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
• [stat.ML]On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
http://arxiv.org/abs/2006.02601v1
• [stat.ML]Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran
http://arxiv.org/abs/2006.02612v1
• [stat.ML]Quadruply Stochastic Gaussian Processes
Trefor W. Evans, Prasanth B. Nair
http://arxiv.org/abs/2006.03015v1
• [stat.ML]Shallow Neural Hawkes: Non-parametric kernel estimation for Hawkes processes
Sobin Joseph, Lekhapriya Dheeraj Kashyap, Shashi Jain
http://arxiv.org/abs/2006.02460v1
• [stat.ML]Uncertainty quantification in medical image segmentation with Normalizing Flows
Raghavendra Selvan, Frederik Faye, Jon Middleton, Akshay Pai
http://arxiv.org/abs/2006.02683v1