006.02489v1
    • [physics.comp-ph]Integrating Machine Learning with Physics-Based Modeling
    Weinan E, Jiequn Han, Linfeng Zhang
    http://arxiv.org/abs/2006.02619v1
    • [physics.soc-ph]Severability of mesoscale components and local time scales in 8000 dynamical networks
    Yun William Yu, Jean-Charles Delvenne, Sophia N. Yaliraki, Mauricio Barahona
    http://arxiv.org/abs/2006.02972v1
    • [q-bio.NC]The growth and form of knowledge networks by kinesthetic curiosity
    Dale Zhou, David M. Lydon-Staley, Perry Zurn, Danielle S. Bassett
    http://arxiv.org/abs/2006.02949v1
    • [q-fin.ST]A New Look to Three-Factor Fama-French Regression Model using Sample Innovations
    Javad Shaabani, Ali Akbar Jafari
    http://arxiv.org/abs/2006.02467v1
    • [stat.AP]Time Series Methods and Ensemble Models to Nowcast Dengue at the State Level in Brazil
    Katherine Kempfert, Kaitlyn Martinez, Amir Siraj, Jessica Conrad, Geoffrey Fairchild, Amanda Ziemann, Nidhi Parikh, David Osthus, Nicholas Generous, Sara Del Valle, Carrie Manore
    http://arxiv.org/abs/2006.02483v1
    • [stat.AP]Use Internet Search Data to Accurately Track State-Level Influenza Epidemics
    Shihao Yang, Shaoyang Ning, S. C. Kou
    http://arxiv.org/abs/2006.02927v1
    • [stat.CO]Median regression with differential privacy
    E Chen, Ying Miao, Yu Tang
    http://arxiv.org/abs/2006.02983v1
    • [stat.ME]A note on the formulation of the Ensemble Adjustment Kalman Filter
    Ian Grooms
    http://arxiv.org/abs/2006.02941v1
    • [stat.ME]A statistical Testing Procedure for Validating Class Labels
    Melissa C. Key, Ben Boukai
    http://arxiv.org/abs/2006.03025v1
    • [stat.ME]Bayesian clustering of high-dimensional data
    Noirrit Kiran Chandra, Antonio Canale, David B. Dunson
    http://arxiv.org/abs/2006.02700v1
    • [stat.ME]Classification with Valid and Adaptive Coverage
    Yaniv Romano, Matteo Sesia, Emmanuel J. Candès
    http://arxiv.org/abs/2006.02544v1
    • [stat.ME]Inferring food intake from multiple biomarkers using a latent variable model
    Silvia D’Angelo, Lorraine Brennan, Isobel Claire Gormley
    http://arxiv.org/abs/2006.02995v1
    • [stat.ME]Model selection criteria for regression models with splines and the automatic localization of knots
    Alex Rodrigo dos S. Sousa, Magno T. F. Severino, Florencia G. Leonardi
    http://arxiv.org/abs/2006.02649v1
    • [stat.ME]Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates
    Mark Tygert
    http://arxiv.org/abs/2006.02504v1
    • [stat.ME]Tensor Factor Model Estimation by Iterative Projection
    Yuefeng Han, Rong Chen, Dan Yang, Cun-Hui Zhang
    http://arxiv.org/abs/2006.02611v1
    • [stat.ML]Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
    Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James Duncan
    http://arxiv.org/abs/2006.02493v1
    • [stat.ML]An efficient manifold density estimator for all recommendation systems
    Jacek Dąbrowski, Barbara Rychalska, Michał Daniluk, Dominika Basaj, Piotr Babel, Andrzej Michałowski
    http://arxiv.org/abs/2006.01894v2
    • [stat.ML]Debiased Sinkhorn barycenters
    Hicham Janati, Marco Cuturi, Alexandre Gramfort
    http://arxiv.org/abs/2006.02575v1
    • [stat.ML]Double Generative Adversarial Networks for Conditional Independence Testing
    Chengchun Shi, Tianlin Xu, Wicher Bergsma, Lexin Li
    http://arxiv.org/abs/2006.02615v1
    • [stat.ML]Generalized Penalty for Circular Coordinate Representation
    Hengrui Luo, Alice Patania, Jisu Kim, Mikael Vejdemo-Johansson
    http://arxiv.org/abs/2006.02554v1
    • [stat.ML]Handling missing data in model-based clustering
    Alessio Serafini, Thomas Brendan Murphy, Luca Scrucca
    http://arxiv.org/abs/2006.02954v1
    • [stat.ML]Learning DAGs without imposing acyclicity
    Gherardo Varando
    http://arxiv.org/abs/2006.03005v1
    • [stat.ML]Low-Rank Generalized Linear Bandit Problems
    Yangyi Lu, Amirhossein Meisami, Ambuj Tewari
    http://arxiv.org/abs/2006.02948v1
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