cond-mat.stat-mech - 统计数学 cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.ET - 新兴技术 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.DS - 动力系统 math.OC - 优化与控制 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cond-mat.stat-mech]A random walk on Area Restricted Search
    • [cs.AI]Learning Task-General Representations with Generative Neuro-Symbolic Modeling
    • [cs.AI]Plausible Reasoning about EL-Ontologies using Concept Interpolation
    • [cs.AI]SOAC: The Soft Option Actor-Critic Architecture
    • [cs.CL]A Simple Approach to Case-Based Reasoning in Knowledge Bases
    • [cs.CL]Analyzing Effect of Repeated Reading on Oral Fluency and Narrative Production for Computer-Assisted Language Learning
    • [cs.CL]Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes
    • [cs.CL]IIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and Selection
    • [cs.CL]Learning Source Phrase Representations for Neural Machine Translation
    • [cs.CL]Multilingual Jointly Trained Acoustic and Written Word Embeddings
    • [cs.CL]Neural Machine Translation For Paraphrase Generation
    • [cs.CL]Neural Machine Translation for Multilingual Grapheme-to-Phoneme Conversion
    • [cs.CL]Unsupervised Cross-lingual Representation Learning for Speech Recognition
    • [cs.CL]XREF: Entity Linking for Chinese News Comments with Supplementary Article Reference
    • [cs.CR]Blacklight: Defending Black-Box Adversarial Attacks on Deep Neural Networks
    • [cs.CR]Differentially Private Health Tokens for Estimating COVID-19 Risk
    • [cs.CR]Privacy at Facebook Scale
    • [cs.CV]A causal view of compositional zero-shot recognition
    • [cs.CV]An Analysis of SVD for Deep Rotation Estimation
    • [cs.CV]Backdoor Attacks on Facial Recognition in the Physical World
    • [cs.CV]DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors
    • [cs.CV]Deep Learning for Cornea Microscopy Blind Deblurring
    • [cs.CV]Diffusion-Weighted Magnetic Resonance Brain Images Generation with Generative Adversarial Networks and Variational Autoencoders: A Comparison Study
    • [cs.CV]Discontinuous and Smooth Depth Completion with Binary Anisotropic Diffusion Tensor
    • [cs.CV]Dynamically Mitigating Data Discrepancy with Balanced Focal Loss for Replay Attack Detection
    • [cs.CV]Estimating Displaced Populations from Overhead
    • [cs.CV]Extended Labeled Faces in-the-Wild (ELFW): Augmenting Classes for Face Segmentation
    • [cs.CV]Kinematic-Structure-Preserved Representation for Unsupervised 3D Human Pose Estimation
    • [cs.CV]Layout Generation and Completion with Self-attention
    • [cs.CV]Learning to simulate complex scenes
    • [cs.CV]Lifted Disjoint Paths with Application in Multiple Object Tracking
    • [cs.CV]Neural Architecture Design for GPU-Efficient Networks
    • [cs.CV]One Thousand and One Hours: Self-driving Motion Prediction Dataset
    • [cs.CV]Parametric Instance Classification for Unsupervised Visual Feature Learning
    • [cs.CV]PropagationNet: Propagate Points to Curve to Learn Structure Information
    • [cs.CV]Road obstacles positional and dynamic features extraction combining object detection, stereo disparity maps and optical flow data
    • [cs.CV]SACT: Self-Aware Multi-Space Feature Composition Transformer for Multinomial Attention for Video Captioning
    • [cs.CV]SRFlow: Learning the Super-Resolution Space with Normalizing Flow
    • [cs.CV]SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization
    • [cs.CV]Searching towards Class-Aware Generators for Conditional Generative Adversarial Networks
    • [cs.CV]Self-Segregating and Coordinated-Segregating Transformer for Focused Deep Multi-Modular Network for Visual Question Answering
    • [cs.CV]SmallBigNet: Integrating Core and Contextual Views for Video Classification
    • [cs.CV]Space-Time Correspondence as a Contrastive Random Walk
    • [cs.CV]The flag manifold as a tool for analyzing and comparing data sets
    • [cs.CV]Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks
    • [cs.CY]A Protocol to Convert Infrastructure Data from Computer-Aided Design (CAD) to Geographic Information Systems (GIS)
    • [cs.CY]Blockchain-Based Applications in Higher Education: A Systematic Mapping Study
    • [cs.CY]Case study: Mapping potential informal settlements areas in Tegucigalpa with machine learning to plan ground survey
    • [cs.CY]Confidential Computing for Privacy-Preserving Contact Tracing
    • [cs.CY]Fair navigation planning: a humanitarian robot use case
    • [cs.CY]On the Nature of Programming Exercises
    • [cs.CY]Snitches Get Stitches: On The Difficulty of Whistleblowing
    • [cs.CY]Usability, Accessibility and Web Security Assessment of E-government Websites in Tanzania
    • [cs.DB]SPIDER: Selective Plotting of Interconnected Data and Entity Relations
    • [cs.DC]Fast General Distributed Transactions with Opacity using Global Time
    • [cs.ET]Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence
    • [cs.GT]Mobility operator resource-pooling contract design to hedge against network disruptions
    • [cs.HC]Mood-based On-Car Music Recommendations
    • [cs.IT]An Error-limited NOMA-HARQ Approach using Short Packets
    • [cs.IT]Large-Scale Fading Precoding for Spatially Correlated Rician Fading with Phase Shifts
    • [cs.IT]On Integrated Access and Backhaul Networks: Current Status and Potentials
    • [cs.IT]Rank-metric codes over arbitrary Galois extensions and rank analogues of Reed-Muller codes
    • [cs.LG]A Closer Look at Invalid Action Masking in Policy Gradient Algorithms
    • [cs.LG]A New Modal Autoencoder for Functionally Independent Feature Extraction
    • [cs.LG]A Theoretical Framework for Target Propagation
    • [cs.LG]Active Online Domain Adaptation
    • [cs.LG]Anomaly Detection using Deep Reconstruction and Forecasting for Autonomous Systems
    • [cs.LG]Architopes: An Architecture Modification for Composite Pattern Learning, Increased Expressiveness, and Reduced Training Time
    • [cs.LG]Artemis: tight convergence guarantees for bidirectional compression in Federated Learning
    • [cs.LG]Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL
    • [cs.LG]AutoNCP: Automated pipelines for accurate confidence intervals
    • [cs.LG]Background Knowledge Injection for Interpretable Sequence Classification
    • [cs.LG]Between-Domain Instance Transition Via the Process of Gibbs Sampling in RBM
    • [cs.LG]Class-Similarity Based Label Smoothing for Generalized Confidence Calibration
    • [cs.LG]Combining Ensemble Kalman Filter and Reservoir Computing to predict spatio-temporal chaotic systems from imperfect observations and models
    • [cs.LG]Compositional Explanations of Neurons
    • [cs.LG]Data-dependent Pruning to find the Winning Lottery Ticket
    • [cs.LG]Does Adversarial Transferability Indicate Knowledge Transferability?
    • [cs.LG]Empirical Analysis of Overfitting and Mode Drop in GAN Training
    • [cs.LG]Ensembles of Generative Adversarial Networks for Disconnected Data
    • [cs.LG]Ensuring Learning Guarantees on Concept Drift Detection with Statistical Learning Theory
    • [cs.LG]Epoch-evolving Gaussian Process Guided Learning
    • [cs.LG]Extracting the main trend in a dataset: the Sequencer algorithm
    • [cs.LG]Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
    • [cs.LG]Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
    • [cs.LG]Geometric Prediction: Moving Beyond Scalars
    • [cs.LG]Global Convergence and Induced Kernels of Gradient-Based Meta-Learning with Neural Nets
    • [cs.LG]Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems
    • [cs.LG]Graph Structural-topic Neural Network
    • [cs.LG]Green Machine Learning via Augmented Gaussian Processes and Multi-Information Source Optimization
    • [cs.LG]High-Dimensional Quadratic Discriminant Analysis under Spiked Covariance Model
    • [cs.LG]Implicitly Maximizing Margins with the Hinge Loss
    • [cs.LG]Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift
    • [cs.LG]Maximum Multiscale Entropy and Neural Network Regularization
    • [cs.LG]Minimum Cost Active Labeling
    • [cs.LG]Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping
    • [cs.LG]Newton-type Methods for Minimax Optimization
    • [cs.LG]Noise, overestimation and exploration in Deep Reinforcement Learning
    • [cs.LG]On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools
    • [cs.LG]On Mitigating Random and Adversarial Bit Errors
    • [cs.LG]Pareto Active Learning with Gaussian Processes and Adaptive Discretization
    • [cs.LG]Practical applications of metric space magnitude and weighting vectors
    • [cs.LG]Prior-guided Bayesian Optimization
    • [cs.LG]Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression
    • [cs.LG]Recurrent Quantum Neural Networks
    • [cs.LG]Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
    • [cs.LG]Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces
    • [cs.LG]Scalable Spectral Clustering with Nystrom Approximation: Practical and Theoretical Aspects
    • [cs.LG]SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
    • [cs.LG]Sequence-to-sequence models for workload interference
    • [cs.LG]Smooth Adversarial Training
    • [cs.LG]Sparse Convex Optimization via Adaptively Regularized Hard Thresholding
    • [cs.LG]Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent
    • [cs.LG]Stochastic Subset Selection
    • [cs.LG]Subpopulation Data Poisoning Attacks
    • [cs.LG]Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms
    • [cs.LG]Tangles: From Weak to Strong Clustering
    • [cs.LG]Target Consistency for Domain Adaptation: when Robustness meets Transferability
    • [cs.LG]The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification
    • [cs.LG]The Effect of Optimization Methods on the Robustness of Out-of-Distribution Detection Approaches
    • [cs.LG]The Max-Cut Decision Tree: Improving on the Accuracy and Running Time of Decision Trees
    • [cs.LG]The Quenching-Activation Behavior of the Gradient Descent Dynamics for Two-layer Neural Network Models
    • [cs.LG]The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks
    • [cs.LG]Time-varying Graph Representation Learning via Higher-Order Skip-Gram with Negative Sampling
    • [cs.LG]Topological Insights in Sparse Neural Networks
    • [cs.LG]Towards Differentially Private Text Representations
    • [cs.LG]Uncertainty in Neural Relational Inference Trajectory Reconstruction
    • [cs.LG]When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
    • [cs.MM]Fine granularity access in interactive compression of 360-degree images based on rate adaptive channel codes
    • [cs.NE]Empirical Study on the Benefits of Multiobjectivization for Solving Single-Objective Problems
    • [cs.NE]Fast and stable MAP-Elites in noisy domains using deep grids
    • [cs.NE]Inference with Artificial Neural Networks on Analog Neuromorphic Hardware
    • [cs.NE]Learning compositional functions via multiplicative weight updates
    • [cs.NI]Design And Develop Network Storage Virtualization By Using GNS3
    • [cs.NI]Perigee: Efficient Peer-to-Peer Network Design for Blockchains
    • [cs.RO]Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences
    • [cs.RO]Mobile Robot Path Planning in Dynamic Environments: A Survey
    • [cs.RO]Optimal Trajectory Planning for Flexible Robots with Large Deformation
    • [cs.RO]Robust Relative Hand Placement For Bi-Manual Tasks
    • [cs.RO]Three-Dimensional Dynamic Modeling and Motion Analysis for an Active-Tail-Actuated Robotic Fish with Barycentre Regulating Mechanism
    • [cs.SI]A metric on directed graphs and Markov chains based on hitting probabilities
    • [cs.SI]Controversial information spreads faster and further in Reddit
    • [cs.SI]Identify Influential Nodes in Online Social Network for Brand Communication
    • [cs.SI]Mobile smartphone tracing can detect almost all SARS-CoV-2 infections
    • [cs.SI]TweetsCOV19 — A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic
    • [econ.EM]A Model of the Fed’s View on Inflation
    • [econ.EM]Cointegration in large VARs
    • [econ.EM]Inference without smoothing for large panels with cross-sectional and temporal dependence
    • [eess.AS]Gamma Boltzmann Machine for Simultaneously Modeling Linear- and Log-amplitude Spectra
    • [eess.IV]Block-matching in FPGA
    • [eess.IV]Collaborative Boundary-aware Context Encoding Networks for Error Map Prediction
    • [eess.IV]Deep Residual 3D U-Net for Joint Segmentation and Texture Classification of Nodules in Lung
    • [eess.IV]Multimarginal Wasserstein Barycenter for Stain Normalization and Augmentation
    • [eess.IV]Perfusion Quantification from Endoscopic Videos: Learning to Read Tumor Signatures
    • [eess.IV]Training Variational Networks with Multi-Domain Simulations: Speed-of-Sound Image Reconstruction
    • [eess.SP]Artificial Lateral Line Based Relative State Estimation for Two Adjacent Robotic Fish
    • [eess.SP]Composition Modulation
    • [eess.SP]Neural Networks Based Beam Codebooks: Learning mmWave Massive MIMO Beams that Adapt to Deployment and Hardware
    • [math.DS]Inferring Causal Networks of Dynamical Systems through Transient Dynamics and Perturbation
    • [math.OC]Dual-Free Stochastic Decentralized Optimization with Variance Reduction
    • [math.OC]Heat kernel and intrinsic Gaussian processes on manifolds
    • [math.OC]Multi-marginal optimal transport and probabilistic graphical models
    • [math.OC]Riccati-based feedback stabilization for unstable Power system models
    • [math.ST]An $\ellp$ theory of PCA and spectral clustering
    • [math.ST]Deconvolution with unknown noise distribution is possible for multivariate signals
    • [math.ST]Estimation and Comparison of Correlation-based Measures of Concordance
    • [math.ST]On the relationship between beta-Bartlett and Uhlig extended processes
    • [math.ST]Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets
    • [physics.soc-ph]Estimating Road Network Accessibility during a Hurricane Evacuation: A Case Study of Hurricane Irma in Florida
    • [physics.soc-ph]Estimating a Large Drive Time Matrix between Zip Codes in the United States: A Differential Sampling Approach
    • [physics.soc-ph]Intervention scenarios to enhance knowledge transfer in a network of firm
    • [physics.soc-ph]Statistical inference of assortative community structures
    • [physics.soc-ph]Topology dependent payoffs can lead to escape from prisoner’s dilemma
    • [q-bio.NC]Habit learning supported by efficiently controlled network dynamics in naive macaque monkeys
    • [q-bio.NC]Predictive coding in balanced neural networks with noise, chaos and delays
    • [quant-ph]Un-Weyl-ing the Clifford Hierarchy
    • [stat.AP]A Clinical Trial Derived Reference Set for Evaluating Observational Study Methods
    • [stat.AP]Categorical Exploratory Data Analysis: From Multiclass Classification and Response Manifold Analytics perspectives of baseball pitching dynamics
    • [stat.AP]Data-driven Analytics of COVID-2019 for Epidemic Prediction, Clinical Diagnosis, Policy Effectiveness and Contact Tracing: A Survey
    • [stat.AP]Identifying group contributions in NBA lineups with spectral analysis
    • [stat.AP]Retiree mortality forecasting: A partial age-range or a full age-range model?
    • [stat.AP]The Hot Hand in Actual Game Situations
    • [stat.CO]Stratified stochastic variational inference for high-dimensional network factor model
    • [stat.ME]Break Point Detection for Functional Covariance
    • [stat.ME]Discussion of ‘Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection’
    • [stat.ME]Inferring median survival differences in general factorial designs via permutation tests
    • [stat.ME]Robust and Efficient Approximate Bayesian Computation: A Minimum Distance Approach
    • [stat.ME]Spatio-temporal Inversion using the Selection Kalman Model
    • [stat.ML]Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation
    • [stat.ML]BoXHED: Boosted eXact Hazard Estimator with Dynamic covariates
    • [stat.ML]Consistency of Anchor-based Spectral Clustering
    • [stat.ML]Inverse Active Sensing: Modeling and Understanding Timely Decision-Making
    • [stat.ML]Labeled Optimal Partitioning
    • [stat.ML]Machine learning the real discriminant locus
    • [stat.ML]Neural Decomposition: Functional ANOVA with Variational Autoencoders
    • [stat.ML]Predicting First Passage Percolation Shapes Using Neural Networks
    • [stat.ML]Q-NET: A Formula for Numerical Integration of a Shallow Feed-forward Neural Network
    • [stat.ML]STORM: Foundations of End-to-End Em
    805
    pirical Risk Minimization on the Edge
    • [stat.ML]Slice Sampling for General Completely Random Measures
    • [stat.ML]Spatio-temporal Sequence Prediction with Point Processes and Self-organizing Decision Trees
    • [stat.ML]Strictly Batch Imitation Learning by Energy-based Distribution Matching
    • [stat.ML]Taming GANs with Lookahead
    • [stat.ML]Tensor Programs II: Neural Tangent Kernel for Any Architecture
    ·····································
    • [cond-mat.stat-mech]A random walk on Area Restricted Search
    _Simone Santini
    http://arxiv.org/abs/2006.14318v1
    • [cs.AI]Learning Task-General Representations with Generative Neuro-Symbolic Modeling
    Reuben Feinman, Brenden M. Lake
    http://arxiv.org/abs/2006.14448v1
    • [cs.AI]Plausible Reasoning about EL-Ontologies using Concept Interpolation
    Yazmín Ibáñez-García, Víctor Gutiérrez-Basulto, Steven Schockaert
    http://arxiv.org/abs/2006.14437v1
    • [cs.AI]SOAC: The Soft Option Actor-Critic Architecture
    Chenghao Li, Xiaoteng Ma, Chongjie Zhang, Jun Yang, Li Xia, Qianchuan Zhao
    http://arxiv.org/abs/2006.14363v1
    • [cs.CL]A Simple Approach to Case-Based Reasoning in Knowledge Bases
    Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum
    http://arxiv.org/abs/2006.14198v1
    • [cs.CL]Analyzing Effect of Repeated Reading on Oral Fluency and Narrative Production for Computer-Assisted Language Learning
    Santosh Kumar Barnwal, Uma Shanker Tiwary
    http://arxiv.org/abs/2006.14320v1
    • [cs.CL]Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes
    Marina Sedinkina, Nikolas Breitkopf, Hinrich Schütze
    http://arxiv.org/abs/2006.14209v1
    • [cs.CL]IIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and Selection
    Vivek Srivastava, Mayank Singh
    http://arxiv.org/abs/2006.14465v1
    • [cs.CL]Learning Source Phrase Representations for Neural Machine Translation
    Hongfei Xu, Josef van Genabith, Deyi Xiong, Qiuhui Liu, Jingyi Zhang
    http://arxiv.org/abs/2006.14405v1
    • [cs.CL]Multilingual Jointly Trained Acoustic and Written Word Embeddings
    Yushi Hu, Shane Settle, Karen Livescu
    http://arxiv.org/abs/2006.14007v1
    • [cs.CL]Neural Machine Translation For Paraphrase Generation
    Alex Sokolov, Denis Filimonov
    http://arxiv.org/abs/2006.14223v1
    • [cs.CL]Neural Machine Translation for Multilingual Grapheme-to-Phoneme Conversion
    Alex Sokolov, Tracy Rohlin, Ariya Rastrow
    http://arxiv.org/abs/2006.14194v1
    • [cs.CL]Unsupervised Cross-lingual Representation Learning for Speech Recognition
    Alexis Conneau, Alexei Baevski, Ronan Collobert, Abdelrahman Mohamed, Michael Auli
    http://arxiv.org/abs/2006.13979v1
    • [cs.CL]XREF: Entity Linking for Chinese News Comments with Supplementary Article Reference
    Xinyu Hua, Lei Li, Lifeng Hua, Lu Wang
    http://arxiv.org/abs/2006.14017v1
    • [cs.CR]Blacklight: Defending Black-Box Adversarial Attacks on Deep Neural Networks
    Huiying Li, Shawn Shan, Emily Wenger, Jiayun Zhang, Haitao Zheng, Ben Y. Zhao
    http://arxiv.org/abs/2006.14042v1
    • [cs.CR]Differentially Private Health Tokens for Estimating COVID-19 Risk
    David Butler, Chris Hicks, James Bell, Carsten Maple, Jon Crowcroft
    http://arxiv.org/abs/2006.14329v1
    • [cs.CR]Privacy at Facebook Scale
    Paulo Tanaka, Sameet Sapra, Nikolay Laptev
    http://arxiv.org/abs/2006.14109v1
    • [cs.CV]A causal view of compositional zero-shot recognition
    Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik
    http://arxiv.org/abs/2006.14610v1
    • [cs.CV]An Analysis of SVD for Deep Rotation Estimation
    Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia
    http://arxiv.org/abs/2006.14616v1
    • [cs.CV]Backdoor Attacks on Facial Recognition in the Physical World
    Emily Wenger, Josephine Passananti, Yuanshun Yao, Haitao Zheng, Ben Y. Zhao
    http://arxiv.org/abs/2006.14580v1
    • [cs.CV]DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors
    Wenbin Gao, Lei Zhang, Qi Teng, Hao Wu, Fuhong Min, Jun He
    http://arxiv.org/abs/2006.14435v1
    • [cs.CV]Deep Learning for Cornea Microscopy Blind Deblurring
    Toussain Cardot, Pilar Marxer, Ivan Snozzi
    http://arxiv.org/abs/2006.14319v1
    • [cs.CV]Diffusion-Weighted Magnetic Resonance Brain Images Generation with Generative Adversarial Networks and Variational Autoencoders: A Comparison Study
    Alejandro Ungría Hirte, Moritz Platscher, Thomas Joyce, Jeremy J. Heit, Eric Tranvinh, Christian Federau
    http://arxiv.org/abs/2006.13944v1
    • [cs.CV]Discontinuous and Smooth Depth Completion with Binary Anisotropic Diffusion Tensor
    Yasuhiro Yao, Menandro Roxas, Ryoichi Ishikawa, Shingo Ando, Jun Shimamura, Takeshi Oishi
    http://arxiv.org/abs/2006.14374v1
    • [cs.CV]Dynamically Mitigating Data Discrepancy with Balanced Focal Loss for Replay Attack Detection
    Yongqiang Dou, Haocheng Yang, Maolin Yang, Yanyan Xu, Dengfeng Ke
    http://arxiv.org/abs/2006.14563v1
    • [cs.CV]Estimating Displaced Populations from Overhead
    Armin Hadzic, Gordon Christie, Jeffrey Freeman, Amber Dismer, Stevan Bullard, Ashley Greiner, Nathan Jacobs, Ryan Mukherjee
    http://arxiv.org/abs/2006.14547v1
    • [cs.CV]Extended Labeled Faces in-the-Wild (ELFW): Augmenting Classes for Face Segmentation
    Rafael Redondo, Jaume Gibert
    http://arxiv.org/abs/2006.13980v1
    • [cs.CV]Kinematic-Structure-Preserved Representation for Unsupervised 3D Human Pose Estimation
    Jogendra Nath Kundu, Siddharth Seth, Rahul M V, Mugalodi Rakesh, R. Venkatesh Babu, Anirban Chakraborty
    http://arxiv.org/abs/2006.14107v1
    • [cs.CV]Layout Generation and Completion with Self-attention
    Kamal Gupta, Alessandro Achille, Justin Lazarow, Larry Davis, Vijay Mahadevan, Abhinav Shrivastava
    http://arxiv.org/abs/2006.14615v1
    • [cs.CV]Learning to simulate complex scenes
    Zhenfeng Xue, Weijie Mao, Liang Zheng
    http://arxiv.org/abs/2006.14611v1
    • [cs.CV]Lifted Disjoint Paths with Application in Multiple Object Tracking
    Andrea Hornakova, Roberto Henschel, Bodo Rosenhahn, Paul Swoboda
    http://arxiv.org/abs/2006.14550v1
    • [cs.CV]Neural Architecture Design for GPU-Efficient Networks
    Ming Lin, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin
    http://arxiv.org/abs/2006.14090v1
    • [cs.CV]One Thousand and One Hours: Self-driving Motion Prediction Dataset
    John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska
    http://arxiv.org/abs/2006.14480v1
    • [cs.CV]Parametric Instance Classification for Unsupervised Visual Feature Learning
    Yue Cao, Zhenda Xie, Bin Liu, Yutong Lin, Zheng Zhang, Han Hu
    http://arxiv.org/abs/2006.14618v1
    • [cs.CV]PropagationNet: Propagate Points to Curve to Learn Structure Information
    Xiehe Huang, Weihong Deng, Haifeng Shen, Xiubao Zhang, Jieping Ye
    http://arxiv.org/abs/2006.14308v1
    • [cs.CV]Road obstacles positional and dynamic features extraction combining object detection, stereo disparity maps and optical flow data
    Thiago Rateke, Aldo von Wangenheim
    http://arxiv.org/abs/2006.14011v1
    • [cs.CV]SACT: Self-Aware Multi-Space Feature Composition Transformer for Multinomial Attention for Video Captioning
    Chiranjib Sur
    http://arxiv.org/abs/2006.14262v1
    • [cs.CV]SRFlow: Learning the Super-Resolution Space with Normalizing Flow
    Andreas Lugmayr, Martin Danelljan, Luc Van Gool, Radu Timofte
    http://arxiv.org/abs/2006.14200v1
    • [cs.CV]SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization
    Rakshit Naidu, Joy Michael
    http://arxiv.org/abs/2006.14255v1
    • [cs.CV]Searching towards Class-Aware Generators for Conditional Generative Adversarial Networks
    Peng Zhou, Lingxi Xie, Xiaopeng Zhang, Bingbing Ni, Qi Tian
    http://arxiv.org/abs/2006.14208v1
    • [cs.CV]Self-Segregating and Coordinated-Segregating Transformer for Focused Deep Multi-Modular Network for Visual Question Answering
    Chiranjib Sur
    http://arxiv.org/abs/2006.14264v1
    • [cs.CV]SmallBigNet: Integrating Core and Contextual Views for Video Classification
    Xianhang Li, Yali Wang, Zhipeng Zhou, Yu Qiao
    http://arxiv.org/abs/2006.14582v1
    • [cs.CV]Space-Time Correspondence as a Contrastive Random Walk
    Allan Jabri, Andrew Owens, Alexei A. Efros
    http://arxiv.org/abs/2006.14613v1
    • [cs.CV]The flag manifold as a tool for analyzing and comparing data sets
    Xiaofeng Ma, Michael Kirby, Chris Peterson
    http://arxiv.org/abs/2006.14086v1
    • [cs.CV]Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks
    Vikash Sehwag, Rajvardhan Oak, Mung Chiang, Prateek Mittal
    http://arxiv.org/abs/2006.14077v1
    • [cs.CY]A Protocol to Convert Infrastructure Data from Computer-Aided Design (CAD) to Geographic Information Systems (GIS)
    Eric Sergio Boria, Mohamed Badhrudeen, Guillemette Fonteix, Sybil Derrible, Michael Siciliano
    http://arxiv.org/abs/2006.14112v1
    • [cs.CY]Blockchain-Based Applications in Higher Education: A Systematic Mapping Study
    B. Awaji, E. Solaiman, A. Albshri
    http://arxiv.org/abs/2006.14528v1
    • [cs.CY]Case study: Mapping potential informal settlements areas in Tegucigalpa with machine learning to plan ground survey
    Federico Bayle, Damian E. Silvani
    http://arxiv.org/abs/2006.14490v1
    • [cs.CY]Confidential Computing for Privacy-Preserving Contact Tracing
    David Sturzenegger, Aetienne Sardon, Stefan Deml, Thomas Hardjono
    http://arxiv.org/abs/2006.14235v1
    • [cs.CY]Fair navigation planning: a humanitarian robot use case
    Martim Brandao
    http://arxiv.org/abs/2006.14479v1
    • [cs.CY]On the Nature of Programming Exercises
    Alberto Simões, Ricardo Queirós
    http://arxiv.org/abs/2006.14476v1
    • [cs.CY]Snitches Get Stitches: On The Difficulty of Whistleblowing
    Mansoor Ahmed-Rengers, Ross Anderson, Darija Halatova, Ilia Shumailov
    http://arxiv.org/abs/2006.14407v1
    • [cs.CY]Usability, Accessibility and Web Security Assessment of E-government Websites in Tanzania
    Noe Elisa
    http://arxiv.org/abs/2006.14245v1
    • [cs.DB]SPIDER: Selective Plotting of Interconnected Data and Entity Relations
    Pranav Addepalli, Eric Wu, Douglas Bossart, Christina Lin, Allistar Smith
    http://arxiv.org/abs/2006.14416v1
    • [cs.DC]Fast General Distributed Transactions with Opacity using Global Time
    Alex Shamis, Matthew Renzelmann, Stanko Novakovic, Georgios Chatzopoulos, Anders T. Gjerdrum, Dan Alistarh, Aleksandar Dragojevic, Dushyanth Narayanan, Miguel Castro
    http://arxiv.org/abs/2006.14346v1
    • [cs.ET]Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence
    Arianna Rubino, Can Livanelioglu, Ning Qiao, Melika Payvand, Giacomo Indiveri
    http://arxiv.org/abs/2006.14270v1
    • [cs.GT]Mobility operator resource-pooling contract design to hedge against network disruptions
    Theodoros P. Pantelidis, Joseph Y. J. Chow, Oded Cats
    http://arxiv.org/abs/2006.14518v1
    • [cs.HC]Mood-based On-Car Music Recommendations
    Erion Çano, Riccardo Coppola, Eleonora Gargiulo, Marco Marengo, Maurizio Morisio
    http://arxiv.org/abs/2006.14279v1
    • [cs.IT]An Error-limited NOMA-HARQ Approach using Short Packets
    Behrooz Makki, Tommy Svensson, Michele Zorzi
    http://arxiv.org/abs/2006.14315v1
    • [cs.IT]Large-Scale Fading Precoding for Spatially Correlated Rician Fading with Phase Shifts
    Özlem Tuğfe Demir, Emil Björnson
    http://arxiv.org/abs/2006.14267v1
    • [cs.IT]On Integrated Access and Backhaul Networks: Current Status and Potentials
    Charitha Madapatha, Behrooz Makki, Chao Fang, Oumer Teyeb, Erik Dahlman, Mohamed-Slim Alouini, Tommy Svensson
    http://arxiv.org/abs/2006.14216v1
    • [cs.IT]Rank-metric codes over arbitrary Galois extensions and rank analogues of Reed-Muller codes
    Daniel Augot, Alain Couvreur, Julien Lavauzelle, Alessandro Neri
    http://arxiv.org/abs/2006.14489v1
    • [cs.LG]A Closer Look at Invalid Action Masking in Policy Gradient Algorithms
    Shengyi Huang, Santiago Ontañón
    http://arxiv.org/abs/2006.14171v1
    • [cs.LG]A New Modal Autoencoder for Functionally Independent Feature Extraction
    Yuzhu Guo, Kang Pan, Simeng Li, Zongchang Han, Kexin Wang, Li Li
    http://arxiv.org/abs/2006.14390v1
    • [cs.LG]A Theoretical Framework for Target Propagation
    Alexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens, João Sacramento, Benjamin F. Grewe
    http://arxiv.org/abs/2006.14331v1
    • [cs.LG]Active Online Domain Adaptation
    Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang
    http://arxiv.org/abs/2006.14481v1
    • [cs.LG]Anomaly Detection using Deep Reconstruction and Forecasting for Autonomous Systems
    Nadarasar Bahavan, Navaratnarajah Suman, Sulhi Cader, Ruwinda Ranganayake, Damitha Seneviratne, Vinu Maddumage, Gershom Seneviratne, Yasinha Supun, Isuru Wijesiri, Suchitha Dehigaspitiya, Dumindu Tissera, Chamira Edussooriya
    http://arxiv.org/abs/2006.14556v1
    • [cs.LG]Architopes: An Architecture Modification for Composite Pattern Learning, Increased Expressiveness, and Reduced Training Time
    Anastasis Kratsios, Behnoosh Zamanlooy
    http://arxiv.org/abs/2006.14378v1
    • [cs.LG]Artemis: tight convergence guarantees for bidirectional compression in Federated Learning
    Constantin Philippenko, Aymeric Dieuleveut
    http://arxiv.org/abs/2006.14591v1
    • [cs.LG]Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL
    Lucas Zimmer, Marius Lindauer, Frank Hutter
    http://arxiv.org/abs/2
    abs/2006.13799v1
    abs/2006.13799v1)
    • [cs.LG]AutoNCP: Automated pipelines for accurate confidence intervals
    Yao Zhang, William Zame, Mihaela van der Schaar
    http://arxiv.org/abs/2006.14099v1
    • [cs.LG]Background Knowledge Injection for Interpretable Sequence Classification
    Severin Gsponer, Luca Costabello, Chan Le Van, Sumit Pai, Christophe Gueret, Georgiana Ifrim, Freddy Lecue
    http://arxiv.org/abs/2006.14248v1
    • [cs.LG]Between-Domain Instance Transition Via the Process of Gibbs Sampling in RBM
    Hossein Shahabadi Farahani, Alireza Fatehi, Mahdi Aliyari Shoorehdeli
    http://arxiv.org/abs/2006.14538v1
    • [cs.LG]Class-Similarity Based Label Smoothing for Generalized Confidence Calibration
    Chihuang Liu, Joseph JaJa
    http://arxiv.org/abs/2006.14028v1
    • [cs.LG]Combining Ensemble Kalman Filter and Reservoir Computing to predict spatio-temporal chaotic systems from imperfect observations and models
    Futo Tomizawa, Yohei Sawada
    http://arxiv.org/abs/2006.14276v1
    • [cs.LG]Compositional Explanations of Neurons
    Jesse Mu, Jacob Andreas
    http://arxiv.org/abs/2006.14032v1
    • [cs.LG]Data-dependent Pruning to find the Winning Lottery Ticket
    Dániel Lévai, Zsolt Zombori
    http://arxiv.org/abs/2006.14350v1
    • [cs.LG]Does Adversarial Transferability Indicate Knowledge Transferability?
    Kaizhao Liang, Jacky Y. Zhang, Oluwasanmi Koyejo, Bo Li
    http://arxiv.org/abs/2006.14512v1
    • [cs.LG]Empirical Analysis of Overfitting and Mode Drop in GAN Training
    Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Vijay Chandrasekhar
    http://arxiv.org/abs/2006.14265v1
    • [cs.LG]Ensembles of Generative Adversarial Networks for Disconnected Data
    Lorenzo Luzi, Randall Balestriero, Richard G. Baraniuk
    http://arxiv.org/abs/2006.14600v1
    • [cs.LG]Ensuring Learning Guarantees on Concept Drift Detection with Statistical Learning Theory
    Lucas Pagliosa, Rodrigo Mello
    http://arxiv.org/abs/2006.14079v1
    • [cs.LG]Epoch-evolving Gaussian Process Guided Learning
    Jiabao Cui, Xuewei Li, Bin Li, Hanbin Zhao, Bourahla Omar, Xi Li
    http://arxiv.org/abs/2006.14347v1
    • [cs.LG]Extracting the main trend in a dataset: the Sequencer algorithm
    Dalya Baron, Brice Ménard
    http://arxiv.org/abs/2006.13948v1
    • [cs.LG]Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
    Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
    http://arxiv.org/abs/2006.14117v1
    • [cs.LG]Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
    Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
    http://arxiv.org/abs/2006.14284v1
    • [cs.LG]Geometric Prediction: Moving Beyond Scalars
    Raphael J. L. Townshend, Brent Townshend, Stephan Eismann, Ron O. Dror
    http://arxiv.org/abs/2006.14163v1
    • [cs.LG]Global Convergence and Induced Kernels of Gradient-Based Meta-Learning with Neural Nets
    Haoxiang Wang, Ruoyu Sun, Bo Li
    http://arxiv.org/abs/2006.14606v1
    • [cs.LG]Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems
    Bhaskar Mukhoty, Govind Gopakumar, Prateek Jain, Purushottam Kar
    http://arxiv.org/abs/2006.14211v1
    • [cs.LG]Graph Structural-topic Neural Network
    Qingqing Long, Yilun Jin, Guojie Song, Yi Li, Wei Lin
    http://arxiv.org/abs/2006.14278v1
    • [cs.LG]Green Machine Learning via Augmented Gaussian Processes and Multi-Information Source Optimization
    Antonio Candelieri, Riccardo Perego, Francesco Archetti
    http://arxiv.org/abs/2006.14233v1
    • [cs.LG]High-Dimensional Quadratic Discriminant Analysis under Spiked Covariance Model
    Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini
    http://arxiv.org/abs/2006.14325v1
    • [cs.LG]Implicitly Maximizing Margins with the Hinge Loss
    Justin Lizama
    http://arxiv.org/abs/2006.14286v1
    • [cs.LG]Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift
    Lukas Galke, Iacopo Vagliano, Ansgar Scherp
    http://arxiv.org/abs/2006.14422v1
    • [cs.LG]Maximum Multiscale Entropy and Neural Network Regularization
    Amir R. Asadi, Emmanuel Abbe
    http://arxiv.org/abs/2006.14614v1
    • [cs.LG]Minimum Cost Active Labeling
    Hang Qiu, Krishna Chintalapudi, Ramesh Govindan
    http://arxiv.org/abs/2006.13999v1
    • [cs.LG]Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping
    Shashanka Ubaru, Sanjeeb Dash, Arya Mazumdar, Oktay Gunluk
    http://arxiv.org/abs/2006.14084v1
    • [cs.LG]Newton-type Methods for Minimax Optimization
    Guojun Zhang, Kaiwen Wu, Pascal Poupart, Yaoliang Yu
    http://arxiv.org/abs/2006.14592v1
    • [cs.LG]Noise, overestimation and exploration in Deep Reinforcement Learning
    Rafael Stekolshchik
    http://arxiv.org/abs/2006.14167v1
    • [cs.LG]On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools
    Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman, Guillaume Lajoie
    http://arxiv.org/abs/2006.14123v1
    • [cs.LG]On Mitigating Random and Adversarial Bit Errors
    David Stutz, Nandhini Chandramoorthy, Matthias Hein, Bernt Schiele
    http://arxiv.org/abs/2006.13977v1
    • [cs.LG]Pareto Active Learning with Gaussian Processes and Adaptive Discretization
    Andi Nika, Kerem Bozgan, Çağın Ararat, Cem Tekin
    http://arxiv.org/abs/2006.14061v1
    • [cs.LG]Practical applications of metric space magnitude and weighting vectors
    Eric Bunch, Daniel Dickinson, Jeffry Kline, Glenn Fung
    http://arxiv.org/abs/2006.14063v1
    • [cs.LG]Prior-guided Bayesian Optimization
    Artur Souza, Luigi Nardi, Leonardo B. Oliveira, Kunle Olukotun, Marius Lindauer, Frank Hutter
    http://arxiv.org/abs/2006.14608v1
    • [cs.LG]Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression
    Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Joseph Salmon
    http://arxiv.org/abs/2006.13533v2
    • [cs.LG]Recurrent Quantum Neural Networks
    Johannes Bausch
    http://arxiv.org/abs/2006.14619v1
    • [cs.LG]Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
    Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
    http://arxiv.org/abs/2006.14389v1
    • [cs.LG]Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces
    Dongge Han, Shruti Tople, Alex Rogers, Michael Wooldridge, Olga Ohrimenko, Sebastian Tschiatschek
    http://arxiv.org/abs/2006.14583v1
    • [cs.LG]Scalable Spectral Clustering with Nystrom Approximation: Practical and Theoretical Aspects
    Farhad Pourkamali-Anaraki
    http://arxiv.org/abs/2006.14470v1
    • [cs.LG]SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
    Mikhail Yurochkin, Yuekai Sun
    http://arxiv.org/abs/2006.14168v1
    • [cs.LG]Sequence-to-sequence models for workload interference
    David Buchaca Prats, Joan Marcual, Josep Lluís Berral, David Carrera
    http://arxiv.org/abs/2006.14429v1
    • [cs.LG]Smooth Adversarial Training
    Cihang Xie, Mingxing Tan, Boqing Gong, Alan Yuille, Quoc V. Le
    http://arxiv.org/abs/2006.14536v1
    • [cs.LG]Sparse Convex Optimization via Adaptively Regularized Hard Thresholding
    Kyriakos Axiotis, Maxim Sviridenko
    http://arxiv.org/abs/2006.14571v1
    • [cs.LG]Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent
    Lauren Watson, Benedek Rozemberczki, Rik Sarkar
    http://arxiv.org/abs/2006.14360v1
    • [cs.LG]Stochastic Subset Selection
    Tuan A. Nguyen, Bruno Andreis, Juho Lee, Eunho Yang, Sung Ju Hwang
    http://arxiv.org/abs/2006.14222v1
    • [cs.LG]Subpopulation Data Poisoning Attacks
    Matthew Jagielski, Giorgio Severi, Niklas Pousette Harger, Alina Oprea
    http://arxiv.org/abs/2006.14026v1
    • [cs.LG]Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms
    Attila Lovas, Iosif Lytras, Miklós Rásonyi, Sotirios Sabanis
    http://arxiv.org/abs/2006.14514v1
    • [cs.LG]Tangles: From Weak to Strong Clustering
    Christian Elbracht, Diego Fioravanti, Solveig Klepper, Jakob Kneip, Luca Rendsburg, Maximilian Teegen, Ulrike von Luxburg
    http://arxiv.org/abs/2006.14444v1
    • [cs.LG]Target Consistency for Domain Adaptation: when Robustness meets Transferability
    Yassine Ouali, Victor Bouvier, Myriam Tami, Céline Hudelot
    http://arxiv.org/abs/2006.14263v1
    • [cs.LG]The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification
    Christian Tjandraatmadja, Ross Anderson, Joey Huchette, Will Ma, Krunal Patel, Juan Pablo Vielma
    http://arxiv.org/abs/2006.14076v1
    • [cs.LG]The Effect of Optimization Methods on the Robustness of Out-of-Distribution Detection Approaches
    Vahdat Abdelzad, Krzysztof Czarnecki, Rick Salay
    http://arxiv.org/abs/2006.14584v1
    • [cs.LG]The Max-Cut Decision Tree: Improving on the Accuracy and Running Time of Decision Trees
    Jonathan Bodine, Dorit S. Hochbaum
    http://arxiv.org/abs/2006.14118v1
    • [cs.LG]The Quenching-Activation Behavior of the Gradient Descent Dynamics for Two-layer Neural Network Models
    Chao Ma, Lei Wu, Weinan E
    http://arxiv.org/abs/2006.14450v1
    • [cs.LG]The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks
    Wei Hu, Lechao Xiao, Ben Adlam, Jeffrey Pennington
    http://arxiv.org/abs/2006.14599v1
    • [cs.LG]Time-varying Graph Representation Learning via Higher-Order Skip-Gram with Negative Sampling
    Simone Piaggesi, André Panisson
    http://arxiv.org/abs/2006.14330v1
    • [cs.LG]Topological Insights in Sparse Neural Networks
    Shiwei Liu, Tim Van der Lee, Anil Yaman, Zahra Atashgahi, Davide Ferraro, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu
    http://arxiv.org/abs/2006.14085v1
    • [cs.LG]Towards Differentially Private Text Representations
    Lingjuan Lyu, Yitong Li, Xuanli He, Tong Xiao
    http://arxiv.org/abs/2006.14170v1
    • [cs.LG]Uncertainty in Neural Relational Inference Trajectory Reconstruction
    Vasileios Karavias, Ben Day, Pietro Liò
    http://arxiv.org/abs/2006.13666v2
    • [cs.LG]When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
    Ziwei Guan, Tengyu Xu, Yingbin Liang
    http://arxiv.org/abs/2006.13506v2
    • [cs.MM]Fine granularity access in interactive compression of 360-degree images based on rate adaptive channel codes
    Navid Mahmoudian Bidgoli, Thomas Maugey, Aline Roumy
    http://arxiv.org/abs/2006.14239v1
    • [cs.NE]Empirical Study on the Benefits of Multiobjectivization for Solving Single-Objective Problems
    Vera Steinhoff, Pascal Kerschke, Christian Grimme
    http://arxiv.org/abs/2006.14423v1
    • [cs.NE]Fast and stable MAP-Elites in noisy domains using deep grids
    Manon Flageat, Antoine Cully
    http://arxiv.org/abs/2006.14253v1
    • [cs.NE]Inference with Artificial Neural Networks on Analog Neuromorphic Hardware
    Johannes Weis, Philipp Spilger, Sebastian Billaudelle, Yannik Stradmann, Arne Emmel, Eric Müller, Oliver Breitwieser, Andreas Grübl, Joscha Ilmberger, Vitali Karasenko, Mitja Kleider, Christian Mauch, Korbinian Schreiber, Johannes Schemmel
    http://arxiv.org/abs/2006.13177v2
    • [cs.NE]Learning compositional functions via multiplicative weight updates
    Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue
    http://arxiv.org/abs/2006.14560v1
    • [cs.NI]Design And Develop Network Storage Virtualization By Using GNS3
    Abdul Ahad Abro, Ufaque Shaikh
    http://arxiv.org/abs/2006.14074v1
    • [cs.NI]Perigee: Efficient Peer-to-Peer Network Design for Blockchains
    Yifan Mao, Soubhik Deb, Shaileshh Bojja Venkatakrishnan, Sreeram Kannan, Kannan Srinivasan
    http://arxiv.org/abs/2006.14186v1
    • [cs.RO]Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences
    Erdem Bıyık, Dylan P. Losey, Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh
    http://arxiv.org/abs/2006.14091v1
    • [cs.RO]Mobile Robot Path Planning in Dynamic Environments: A Survey
    Kuanqi Cai, Chaoqun Wang, Jiyu Cheng, Clarence W De Silva, Max Q. -H. Meng
    http://arxiv.org/abs/2006.14195v1
    • [cs.RO]Optimal Trajectory Planning for Flexible Robots with Large Deformation
    M. Sajjad Edalatzadeh
    http://arxiv.org/abs/2006.14281v1
    • [cs.RO]Robust Relative Hand Placement For Bi-Manual Tasks
    Anirban Sinha, Nilanjan Chakraborty
    http://arxiv.org/abs/2006.14467v1
    • [cs.RO]Three-Dimensional Dynamic Modeling and Motion Analysis for an Active-Tail-Actuated Robotic Fish with Barycentre Regulating Mechanism
    Xingwen Zheng, Minglei Xiong, Junzheng Zheng, Manyi Wang, Runyu Tian, Guangming Xie
    http://arxiv.org/abs/2006.14420v1
    • [cs.SI]A metric on directed graphs and Markov chains based on hitting probabilities
    Zachary M. Boyd, Nicolas Fraiman, Jeremy L. Marzuola, Peter J. Mucha, Braxton Osting, Jonathan Weare
    http://arxiv.org/abs/2006.14482v1
    • [cs.SI]Controversial information spreads faster and further in Reddit
    Jasser Jasser, Ivan Garibay, Steve Scheinert, Alexander V. Mantzaris
    http://arxiv.org/abs/2006.13991v1
    • [cs.SI]Identify Influential Nodes in Online Social Network for Brand Communication
    Yuxin Mao, Lujie Zhou, Naixue Xiong
    http://arxiv.org/abs/2006.14104v1
    • [cs.SI]Mobile smartphone tracing can detect almost all SARS-CoV-2 infections
    Bastian Prasse, Piet Van Mieghem
    http://arxiv.org/abs/2006.14285v1
    • [cs.SI]TweetsCOV19 — A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic
    Dimitar Dimitrov, Erdal Baran, Pavlos Fafalios, Ran Yu, Xiaofei Zhu, Matthäus Zloch, Stefan Dietze
    http://arxiv.org/abs/2006.14492v1
    • [econ.EM]A Model of the Fed’s View on Inflation
    Thomas Hasenzagl, Filippo Pellegrino, Lucrezia Reichlin, Giovanni Ricco
    http://arxiv.org/abs/2006.14110v1
    • [econ.EM]Cointegration in large VARs
    Anna Bykhovskaya, Vadim Gorin
    http://arxiv.org/abs/2006.14179v1
    • [econ.EM]Inference without smoothing for large panels with cross-sectional and temporal dependence
    J. Hidalgo, M. Schafgans
    http://arxiv.org/abs/2006.14409v1
    • [eess.AS]Gamma Boltzmann Machine for Simultaneously Modeling Linear- and Log-amplitude Spectra
    Toru Nakashika, Kohei Yatabe
    http://arxiv.org/abs/2006.13590v2
    • [eess.IV]Block-matching in FPGA
    Rafael Pizarro Solar, Michal Pleskowicz
    http://arxiv.org/abs/2006.14105v1
    • [eess.IV]Collaborative Boundary-aware Context Encoding Networks for Error Map Prediction
    Zhenxi Zhang, Chunna Tian, Jie Li, Zhusi Zhong, Zhicheng Jiao, Xinbo Gao
    http://arxiv.org/abs/2006.14345v1
    • [eess.IV]Deep Residual 3D U-Net for Joint Segmentation and Texture Classification of Nodules in Lung
    Alexandr G. Rassadin
    http://arxiv.org/abs/2006.14215v1
    • [eess.IV]Multimarginal Wasserstein Barycenter for Stain Normalization and Augmentation
    Saad Nadeem, Travis Hollmann, Allen Tannenbaum
    http://arxiv.org/abs/2006.14566v1
    • [eess.IV]Perfusion Quantification from Endoscopic Videos: Learning to Read Tumor Signatures
    Sergiy Zhuk, Jonathan P. Epperlein, Rahul Nair, Seshu Thirupati, Pol Mac Aonghusa, Ronan Cahill, Donal O’Shea
    http://arxiv.org/abs/2006.14321v1
    • [eess.IV]Training Variational Networks with Multi-Domain Simulations: Speed-of-Sound Image Reconstruction
    Melanie Bernhardt, Valery Vishnevskiy, Richard Rau, Orcun Goksel
    http://arxiv.org/abs/2006.14395v1
    • [eess.SP]Artificial Lateral Line Based Relative State Estimation for Two Adjacent Robotic Fish
    Xingwen Zheng, Wei Wang, Liang Li, Guangming Xie
    http://arxiv.org/abs/2006.14421v1
    • [eess.SP]Composition Modulation
    Ferhat Yarkin, Justin P. Coon
    http://arxiv.org/abs/2006.14400v1
    • [eess.SP]Neural Networks Based Beam Codebooks: Learning mmWave Massive MIMO Beams that Adapt to Deployment and Hardware
    Muhammad Alrabeiah, Yu Zhang, Ahmed Alkhateeb
    http://arxiv.org/abs/2006.14501v1
    • [math.DS]Inferring Causal Networks of Dynamical Systems through Transient Dynamics and Perturbation
    George Stepaniants, Bingni W. Brunton, J. Nathan Kutz
    http://arxiv.org/abs/2006.13154v2
    • [math.OC]Dual-Free Stochastic Decentralized Optimization with Variance Reduction
    Hadrien Hendrikx, Francis Bach, Laurent Massoulié
    http://arxiv.org/abs/2006.14384v1
    • [math.OC]Heat kernel and intrinsic Gaussian processes on manifolds
    Ke Ye, Mu Niu, Pokman Cheung
    http://arxiv.org/abs/2006.14266v1
    • [math.OC]Multi-marginal optimal transport and probabilistic graphical models
    Isabel Haasler, Rahul Singh, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
    http://arxiv.org/abs/2006.14113v1
    • [math.OC]Riccati-based feedback stabilization for unstable Power system models
    Mahtab Uddin, M. Monir Uddin, Md. Abdul Hakim Khan
    http://arxiv.org/abs/2006.14210v1
    • [math.ST]An $\ell_p$ theory of PCA and spectral clustering
    Emmanuel Abbe, Jianqing Fan, Kaizheng Wang
    http://arxiv.org/abs/2006.14062v1
    • [math.ST]Deconvolution with unknown noise distribution is possible for multivariate signals
    Elisabeth Gassiat, Sylvain Le Corff, Luc Lehéricy
    http://arxiv.org/abs/2006.14226v1
    • [math.ST]Estimation and Comparison of Correlation-based Measures of Concordance
    Takaaki Koike, Marius Hofert
    http://arxiv.org/abs/2006.13975v1
    • [math.ST]On the relationship between beta-Bartlett and Uhlig extended processes
    Víctor Peña, Kaoru Irie
    http://arxiv.org/abs/2006.13868v2
    • [math.ST]Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets
    Avetik Karagulyan, Arnak S. Dalalyan
    http://arxiv.org/abs/2006.13998v1
    • [physics.soc-ph]Estimating Road Network Accessibility during a Hurricane Evacuation: A Case Study of Hurricane Irma in Florida
    Yi-Jie Zhu, Yujie Hu, Jennifer M. Collins
    http://arxiv.org/abs/2006.14137v1
    • [physics.soc-ph]Estimating a Large Drive Time Matrix between Zip Codes in the United States: A Differential Sampling Approach
    Yujie Hu, Changzhen Wang, Ruiyang Li, Fahui Wang
    http://arxiv.org/abs/2006.14138v1
    • [physics.soc-ph]Intervention scenarios to enhance knowledge transfer in a network of firm
    Frank Schweitzer, Yan Zhang, Giona Casiraghi
    http://arxiv.org/abs/2006.14249v1
    • [physics.soc-ph]Statistical inference of assortative community structures
    Lizhi Zhang, Tiago P. Peixoto
    http://arxiv.org/abs/2006.14493v1
    • [physics.soc-ph]Topology dependent payoffs can lead to escape from prisoner’s dilemma
    Saptarshi Sinha, Deep Nath, Soumen Roy
    http://arxiv.org/abs/2006.14593v1
    • [q-bio.NC]Habit learning supported by efficiently controlled network dynamics in naive macaque monkeys
    Karol P. Szymula, Fabio Pasqualetti, Ann M. Graybiel, Theresa M. Desrochers, Danielle S. Bassett
    http://arxiv.org/abs/2006.14565v1
    • [q-bio.NC]Predictive coding in balanced neural networks with noise, chaos and delays
    Jonathan Kadmon, Jonathan Timcheck, Surya Ganguli
    http://arxiv.org/abs/2006.14178v1
    • [quant-ph]Un-Weyl-ing the Clifford Hierarchy
    Tefjol Pllaha, Narayanan Rengaswamy, Olav Tirkkonen, Robert Calderbank
    http://arxiv.org/abs/2006.14040v1
    • [stat.AP]A Clinical Trial Derived Reference Set for Evaluating Observational Study Methods
    Ethan Steinberg, Steve Yadlowsky, Nigam H. Shah
    http://arxiv.org/abs/2006.14102v1
    • [stat.AP]Categorical Exploratory Data Analysis: From Multiclass Classification and Response Manifold Analytics perspectives of baseball pitching dynamics
    Fushing Hsieh, Elizabeth P. Chou
    http://arxiv.org/abs/2006.14411v1
    • [stat.AP]Data-driven Analytics of COVID-2019 for Epidemic Prediction, Clinical Diagnosis, Policy Effectiveness and Contact Tracing: A Survey
    Ying Mao, Susiyan Jiang, Daniel Nametz, Yuxin Lin, Jake Hack, John Hensley, Ryan Monaghan, Tess Gutenbrunner
    http://arxiv.org/abs/2006.13994v1
    • [stat.AP]Identifying group contributions in NBA lineups with spectral analysis
    Stephen Devlin, David Uminsky
    http://arxiv.org/abs/2006.14188v1
    • [stat.AP]Retiree mortality forecasting: A partial age-range or a full age-range model?
    Han Lin Shang, Steven Haberman
    http://arxiv.org/abs/2006.14131v1
    • [stat.AP]The Hot Hand in Actual Game Situations
    Konstantinos Pelechrinis, Wayne Winston
    http://arxiv.org/abs/2006.14609v1
    • [stat.CO]Stratified stochastic variational inference for high-dimensional network factor model
    Emanuele Aliverti, Massimiliano Russo
    http://arxiv.org/abs/2006.14217v1
    • [stat.ME]Break Point Detection for Functional Covariance
    Shuhao Jiao, Ron D. Frostig, Hernando Ombao
    http://arxiv.org/abs/2006.13887v2
    • [stat.ME]Discussion of ‘Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection’
    Haeran Cho, Claudia Kirch
    http://arxiv.org/abs/2006.14273v1
    • [stat.ME]Inferring median survival differences in general factorial designs via permutation tests
    Marc Ditzhaus, Dennis Dobler, Markus Pauly
    http://arxiv.org/abs/2006.14316v1
    • [stat.ME]Robust and Efficient Approximate Bayesian Computation: A Minimum Distance Approach
    David T. Frazier
    http://arxiv.org/abs/2006.14126v1
    • [stat.ME]Spatio-temporal Inversion using the Selection Kalman Model
    Maxime Conjard, Henning Omre
    http://arxiv.org/abs/2006.14343v1
    • [stat.ML]Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation
    Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande
    http://arxiv.org/abs/2006.14376v1
    • [stat.ML]BoXHED: Boosted eXact Hazard Estimator with Dynamic covariates
    Xiaochen Wang, Arash Pakbin, Bobak J. Mortazavi, Hongyu Zhao, Donald K. K. Lee
    http://arxiv.org/abs/2006.14218v1
    • [stat.ML]Consistency of Anchor-based Spectral Clustering
    Henry-Louis de Kergorlay, Desmond John Higham
    http://arxiv.org/abs/2006.13984v1
    • [stat.ML]Inverse Active Sensing: Modeling and Understanding Timely Decision-Making
    Daniel Jarrett, Mihaela van der Schaar
    http://arxiv.org/abs/2006.14141v1
    • [stat.ML]Labeled Optimal Partitioning
    Toby Dylan Hocking, Anuraag Srivastava
    http://arxiv.org/abs/2006.13967v1
    • [stat.ML]Machine learning the real discriminant locus
    Edgar A. Bernal, Jonathan D. Hauenstein, Dhagash Mehta, Margaret H. Regan, Tingting Tang
    http://arxiv.org/abs/2006.14078v1
    • [stat.ML]Neural Decomposition: Functional ANOVA with Variational Autoencoders
    Kaspar Märtens, Christopher Yau
    http://arxiv.org/abs/2006.14293v1
    • [stat.ML]Predicting First Passage Percolation Shapes Using Neural Networks
    Sebastian Rosengren
    http://arxiv.org/abs/2006.14004v1
    • [stat.ML]Q-NET: A Formula for Numerical Integration of a Shallow Feed-forward Neural Network
    Kartic Subr
    http://arxiv.org/abs/2006.14396v1
    • [stat.ML]STORM: Foundations of End-to-End Em
    805
    pirical Risk Minimization on the Edge
    Benjamin Coleman, Gaurav Gupta, John Chen, Anshumali Shrivastava
    http://arxiv.org/abs/2006.14554v1
    • [stat.ML]Slice Sampling for General Completely Random Measures
    Peiyuan Zhu, Alexandre Bouchard-Côté, Trevor Campbell
    http://arxiv.org/abs/2006.13925v2
    • [stat.ML]Spatio-temporal Sequence Prediction with Point Processes and Self-organizing Decision Trees
    Oguzhan Karaahmetoglu, Suleyman S. Kozat
    http://arxiv.org/abs/2006.14426v1
    • [stat.ML]Strictly Batch Imitation Learning by Energy-based Distribution Matching
    Daniel Jarrett, Ioana Bica, Mihaela van der Schaar
    http://arxiv.org/abs/2006.14154v1
    • [stat.ML]Taming GANs with Lookahead
    Tatjana Chavdarova, Matteo Pagliardini, Martin Jaggi, Francois Fleuret
    http://arxiv.org/abs/2006.14567v1
    • [stat.ML]Tensor Programs II: Neural Tangent Kernel for Any Architecture
    Greg Yang
    http://arxiv.org/abs/2006.14548v1