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.DS - 数据结构与算法 cs.HC - 人机接口 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.RO - 机器人学 cs.SD - 声音处理 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 eess.SY - 系统和控制 math-ph - 数学物理 math.OC - 优化与控制 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-bio.TO - 组织和器官 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

    • [cs.AI]AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
    • [cs.AI]Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings
    • [cs.AI]Circuit Routing Using Monte Carlo Tree Search and Deep Neural Networks
    • [cs.AI]Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario
    • [cs.AI]On the Relationship Between Active Inference and Control as Inference
    • [cs.AI]Turbocharging Treewidth-Bounded Bayesian Network Structure Learning
    • [cs.CL]A High-Quality Multilingual Dataset for Structured Documentation Translation
    • [cs.CL]Attention-Based Neural Networks for Sentiment Attitude Extraction using Distant Supervision
    • [cs.CL]Automating Text Naturalness Evaluation of NLG Systems
    • [cs.CL]Classifying Referential and Non-referential It Using Gaze
    • [cs.CL]Efficient Constituency Parsing by Pointing
    • [cs.CL]Exploring Software Naturalness through Neural Language Models
    • [cs.CL]One Model to Pronounce Them All: Multilingual Grapheme-to-Phoneme Conversion With a Transformer Ensemble
    • [cs.CL]Supervised Understanding of Word Embeddings
    • [cs.CR]A First Look at Contact Tracing Apps
    • [cs.CR]ACOUSTIC-TURF: Acoustic-based Privacy-Preserving COVID-19 Contact Tracing
    • [cs.CR]DeepMnemonic: Password Mnemonic Generation via Deep Attentive Encoder-Decoder Model
    • [cs.CR]Less is More: Exploiting Social Trust to Increase the Effectiveness of a Deception Attack
    • [cs.CR]Practical and Verifiable Electronic Sortition
    • [cs.CV]3D Pose Detection in Videos: Focusing on Occlusion
    • [cs.CV]3DMotion-Net: Learning Continuous Flow Function for 3D Motion Prediction
    • [cs.CV]A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge
    • [cs.CV]ATSO: Asynchronous Teacher-Student Optimizationfor Semi-Supervised Medical Image Segmentation
    • [cs.CV]Affinity Fusion Graph-based Framework for Natural Image Segmentation
    • [cs.CV]Anomaly Detection with Deep Perceptual Autoencoders
    • [cs.CV]Applying Lie Groups Approaches for Rigid Registration of Point Clouds
    • [cs.CV]Artist-Guided Semiautomatic Animation Colorization
    • [cs.CV]Automatic Estimation of Self-Reported Pain by Interpretable Representations of Motion Dynamics
    • [cs.CV]Comprehensive Information Integration Modeling Framework for Video Titling
    • [cs.CV]DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection for Dual-Energy X-Ray Baggage Imagery
    • [cs.CV]DISK: Learning local features with policy gradient
    • [cs.CV]DISK: Learning local features with policy gradient
    • [cs.CV]DeepTracking-Net: 3D Tracking with Unsupervised Learning of Continuous Flow
    • [cs.CV]Disentangle Perceptual Learning through Online Contrastive Learning
    • [cs.CV]Dynamic Functional Connectivity and Graph Convolution Network for Alzheimer’s Disease Classification
    • [cs.CV]FBK-HUPBA Submission to the EPIC-Kitchens Action Recognition 2020 Challenge
    • [cs.CV]Feature-dependent Cross-Connections in Multi-Path Neural Networks
    • [cs.CV]Generating Annotated High-Fidelity Images Containing Multiple Coherent Objects
    • [cs.CV]IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency
    • [cs.CV]Image-to-image Mapping with Many Domains by Sparse Attribute Transfer
    • [cs.CV]Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness
    • [cs.CV]Improving task-specific representation via 1M unlabelled images without any extra knowledge
    • [cs.CV]Insights from the Future for Continual Learning
    • [cs.CV]Iris Presentation Attack Detection: Where Are We Now?
    • [cs.CV]Labelling unlabelled videos from scratch with multi-modal self-supervision
    • [cs.CV]Large-scale detection and categorization of oil spills from SAR images with deep learning
    • [cs.CV]Learning Interclass Relations for Image Classification
    • [cs.CV]Learning Physical Graph Representations from Visual Scenes
    • [cs.CV]Learning Semantically Enhanced Feature for Fine-Grained Image Classification
    • [cs.CV]Meta Transfer Learning for Emotion Recognition
    • [cs.CV]Modelling the Statistics of Cyclic Activities by Trajectory Analysis on the Manifold of Positive-Semi-Definite Matrices
    • [cs.CV]Movement Tracking by Optical Flow Assisted Inertial Navigation
    • [cs.CV]Multi-view Drone-based Geo-localization via Style and Spatial Alignment
    • [cs.CV]NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
    • [cs.CV]Neural Non-Rigid Tracking
    • [cs.CV]Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks
    • [cs.CV]PhishGAN: Data Augmentation and Identification of Homoglpyh Attacks
    • [cs.CV]Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders
    • [cs.CV]RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification
    • [cs.CV]Recurrent Relational Memory Network for Unsupervised Image Captioning
    • [cs.CV]Rescaling Egocentric Vision
    • [cs.CV]Rethinking Distributional Matching Based Domain Adaptation
    • [cs.CV]Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks
    • [cs.CV]Road surface detection and differentiation considering surface damages
    • [cs.CV]Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with Consistency
    • [cs.CV]Self-Convolution: A Highly-Efficient Operator for Non-Local Image Restoration
    • [cs.CV]Towards Adversarial Planning for Indoor Scenes with Rotation
    • [cs.CV]Unifying Optimization Methods for Color Filter Design
    • [cs.CV]X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data
    • [cs.CY]A Cloud Computing Capability Model for Large-Scale Semantic Annotation
    • [cs.CY]Adoption of ICT innovations in the agriculture sector in Africa: A Systematic Literature Review
    • [cs.CY]Computational Support for Substance Use Disorder Prevention, Detection, Treatment, and Recovery
    • [cs.CY]K-Prototype Segmentation Analysis on Large-scale Ridesourcing Trip Data
    • [cs.CY]On Fair Selection in the Presence of Implicit Variance
    • [cs.CY]Using Deep Learning and Explainable Artificial Intelligence in Patients’ Choices of Hospital Levels
    • [cs.DC]A Benchmarking Framework for Interactive 3D Applications in the Cloud
    • [cs.DC]Effective Elastic Scaling of Deep Learning Workloads
    • [cs.DC]Integrating LHCb workflows on HPC resources: status and strategies
    • [cs.DC]Local-Search Based Heuristics for Advertisement Scheduling
    • [cs.DL]DINGO: an ontology for projects and grants linked data
    • [cs.DS]Approximation of the Diagonal of a Laplacian’s Pseudoinverse for Complex Network Analysis
    • [cs.DS]Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time
    • [cs.DS]The Power of Connection: Leveraging Network Analysis to Advance Receivable Financing
    • [cs.HC]A Methodology for Creating AI FactSheets
    • [cs.HC]Order of Control and Perceived Control over Personal Information
    • [cs.HC]TeslaMirror: Multistimulus Encounter-Type Haptic Display for Shape and Texture Rendering in VR
    • [cs.IR]Community-Based Data Integration of Course and Job Data in Support of Personalized Career-Education Recommendations
    • [cs.IR]Mining Misdiagnosis Patterns from Biomedical Literature
    • [cs.IT]Backscatter Cooperation in NOMA Communications Systems
    • [cs.IT]Deep Reinforcement Learning for Joint Beamwidth and Power Optimization in mmWave Systems
    • [cs.IT]Downlink Analysis for Reconfigurable Intelligent Surfaces Aided NOMA Networks
    • [cs.IT]Multi-Agent Reinforcement Learning for Cooperative Coded Caching via Homotopy Optimization
    • [cs.IT]Non-Orthogonal Multiple Access for UAV-Aided Heterogeneous Networks: A Stochastic Geometry Model
    • [cs.IT]On the Capacity of the Joint Time and Concentration Modulation for Molecular Communications
    • [cs.IT]Semi-Grant-Free NOMA: A Stochastic Geometry Model
    • [cs.IT]Stochastic Transceiver Optimization in Multi-Tags Symbiotic Radio Systems
    • [cs.IT]The Effect of Coupling Memory and Block Length on Spatially Coupled Serially Concatenated Codes
    • [cs.IT]The benefits of acting locally: Reconstruction algorithms for sparse in levels signals with stable and robust recovery guarantees
    • [cs.LG]A Limitation of the PAC-Bayes Framework
    • [cs.LG]A Note on Over-Smoothing for Graph Neural Networks
    • [cs.LG]AReLU: Attention-based Rectified Linear Unit
    • [cs.LG]Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes
    • [cs.LG]Advances in Asynchronous Parallel and Distributed Optimization
    • [cs.LG]Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
    • [cs.LG]Approximating a Target Distribution using Weight Queries
    • [cs.LG]Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View
    • [cs.LG]Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL
    • [cs.LG]Bayesian Sampling Bias Correction: Training with the Right Loss Function
    • [cs.LG]Befriending The Byzantines Through Reputation Scores
    • [cs.LG]Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework
    • [cs.LG]Classification Performance Metric for Imbalance Data Based on Recall and Selectivity Normalized in Class Labels
    • [cs.LG]Continuous Submodular Function Maximization
    • [cs.LG]Control-Aware Representations for Model-based Reinforcement Learning
    • [cs.LG]Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning
    • [cs.LG]Defending against adversarial attacks on medical imaging AI system, classification or detection?
    • [cs.LG]Differentiable Window for Dynamic Local Attention
    • [cs.LG]Distributionally-Robust Machine Learning Using Locally Differentially-Private Data
    • [cs.LG]Dynamic of Stochastic Gradient Descent with State-Dependent Noise
    • [cs.LG]Ensemble Kernel Methods, Implicit Regularization and Determinental Point Processes
    • [cs.LG]Fairness with Overlapping Groups
    • [cs.LG]Fairness without Demographics through Adversarially Reweighted Learning
    • [cs.LG]Generative causal explanations of black-box classifiers
    • [cs.LG]Graph Policy Network for Transferable Active Learning on Graphs
    • [cs.LG]Hierarchically Local Tasks and Deep Convolutional Networks
    • [cs.LG]Hyperparameter Ensembles for Robustness and Uncertainty Quantification
    • [cs.LG]Lattice Representation Learning
    • [cs.LG]Learning Disentangled Representations of Video with Missing Data
    • [cs.LG]Learning Gradient Boosted Multi-label Classification Rules
    • [cs.LG]Learning Potentials of Quantum Systems using Deep Neural Networks
    • [cs.LG]Likelihood-Free Gaussian Process for Regression
    • [cs.LG]Local Stochastic Approximation: A Unified View of Federated Learning and Distributed Multi-Task Reinforcement Learning Algorithms
    • [cs.LG]Locally Masked Convolution for Autoregressive Models
    • [cs.LG]Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks
    • [cs.LG]Non-Convex Structured Phase Retrieval
    • [cs.LG]Normalized Loss Functions for Deep Learning with Noisy Labels
    • [cs.LG]Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
    • [cs.LG]Off-the-grid: Fast and Effective Hyperparameter Search for Kernel Clustering
    • [cs.LG]On Multivariate Singular Spectrum Analysis
    • [cs.LG]On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures
    • [cs.LG]Online Competitive Influence Maximization
    • [cs.LG]Online Dense Subgraph Discovery via Blurred-Graph Feedback
    • [cs.LG]OvA-INN: Continual Learning with Invertible Neural Networks
    • [cs.LG]Principal Component Networks: Parameter Reduction Early in Training
    • [cs.LG]Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds
    • [cs.LG]Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression
    • [cs.LG]Quantifying Differences in Reward Functions
    • [cs.LG]RL Unplugged: Benchmarks for Offline Reinforcement Learning
    • [cs.LG]Ramanujan Bipartite Graph Products for Efficient Block Sparse Neural Networks
    • [cs.LG]Randomized Block-Diagonal Preconditioning for Parallel Learning
    • [cs.LG]Reducing Overestimation Bias by Increasing Representation Dissimilarity in Ensemble Based Deep Q-Learning
    • [cs.LG]Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
    • [cs.LG]Road Network Metric Learning for Estimated Time of Arrival
    • [cs.LG]Robust Domain Adaptation: Representations, Weights and Inductive Bias
    • [cs.LG]Safe Learning under Uncertain Objectives and Constraints
    • [cs.LG]Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations
    • [cs.LG]Spherical Perspective on Learning with Batch Norm
    • [cs.LG]Thalamocortical motor circuit insights for more robust hierarchical control of complex sequences
    • [cs.LG]The NetHack Learning Environment
    • [cs.LG]Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes
    • [cs.LG]Towards Understanding Hierarchical Learning: Benefits of Neural Representations
    • [cs.LG]Uncertainty in Neural Relational Inference Trajectory Reconstruction
    • [cs.LG]Understanding Deep Architectures with Reasoning Layer
    • [cs.LG]When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
    • [cs.LO]DeepAbstract: Neural Network Abstraction for Accelerating Verification
    • [cs.NE]Crossmodal Language Grounding in an Embodied Neurocognitive Model
    • [cs.NE]hxtorch: PyTorch for BrainScaleS-2 — Perceptrons on Analog Neuromorphic Hardware
    • [cs.RO]A Hierarchical Framework for Long-term and Robust Deployment of Field Ground Robots in Large-Scale Farming
    • [cs.RO]A Thermoplastic Elastomer Belt Based Robotic Gripper
    • [cs.RO]Efficient Sampling-Based Maximum Entropy Inverse Reinforcement Learning with Application to Autonomous Driving
    • [cs.RO]Evaluation of Sampling Methods for Robotic Sediment Sampling Systems
    • [cs.RO]GMMLoc: Structure Consistent Visual Localization with Gaussian Mixture Models
    • [cs.RO]Multi-modal Trajectory Optimization for Impact-aware Manipulation
    • [cs.RO]Namira Soccer 2D Simulation Team Description Paper 2020
    • [cs.RO]Robot Object Retrieval with Contextual Natural Language Queries
    • [cs.SD]Bach or Mock? A Grading Function for Chorales in the Style of J.S. Bach
    • [cs.SD]Incorporating Music Knowledge in Continual Dataset Augmentation for Music Generation
    • [cs.SI]Competitive Balance in Team Sports Games
    • [cs.SI]Movie Box office Prediction via Joint Actor Representations and Social Media Sentiment
    • [cs.SI]Network connectivity under a probabilistic node failure model
    • [cs.SI]On Analyzing Annotation Consistency in Online Abusive Behavior Datasets
    • [cs.SI]Provably and Efficiently Approximating Near-cliques using the Turán Shadow: PEANUTS
    • [cs.SI]Quantifying the influence of inter-county mobility patterns on the COVID-19 outbreak in the United States
    • [cs.SI]Wikipedia and Westminster: Quality and Dynamics of Wikipedia Pages about UK Politicians
    • [cs.SI]Winning the competition: enhancing counter-contagion in SIS-like epidemic processes
    • [eess.AS]Black-box Adaptation of ASR for Accented Speech
    • [eess.AS]Face-to-Music Translation Using a Distance-Preserving Generative Adversarial Network with an Auxiliary Discriminator
    • [eess.AS]Gamma Boltzmann Machine for Simultaneously Modeling Linear- and Log-amplitude Spectra
    • [eess.IV]A Novel Approach for Correcting Multiple Discrete Rigid In-Plane Motions Artefacts in MRI Scans
    • [eess.IV]Automated Detection of COVID-19 from CT Scans Using Convolutional Neural Networks
    • [eess.IV]Deep Generative Model-based Quality Control for Cardiac MRI Segmentation
    • [eess.IV]Does Non-COVID19 Lung Lesion Help? Investigating Transferability in COVID-19 CT Image Segmentation
    • [eess.IV]Feedback Graph Attention Convolutional Network for Medical Image Enhancement
    • [eess.IV]Flexible Image Denoising with Multi-layer Conditional Feature Modulation
    • [eess.IV]GIFnets: Differentiable GIF Encoding Framework
    • [eess.IV]Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction
    • [eess.IV]Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model
    • [eess.IV]MRI Image Reconstruction via Learning Optimization using Neural ODEs
    • [eess.IV]Malignancy-Aware Follow-Up Volume Prediction for Lung Nodules
    • [eess.IV]Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials
    • [eess.IV]NINEPINS: Nuclei Instance Segmentation with Point Annotations
    • [eess.IV]Realistic Adversarial Data Augmentation for MR Image Segmentation
    • [eess.IV]Stacked Convolutional Neural Network for Diagnosis of COVID-19 Disease from X-ray Images
    • [eess.IV]Was there COVID-19 back in 2012? Challenge for AI in Diagnosis with Similar Indications
    • [eess.SP]Autonomous Interference Mapping for Industrial IoT Networks over Unlicensed Bands
    • [eess.SP]Clustering and Power Optimization for NOMA Multi-Objective Problems
    • [eess.SP]Energy Minimization in UAV-Aided Networks: Actor-Critic Learning for Constrained Scheduling Optimization
    • [eess.SP]JCR70: A Low-Complexity Millimeter-Wave Proof-of-Concept Platform for A Fully-Digital MIMO Joint Communication-Radar
    • [eess.SP]Traffic congestion anomaly detection and prediction using deep learning
    • [eess.SY]Learning-to-Fly: Learning-based Collision Avoidance for Scalable Urban Air Mobility
    • [math-ph]Exact variance of von Neumann entanglement entropy over the Bures-Hall measure
    • [math.OC]Unified Reinforcement Q-Learning for Mean Field Game and Control Problems
    • [math.ST]A Mean-Field Theory for Learning the Schönberg Measure of Radial Basis Functions
    • [math.ST]Gromov-Wasserstein Distance based Object Matching: Asymptotic Inference
    • [math.ST]On the relationship between beta-Bartlett and Uhlig extended processes
    • [math.ST]Second order asymptotic efficiency for a Poisson process
    • [physics.soc-ph]A critique of the Mean Field Approximation in preferential attachment networks
    • [physics.soc-ph]From form to information: Analysing built environments in different spatial cultures
    • [physics.soc-ph]Quantifying Policy Responses to a Global Emergency: Insights from the COVID-19 Pandemic
    • [q-bio.TO]Deep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primary
    • [quant-ph]Uniqueness and Optimality of Dynamical Extensions of Divergences
    • [stat.AP]Diagnosis Prevalence vs. Efficacy in Machine-learning Based Diagnostic Decision Support
    • [stat.AP]Discrete distributions from a Markov chain
    • [stat.AP]Dynamic Population Estimation Using Anonymized Mobility Data
    • [stat.AP]Spatial Pattern Recognition with Adjacency-Clustering: Improved Diagnostics for Semiconductor Wafer Bin Maps
    • [stat.AP]Using social contact data to improve the overall effect estimate of a cluster-randomized influenza vaccination program in Senega
    • [stat.CO]Fast computation of latent correlations
    • [stat.CO]The Boomerang Sampler
    • [stat.ME]A Fast and Efficient Change-point Detection Framework for Modern Data
    • [stat.ME]A Robust Consistent Information Criterion for Model Selection based on Empirical Likelihood
    • [stat.ME]Bayesian Shrinkage for Functional Network Models with Intractable Normalizing Constants
    • [stat.ME]Break Point Detection for Functional Covariance
    • [stat.ME]Global Sensitivity and Domain-Selective Testing for Functional-Valued Responses: An Application to Climate Economy Models
    • [stat.ME]Inference in Stochastic Epidemic Models via Multinomial Approximations
    • [stat.ME]Min-Mid-Max Scaling, Limits of Agreement, and Agreement Score
    • [stat.ME]Sequential Gibbs Sampling Algorithm for Cognitive Diagnosis Models with Many Attributes
    • [stat.ME]Unified Principal Component Analysis for Sparse and Dense Functional Data under Spatial Dependency
    • [stat.ME]Uniform convergence of local Fréchet regression and time warping for metric-space-valued trajectories
    • [stat.ML]A General Class of Transfer Learning Regression without Implementation Cost
    • [stat.ML]Design and Evaluation of Personalized Free Trials
    • [stat.ML]Distribution-Based Invariant Deep Networks for Learning Meta-Features
    • [stat.ML]Non-Parametric Graph Learning for Bayesian Graph Neural Networks
    • [stat.ML]Simple and Scalable Parallelized Bayesian Optimization
    • [stat.ML]Slice Sampling for General Completely Random Measures
    • [stat.ML]When Do Neural Networks Outperform Kernel Methods?
    ·····································
    • [cs.AI]AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
    Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han
    http://arxiv.org/abs/2006.13473v1
    • [cs.AI]Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings
    David Chang, Ivana Balazevic, Carl Allen, Daniel Chawla, Cynthia Brandt, Richard Andrew Taylor
    http://arxiv.org/abs/2006.13774v1
    • [cs.AI]Circuit Routing Using Monte Carlo Tree Search and Deep Neural Networks
    Youbiao He, Forrest Sheng Bao
    http://arxiv.org/abs/2006.13607v1
    • [cs.AI]Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario
    Francisco Cruz, Richard Dazeley, Peter Vamplew
    http://arxiv.org/abs/2006.13615v1
    • [cs.AI]On the Relationship Between Active Inference and Control as Inference
    Beren Millidge, Alexander Tschantz, Anil K Seth, Christopher L Buckley
    http://arxiv.org/abs/2006.12964v2
    • [cs.AI]Turbocharging Treewidth-Bounded Bayesian Network Structure Learning
    Vaidyanathan P. R., Stefan Szeider
    http://arxiv.org/abs/2006.13843v1
    • [cs.CL]A High-Quality Multilingual Dataset for Structured Documentation Translation
    Kazuma Hashimoto, Raffaella Buschiazzo, James Bradbury, Teresa Marshall, Richard Socher, Caiming Xiong
    http://arxiv.org/abs/2006.13425v1
    • [cs.CL]Attention-Based Neural Networks for Sentiment Attitude Extraction using Distant Supervision
    Nicolay Rusnachenko, Natalia Loukachevitch
    http://arxiv.org/abs/2006.13730v1
    • [cs.CL]Automating Text Naturalness Evaluation of NLG Systems
    Erion Çano, Ondřej Bojar
    http://arxiv.org/abs/2006.13268v1
    • [cs.CL]Classifying Referential and Non-referential It Using Gaze
    Victoria Yaneva, Le An Ha, Richard Evans, Ruslan Mitkov
    http://arxiv.org/abs/2006.13327v1
    • [cs.CL]Efficient Constituency Parsing by Pointing
    Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, Xiaoli Li
    http://arxiv.org/abs/2006.13557v1
    • [cs.CL]Exploring Software Naturalness through Neural Language Models
    Luca Buratti, Saurabh Pujar, Mihaela Bornea, Scott McCarley, Yunhui Zheng, Gaetano Rossiello, Alessandro Morari, Jim Laredo, Veronika Thost, Yufan Zhuang, Giacomo Domeniconi
    http://arxiv.org/abs/2006.12641v2
    • [cs.CL]One Model to Pronounce Them All: Multilingual Grapheme-to-Phoneme Conversion With a Transformer Ensemble
    Kaili Vesik, Muhammad Abdul-Mageed, Miikka Silfverberg
    http://arxiv.org/abs/2006.13343v1
    • [cs.CL]Supervised Understanding of Word Embeddings
    Halid Ziya Yerebakan, Parmeet Bhatia, Yoshihisa Shinagawa
    http://arxiv.org/abs/2006.13299v1
    • [cs.CR]A First Look at Contact Tracing Apps
    Muhammad Ajmal Azad, Junaid Arshad, Ali Akmal, Sidrah Abdullah, Farhan Ahmad, Muhammad Imran, Farhan Riaz
    http://arxiv.org/abs/2006.13354v1
    • [cs.CR]ACOUSTIC-TURF: Acoustic-based Privacy-Preserving COVID-19 Contact Tracing
    Yuxiang Luo, Cheng Zhang, Yunqi Zhang, Chaoshun Zuo, Dong Xuan, Zhiqiang Lin, Adam C. Champion, Ness Shroff
    http://arxiv.org/abs/2006.13362v1
    • [cs.CR]DeepMnemonic: Password Mnemonic Generation via Deep Attentive Encoder-Decoder Model
    Yao Cheng, Chang Xu, Zhen Hai, Yingjiu Li
    http://arxiv.org/abs/2006.13462v1
    • [cs.CR]Less is More: Exploiting Social Trust to Increase the Effectiveness of a Deception Attack
    Shahryar Baki, Rakesh M. Verma, Arjun Mukherjee, Omprakash Gnawali
    http://arxiv.org/abs/2006.13499v1
    • [cs.CR]Practical and Verifiable Electronic Sortition
    Hsun Lee, Hsu-Chun Hsiao
    http://arxiv.org/abs/2006.13920v1
    • [cs.CV]3D Pose Detection in Videos: Focusing on Occlusion
    Justin Wang, Edward Xu, Kangrui Xue, Lukasz Kidzinski
    http://arxiv.org/abs/2006.13517v1
    • [cs.CV]3DMotion-Net: Learning Continuous Flow Function for 3D Motion Prediction
    Shuaihang Yuan, Xiang Li, Anthony Tzes, Yi Fang
    http://arxiv.org/abs/2006.13906v1
    • [cs.CV]A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge
    Jianning Li, Antonio Pepe, Christina Gsaxner, Gord von Campe, Jan Egger
    http://arxiv.org/abs/2006.12449v2
    • [cs.CV]ATSO: Asynchronous Teacher-Student Optimizationfor Semi-Supervised Medical Image Segmentation
    Xinyue Huo, Lingxi Xie, Jianzhong He, Zijie Yang, Qi Tian
    http://arxiv.org/abs/2006.13461v1
    • [cs.CV]Affinity Fusion Graph-based Framework for Natural Image Segmentation
    Yang Zhang, Moyun Liu, Jingwu He, Fei Pan, Yanwen Guo
    http://arxiv.org/abs/2006.13542v1
    • [cs.CV]Anomaly Detection with Deep Perceptual Autoencoders
    Nina Tuluptceva, Bart Bakker, Irina Fedulova, Heinrich Schulz, Dmitry V. Dylov
    http://arxiv.org/abs/2006.13265v1
    • [cs.CV]Applying Lie Groups Approaches for Rigid Registration of Point Clouds
    Liliane Rodrigues de Almeida, Gilson A. Giraldi, Marcelo Bernardes Vieira
    http://arxiv.org/abs/2006.13341v1
    • [cs.CV]Artist-Guided Semiautomatic Animation Colorization
    Harrish Thasarathan, Mehran Ebrahimi
    http://arxiv.org/abs/2006.13717v1
    • [cs.CV]Automatic Estimation of Self-Reported Pain by Interpretable Representations of Motion Dynamics
    Benjamin Szczapa, Mohamed Daoudi, Stefano Berretti, Pietro Pala, Alberto Del Bimbo, Zakia Hammal
    http://arxiv.org/abs/2006.13882v1
    • [cs.CV]Comprehensive Information Integration Modeling Framework for Video Titling
    Shengyu Zhang, Ziqi Tan, Jin Yu, Zhou Zhao, Kun Kuang, Tan Jiang, Jingren Zhou, Hongxia Yang, Fei Wu
    http://arxiv.org/abs/2006.13608v1
    • [cs.CV]DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection for Dual-Energy X-Ray Baggage Imagery
    A. Williamson, P. Dickinson, T. Lambrou, J. C. Murray
    http://arxiv.org/abs/2006.13065v2
    • [cs.CV]DISK: Learning local features with policy gradient
    Michał J. Tyszkiewicz, Pascal Fua, Eduard Trulls
    http://arxiv.org/abs/2006.13566v1
    • [cs.CV]DISK: Learning local features with policy gradient
    Michał J. Tyszkiewicz, Pascal Fua, Eduard Trulls
    http://arxiv.org/abs/2006.13566v1
    4531


    • [cs.CV]DeepTracking-Net: 3D Tracking with Unsupervised Learning of Continuous Flow
    Shuaihang Yuan, Xiang Li, Yi Fang
    http://arxiv.org/abs/2006.13848v1
    • [cs.CV]Disentangle Perceptual Learning through Online Contrastive Learning
    Kangfu Mei, Yao Lu, Qiaosi Yi, Haoyu Wu, Juncheng Li, Rui Huang
    http://arxiv.org/abs/2006.13511v1
    • [cs.CV]Dynamic Functional Connectivity and Graph Convolution Network for Alzheimer’s Disease Classification
    Xingwei An, Yutao Zhou, Yang Di, Dong Ming
    http://arxiv.org/abs/2006.13510v1
    • [cs.CV]FBK-HUPBA Submission to the EPIC-Kitchens Action Recognition 2020 Challenge
    Swathikiran Sudhakaran, Sergio Escalera, Oswald Lanz
    http://arxiv.org/abs/2006.13725v1
    • [cs.CV]Feature-dependent Cross-Connections in Multi-Path Neural Networks
    Dumindu Tissera, Kasun Vithanage, Rukshan Wijesinghe, Kumara Kahatapitiya, Subha Fernando, Ranga Rodrigo
    http://arxiv.org/abs/2006.13904v1
    • [cs.CV]Generating Annotated High-Fidelity Images Containing Multiple Coherent Objects
    Bryan G. Cardenas, Devanshu Arya, Deepak K. Gupta
    http://arxiv.org/abs/2006.12150v2
    • [cs.CV]IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency
    Jiarui Cai, Yizhou Wang, Haotian Zhang, Hung-Min Hsu, Chengqian Ma, Jenq-Neng Hwang
    http://arxiv.org/abs/2006.13458v1
    • [cs.CV]Image-to-image Mapping with Many Domains by Sparse Attribute Transfer
    Matthew Amodio, Rim Assouel, Victor Schmidt, Tristan Sylvain, Smita Krishnaswamy, Yoshua Bengio
    http://arxiv.org/abs/2006.13291v1
    • [cs.CV]Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness
    Linxi Jiang, Xingjun Ma, Zejia Weng, James Bailey, Yu-Gang Jiang
    http://arxiv.org/abs/2006.13726v1
    • [cs.CV]Improving task-specific representation via 1M unlabelled images without any extra knowledge
    Aayush Bansal
    http://arxiv.org/abs/2006.13919v1
    • [cs.CV]Insights from the Future for Continual Learning
    Arthur Douillard, Eduardo Valle, Charles Ollion, Thomas Robert, Matthieu Cord
    http://arxiv.org/abs/2006.13748v1
    • [cs.CV]Iris Presentation Attack Detection: Where Are We Now?
    Aidan Boyd, Zhaoyuan Fang, Adam Czajka, Kevin W. Bowyer
    http://arxiv.org/abs/2006.13252v1
    • [cs.CV]Labelling unlabelled videos from scratch with multi-modal self-supervision
    Yuki M. Asano, Mandela Patrick, Christian Rupprecht, Andrea Vedaldi
    http://arxiv.org/abs/2006.13662v1
    • [cs.CV]Large-scale detection and categorization of oil spills from SAR images with deep learning
    Filippo Maria Bianchi, Martine M. Espeseth, Njål Borch
    http://arxiv.org/abs/2006.13575v1
    • [cs.CV]Learning Interclass Relations for Image Classification
    Muhamedrahimov Raouf, Bar Amir, Akselrod-Ballin Ayelet
    http://arxiv.org/abs/2006.13491v1
    • [cs.CV]Learning Physical Graph Representations from Visual Scenes
    Daniel M. Bear, Chaofei Fan, Damian Mrowca, Yunzhu Li, Seth Alter, Aran Nayebi, Jeremy Schwartz, Li Fei-Fei, Jiajun Wu, Joshua B. Tenenbaum, Daniel L. K. Yamins
    http://arxiv.org/abs/2006.12373v2
    • [cs.CV]Learning Semantically Enhanced Feature for Fine-Grained Image Classification
    Wei Luo, Hengmin Zhang, Jun Li, Xiu-Shen Wei
    http://arxiv.org/abs/2006.13457v1
    • [cs.CV]Meta Transfer Learning for Emotion Recognition
    D
    1440
    ung Nguyen, Sridha Sridharan, Duc Thanh Nguyen, Simon Denman, David Dean, Clinton Fookes
    http://arxiv.org/abs/2006.13211v1
    • [cs.CV]Modelling the Statistics of Cyclic Activities by Trajectory Analysis on the Manifold of Positive-Semi-Definite Matrices
    Ettore Maria Celozzi, Luca Ciabini, Luca Cultrera, Pietro Pala, Stefano Berretti, Mohamed Daoudi, Alberto Del Bimbo
    http://arxiv.org/abs/2006.13895v1
    • [cs.CV]Movement Tracking by Optical Flow Assisted Inertial Navigation
    Lassi Meronen, William J. Wilkinson, Arno Solin
    http://arxiv.org/abs/2006.13856v1
    • [cs.CV]Multi-view Drone-based Geo-localization via Style and Spatial Alignment
    Siyi Hu, Xiaojun Chang
    http://arxiv.org/abs/2006.13681v1
    • [cs.CV]NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
    Rameswar Panda, Michele Merler, Mayoore Jaiswal, Hui Wu, Kandan Ramakrishnan, Ulrich Finkler, Chun-Fu Chen, Minsik Cho, David Kung, Rogerio Feris, Bishwaranjan Bhattacharjee
    http://arxiv.org/abs/2006.13314v1
    • [cs.CV]Neural Non-Rigid Tracking
    Aljaž Božič, Pablo Palafox, Michael Zollhöfer, Angela Dai, Justus Thies, Matthias Nießner
    http://arxiv.org/abs/2006.13240v1
    • [cs.CV]Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks
    Francis Williams, Matthew Trager, Joan Bruna, Denis Zorin
    http://arxiv.org/abs/2006.13782v1
    • [cs.CV]PhishGAN: Data Augmentation and Identification of Homoglpyh Attacks
    Joon Sern Lee, Gui Peng David Yam, Jin Hao Chan
    http://arxiv.org/abs/2006.13742v1
    • [cs.CV]Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders
    Agostina J Larrazabal, César Martínez, Ben Glocker, Enzo Ferrante
    http://arxiv.org/abs/2006.13791v1
    • [cs.CV]RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification
    Jingtian Peng, Chang Xiao, Xun Wei, Yifan Li
    http://arxiv.org/abs/2006.12634v2
    • [cs.CV]Recurrent Relational Memory Network for Unsupervised Image Captioning
    Dan Guo, Yang Wang, Peipei Song, Meng Wang
    http://arxiv.org/abs/2006.13611v1
    • [cs.CV]Rescaling Egocentric Vision
    Dima Damen, Hazel Doughty, Giovanni Maria Farinella, Antonino Furnari, Evangelos Kazakos, Jian Ma, Davide Moltisanti, Jonathan Munro, Toby Perrett, Will Price, Michael Wray
    http://arxiv.org/abs/2006.13256v1
    • [cs.CV]Rethinking Distributional Matching Based Domain Adaptation
    Bo Li, Yezhen Wang, Tong Che, Shanghang Zhang, Sicheng Zhao, Pengfei Xu, Wei Zhou, Yoshua Bengio, Kurt Keutzer
    http://arxiv.org/abs/2006.13352v1
    • [cs.CV]Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks
    Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian
    http://arxiv.org/abs/2006.13593v1
    • [cs.CV]Road surface detection and differentiation considering surface damages
    Thiago Rateke, Aldo von Wangenheim
    http://arxiv.org/abs/2006.13377v1
    • [cs.CV]Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with Consistency
    Hyeonsoo Lee, Won-Ki Jeong
    http://arxiv.org/abs/2006.12890v2
    • [cs.CV]Self-Convolution: A Highly-Efficient Operator for Non-Local Image Restoration
    Lanqing Guo, Saiprasad Ravishankar, Bihan Wen
    http://arxiv.org/abs/2006.13714v1
    • [cs.CV]Towards Adversarial Planning for Indoor Scenes with Rotation
    Xinhan Di, Pengqian Yu, Hong Zhu, Lei Cai, Qiuyan Sheng, Changyu Sun
    http://arxiv.org/abs/2006.13527v1
    • [cs.CV]Unifying Optimization Methods for Color Filter Design
    Graham Finlayson, Yuteng Zhu
    http://arxiv.org/abs/2006.13622v1
    • [cs.CV]X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data
    Danfeng Hong, Naoto Yokoya, Gui-Song Xia, Jocelyn Chanussot, Xiao Xiang Zhu
    http://arxiv.org/abs/2006.13806v1
    • [cs.CY]A Cloud Computing Capability Model for Large-Scale Semantic Annotation
    Oluwasegun Adedugbe, Elhadj Benkhelifa
    http://arxiv.org/abs/2006.13893v1
    • [cs.CY]Adoption of ICT innovations in the agriculture sector in Africa: A Systematic Literature Review
    Claudia Ayim, Ayalew Kassahun, Bedir Tekinerdogan, Chris Addison
    http://arxiv.org/abs/2006.13831v1
    • [cs.CY]Computational Support for Substance Use Disorder Prevention, Detection, Treatment, and Recovery
    Lana Yarosh, Suzanne Bakken, Alan Borning, Munmun De Choudhury, Cliff Lampe, Elizabeth Mynatt, Stephen Schueller, Tiffany Veinot
    http://arxiv.org/abs/2006.13259v1
    • [cs.CY]K-Prototype Segmentation Analysis on Large-scale Ridesourcing Trip Data
    J Soria, Y Chen, A Stathopoulos
    http://arxiv.org/abs/2006.13924v1
    • [cs.CY]On Fair Selection in the Presence of Implicit Variance
    Vitalii Emelianov, Nicolas Gast, Krishna P. Gummadi, Patrick Loiseau
    http://arxiv.org/abs/2006.13699v1
    • [cs.CY]Using Deep Learning and Explainable Artificial Intelligence in Patients’ Choices of Hospital Levels
    Lichin Chen, Yu Tsao, Ji-Tian Sheu
    http://arxiv.org/abs/2006.13427v1
    • [cs.DC]A Benchmarking Framework for Interactive 3D Applications in the Cloud
    Tianyi Liu, Sen He, Sunzhou Huang, Danny Tsang, Lingjia Tang, Jason Mars, Wei Wang
    http://arxiv.org/abs/2006.13378v1
    • [cs.DC]Effective Elastic Scaling of Deep Learning Workloads
    Vaibhav Saxena, K. R. Jayaram, Saurav Basu, Yogish Sabharwal, Ashish Verma
    http://arxiv.org/abs/2006.13878v1
    • [cs.DC]Integrating LHCb workflows on HPC resources: status and strategies
    Federico Stagni, Andrea Valassi, Vladimir Romanovskiy
    http://arxiv.org/abs/2006.13603v1
    • [cs.DC]Local-Search Based Heuristics for Advertisement Scheduling
    M. R. C. da Silva, R. C. S. Schouery
    http://arxiv.org/abs/2006.13432v1
    • [cs.DL]DINGO: an ontology for projects and grants linked data
    Diego Chialva, Alexis-Michel Mugabushaka
    http://arxiv.org/abs/2006.13438v1
    • [cs.DS]Approximation of the Diagonal of a Laplacian’s Pseudoinverse for Complex Network Analysis
    Eugenio Angriman, Maria Predari, Alexander van der Grinten, Henning Meyerhenke
    http://arxiv.org/abs/2006.13679v1
    • [cs.DS]Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time
    Jerry Li, Guanghao Ye
    http://arxiv.org/abs/2006.13312v1
    • [cs.DS]The Power of Connection: Leveraging Network Analysis to Advance Receivable Financing
    Ilaria Bordino, Francesco Gullo, Giacomo Legnaro
    http://arxiv.org/abs/2006.13738v1
    • [cs.HC]A Methodology for Creating AI FactSheets
    John Richards, David Piorkowski, Michael Hind, Stephanie Houde, 38f2
    Aleksandra Mojsilović
    http://arxiv.org/abs/2006.13796v1
    • [cs.HC]Order of Control and Perceived Control over Personal Information
    Yefim Shulman, Thao Ngo, Joachim Meyer
    http://arxiv.org/abs/2006.13898v1
    • [cs.HC]TeslaMirror: Multistimulus Encounter-Type Haptic Display for Shape and Texture Rendering in VR
    Aleksey Fedoseev, Akerke Tleugazy, Luiza Labazanova, Dzmitry Tsetserukou
    http://arxiv.org/abs/2006.13660v1
    • [cs.IR]Community-Based Data Integration of Course and Job Data in Support of Personalized Career-Education Recommendations
    Guoqing Zhu, Naga Anjaneyulu Kopalle, Yongzhen Wang, Xiaozhong Liu, Kemi Jona, Katy Börner
    http://arxiv.org/abs/2006.13864v1
    • [cs.IR]Mining Misdiagnosis Patterns from Biomedical Literature
    Cindy Li, Elizabeth Chen, Guergana Savova, Hamish Fraser, Carsten Eickhoff
    http://arxiv.org/abs/2006.13721v1
    • [cs.IT]Backscatter Cooperation in NOMA Communications Systems
    Weiyu Chen, Haiyang Ding, Shilian Wang, Daniel Benevides da Costa, Fengkui Gong, Pedro Henrique Juliano Nardelli
    http://arxiv.org/abs/2006.13646v1
    • [cs.IT]Deep Reinforcement Learning for Joint Beamwidth and Power Optimization in mmWave Systems
    Jiabao Gao, Caijun Zhong, Xiaoming Chen, Hai Lin, Zhaoyang Zhang
    http://arxiv.org/abs/2006.13518v1
    • [cs.IT]Downlink Analysis for Reconfigurable Intelligent Surfaces Aided NOMA Networks
    Chao Zhang, Wenqiang Yi, Yuanwei Liu, Zhijin Qin, Kok Keong Chai
    http://arxiv.org/abs/2006.13260v1
    • [cs.IT]Multi-Agent Reinforcement Learning for Cooperative Coded Caching via Homotopy Optimization
    Xiongwei Wu, Jun Li, Ming Xiao, P. C. Ching, H. Vincent Poor
    http://arxiv.org/abs/2006.13565v1
    • [cs.IT]Non-Orthogonal Multiple Access for UAV-Aided Heterogeneous Networks: A Stochastic Geometry Model
    Cunzhuo Zhao, Yuanwei Liu, Yunlong Cai, Minjian Zhao
    http://arxiv.org/abs/2006.13657v1
    • [cs.IT]On the Capacity of the Joint Time and Concentration Modulation for Molecular Communications
    Farhad Mirkarimi, Mahtab Mirmohseni, Masoumeh Nasiri-Kenari
    http://arxiv.org/abs/2006.13398v1
    • [cs.IT]Semi-Grant-Free NOMA: A Stochastic Geometry Model
    Chao Zhang, Yuanwei Liu, Zhijin Qin, Zhiguo Ding
    http://arxiv.org/abs/2006.13286v1
    • [cs.IT]Stochastic Transceiver Optimization in Multi-Tags Symbiotic Radio Systems
    Xihan Chen, Hei Victor Cheng, Kaiming Shen, An Liu, Min-Jian Zhao
    http://arxiv.org/abs/2006.13668v1
    • [cs.IT]The Effect of Coupling Memory and Block Length on Spatially Coupled Serially Concatenated Codes
    Mojtaba Mahdavi, Muhammad Umar Farooq, Liang Liu, Ove Edfors, Viktor Öwall, Michael Lentmaier
    http://arxiv.org/abs/2006.13396v1
    • [cs.IT]The benefits of acting locally: Reconstruction algorithms for sparse in levels signals with stable and robust recovery guarantees
    Ben Adcock, Simone Brugiapaglia, Matthew King-Roskamp
    http://arxiv.org/abs/2006.13389v1
    • [cs.LG]A Limitation of the PAC-Bayes Framework
    Roi Livni, Shay Moran
    http://arxiv.org/abs/2006.13508v1
    • [cs.LG]A Note on Over-Smoothing for Graph Neural Networks
    Chen Cai, Yusu Wang
    http://arxiv.org/abs/2006.13318v1
    • [cs.LG]AReLU: Attention-based Rectified Linear Unit
    Dengsheng Chen, Kai Xu
    http://arxiv.org/abs/2006.13858v1
    • [cs.LG]Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes
    Shuai Zheng, Haibin Lin, Sheng Zha, Mu Li
    http://arxiv.org/abs/2006.13484v1
    • [cs.LG]Advances in Asynchronous Parallel and Distributed Optimization
    Mahmoud Assran, Arda Aytekin, Hamid Feyzmahdavian, Mikael Johansson, Michael Rabbat
    http://arxiv.org/abs/2006.13838v1
    • [cs.LG]Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
    Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Christopher Pal, Derek Nowrouzezahrai
    http://arxiv.org/abs/2006.13258v1
    • [cs.LG]Approximating a Target Distribution using Weight Queries
    Sivan Sabato
    http://arxiv.org/abs/2006.13636v1
    • [cs.LG]Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View
    Shen Wang, Jibing Gong, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu
    http://arxiv.org/abs/2006.13257v1
    • [cs.LG]Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL
    Lucas Zimmer, Marius Lindauer, Frank Hutter
    http://arxiv.org/abs/2006.13799v1
    • [cs.LG]Bayesian Sampling Bias Correction: Training with the Right Loss Function
    L. Le Folgoc, V. Baltatzis, A. Alansary, S. Desai, A. Devaraj, S. Ellis, O. E. Martinez Manzanera, F. Kanavati, A. Nair, J. Schnabel, B. Glocker
    http://arxiv.org/abs/2006.13798v1
    • [cs.LG]Befriending The Byzantines Through Reputation Scores
    Jayanth Regatti, Abhishek Gupta
    http://arxiv.org/abs/2006.13421v1
    • [cs.LG]Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework
    Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann
    http://arxiv.org/abs/2006.13365v1
    • [cs.LG]Classification Performance Metric for Imbalance Data Based on Recall and Selectivity Normalized in Class Labels
    Robert Burduk
    http://arxiv.org/abs/2006.13319v1
    • [cs.LG]Continuous Submodular Function Maximization
    Yatao Bian, Joachim M. Buhmann, Andreas Krause
    http://arxiv.org/abs/2006.13474v1
    • [cs.LG]Control-Aware Representations for Model-based Reinforcement Learning
    Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
    http://arxiv.org/abs/2006.13408v1
    • [cs.LG]Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning
    Johnathon Shook, Tryambak Gangopadhyay, Linjiang Wu, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh K. Singh
    http://arxiv.org/abs/2006.13847v1
    • [cs.LG]Defending against adversarial attacks on medical imaging AI system, classification or detection?
    Xin Li, Deng Pan, Dongxiao Zhu
    http://arxiv.org/abs/2006.13555v1
    • [cs.LG]Differentiable Window for Dynamic Local Attention
    Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, Xiaoli Li
    http://arxiv.org/abs/2006.13561v1
    • [cs.LG]Distributionally-Robust Machine Learning Using Locally Differentially-Private Data
    Farhad Farokhi
    http://arxiv.org/abs/2006.13488v1
    • [cs.LG]Dynamic of Stochastic Gradient Descent with State-Dependent Noise
    Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
    http://arxiv.org/abs/2006.13719v1
    • [cs.LG]Ensemble Kernel Methods, Implicit Regularization and Determinental Point Processes
    Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens
    http://arxiv.org/abs/2006.13701v1
    • [cs.LG]Fairness with Overlapping Groups
    Forest Yang, Moustapha Cisse, Sanmi Koyejo
    http://arxiv.org/abs/2006.13485v1
    • [cs.LG]Fairness without Demographics through Adversarially Reweighted Learning
    Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
    http://arxiv.org/abs/2006.13114v2
    • [cs.LG]Generative causal explanations of black-box classifiers
    Matthew O’Shaughnessy, Gregory Canal, Marissa Connor, Mark Davenport, Christopher Rozell
    http://arxiv.org/abs/2006.13913v1
    • [cs.LG]Graph Policy Network for Transferable Active Learning on Graphs
    Shengding Hu, Zheng Xiong, Meng Qu, Xingdi Yuan, Marc-Alexandre Côté, Zhiyuan Liu, Jian Tang
    http://arxiv.org/abs/2006.13463v1
    • [cs.LG]Hierarchically Local Tasks and Deep Convolutional Networks
    Arturo Deza, Qianli Liao, Andrzej Banburski, Tomaso Poggio
    http://arxiv.org/abs/2006.13915v1
    • [cs.LG]Hyperparameter Ensembles for Robustness and Uncertainty Quantification
    Florian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton
    http://arxiv.org/abs/2006.13570v1
    • [cs.LG]Lattice Representation Learning
    Luis A. Lastras
    http://arxiv.org/abs/2006.13833v1
    • [cs.LG]Learning Disentangled Representations of Video with Missing Data
    Armand Comas Massague, Chi Zhang, Zlatan Feric, Octavia Camps, Rose Yu
    http://arxiv.org/abs/2006.13391v1
    • [cs.LG]Learning Gradient Boosted Multi-label Classification Rules
    Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
    http://arxiv.org/abs/2006.13346v1
    • [cs.LG]Learning Potentials of Quantum Systems using Deep Neural Networks
    Arijit Sehanobish, Hector H. Corzo, Onur Kara, David van Dijk
    http://arxiv.org/abs/2006.13297v1
    • [cs.LG]Likelihood-Free Gaussian Process for Regression
    Yuta Shikuri
    http://arxiv.org/abs/2006.13456v1
    • [cs.LG]Local Stochastic Approximation: A Unified View of Federated Learning and Distributed Multi-Task Reinforcement Learning Algorithms
    Thinh T. Doan
    http://arxiv.org/abs/2006.13460v1
    • [cs.LG]Locally Masked Convolution for Autoregressive Models
    Ajay Jain, Pieter Abbeel, Deepak Pathak
    http://arxiv.org/abs/2006.12486v2
    • [cs.LG]Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks
    Weilin Cong, Rana Forsati, Mahmut Kandemir, Mehrdad Mahdavi
    http://arxiv.org/abs/2006.13866v1
    • [cs.LG]Non-Convex Structured Phase Retrieval
    Namrata Vaswani
    http://arxiv.org/abs/2006.13298v1
    • [cs.LG]Normalized Loss Functions for Deep Learning with Noisy Labels
    Xingjun Ma, Hanxun Huang, Yisen Wang, Simone Romano, Sarah Erfani, James Bailey
    http://arxiv.org/abs/2006.13554v1
    • [cs.LG]Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
    Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine
    http://arxiv.org/abs/2006.13916v1
    • [cs.LG]Off-the-grid: Fast and Effective Hyperparameter Search for Kernel Clustering
    Bruno Ordozgoiti, Lluís A. Belanche Muñoz
    http://arxiv.org/abs/2006.13567v1
    • [cs.LG]On Multivariate Singular Spectrum Analysis
    Anish Agarwal, Abdullah Alomar, Devavrat Shah
    http://arxiv.org/abs/2006.13448v1
    • [cs.LG]On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures
    Maxim Samarin, Volker Roth, David Belius
    http://arxiv.org/abs/2006.13645v1
    • [cs.LG]Online Competitive Influence Maximization
    Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C. S. Lui, Wei Chen
    http://arxiv.org/abs/2006.13411v1
    • [cs.LG]Online Dense Subgraph Discovery via Blurred-Graph Feedback
    Yuko Kuroki, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama
    http://arxiv.org/abs/2006.13642v1
    • [cs.LG]OvA-INN: Continual Learning with Invertible Neural Networks
    G. Hocquet, O. Bichler, D. Querlioz
    http://arxiv.org/abs/2006.13772v1
    • [cs.LG]Principal Component Networks: Parameter Reduction Early in Training
    Roger Waleffe, Theodoros Rekatsinas
    http://arxiv.org/abs/2006.13347v1
    • [cs.LG]Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds
    Yingxue Zhou, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Arindam Banerjee
    http://arxiv.org/abs/2006.13501v1
    • [cs.LG]Provably Convergent Working Set Algorithm for Non-Convex Regularized Regression
    Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, Joseph Salmon
    http://arxiv.org/abs/2006.13533v1
    • [cs.LG]Quantifying Differences in Reward Functions
    Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike
    http://arxiv.org/abs/2006.13900v1
    • [cs.LG]RL Unplugged: Benchmarks for Offline Reinforcement Learning
    Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas
    http://arxiv.org/abs/2006.13888v1
    • [cs.LG]Ramanujan Bipartite Graph Products for Efficient Block Sparse Neural Networks
    Dharma Teja Vooturi, Girish Varma, Kishore Kothapalli
    http://arxiv.org/abs/2006.13486v1
    • [cs.LG]Randomized Block-Diagonal Preconditioning for Parallel Learning
    Celestine Mendler-Dünner, Aurelien Lucchi
    http://arxiv.org/abs/2006.13591v1
    • [cs.LG]Reducing Overestimation Bias by Increasing Representation Dissimilarity in Ensemble Based Deep Q-Learning
    Hassam Ullah Sheikh, Ladislau Bölöni
    http://arxiv.org/abs/2006.13823v1
    • [cs.LG]Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
    Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang
    http://arxiv.org/abs/2006.11601v2
    • [cs.LG]Road Network Metric Learning for Estimated Time of Arrival
    Yiwen Sun, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye
    http://arxiv.org/abs/2006.13477v1
    • [cs.LG]Robust Domain Adaptation: Representations, Weights and Inductive Bias
    Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Céline Hudelot
    http://arxiv.org/abs/2006.13629v1
    • [cs.LG]Safe Learning under Uncertain Objectives and Constraints
    Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi, Hamed Hassani
    http://arxiv.org/abs/2006.13326v1
    • [cs.LG]Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations
    Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan
    http://arxiv.org/abs/2006.13476v1
    • [cs.LG]Spherical Perspective on Learning with Batch Norm
    Simon Roburin, Yann de Mont-Marin, Andrei Bursuc, Renaud Marlet, Patrick Pérez, Mathieu Aubry
    http://arxiv.org/abs/2006.13382v1
    • [cs.LG]Thalamocortical motor circuit insights for more robust hierarchical control of complex sequences
    Laureline Logiaco, G. Sean Escola
    http://arxiv.org/abs/2006.13332v1
    • [cs.LG]The NetHack Learning Environment
    Heinrich Küttler, Nantas Nardelli, Alexander H. Miller, Roberta Raileanu, Marco Selvatici, Edward Grefenstette, Tim Rocktäschel
    http://arxiv.org/abs/2006.13760v1
    • [cs.LG]Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes
    Yi Tian, Jian Qian, Suvrit Sra
    http://arxiv.org/abs/2006.13405v1
    • [cs.LG]Towards Understanding Hierarchical Learning: Benefits of Neural Representations
    Minshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher
    http://arxiv.org/abs/2006.13436v1
    • [cs.LG]Uncertainty in Neural Relational Inference Trajectory Reconstruction
    Vasileios Karavias, Ben Day, Pietro Liò
    http://arxiv.org/abs/2006.13666v1
    • [cs.LG]Understanding Deep Architectures with Reasoning Layer
    Xinshi Chen, Yufei Zhang, Christoph Reisinger, Le Song
    http://arxiv.org/abs/2006.13401v1
    • [cs.LG]When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
    Ziwei Guan, Tengyu Xu, Yingbin Liang
    http://arxiv.org/abs/2006.13506v1
    • [cs.LO]DeepAbstract: Neural Network Abstraction for Accelerating Verification
    Pranav Ashok, Vahid Hashemi, Jan Křetínský, Stefanie Mohr
    http://arxiv.org/abs/2006.13735v1
    • [cs.NE]Crossmodal Language Grounding in an Embodied Neurocognitive Model
    Stefan Heinrich, Yuan Yao, Tobias Hinz, Zhiyuan Liu, Thomas Hummel, Matthias Kerzel, Cornelius Weber, Stefan Wermter
    http://arxiv.org/abs/2006.13546v1
    • [cs.NE]hxtorch: PyTorch for BrainScaleS-2 — Perceptrons on Analog Neuromorphic Hardware
    Philipp Spilger, Eric Müller, Arne Emmel, Aron Leibfried, Christian Mauch, Christian Pehle, Johannes Weis, Oliver Breitwieser, Sebastian Billaudelle, Sebastian Schmitt, Timo C. Wunderlich, Yannik Stradmann, Johannes Schemmel
    http://arxiv.org/abs/2006.13138v2
    • [cs.RO]A Hierarchical Framework for Long-term and Robust Deployment of Field Ground Robots in Large-Scale Farming
    Stuart Eiffert, Nathan D. Wallace, He Kong, Navid Pirmarzdashti, Salah Sukkarieh
    http://arxiv.org/abs/2006.13413v1
    • [cs.RO]A Thermoplastic Elastomer Belt Based Robotic Gripper
    Xingwen Zheng, Ningzhe Hou, Pascal Johannes Daniel Dinjens, Ruifeng Wang, Chengyang Dong, Guangming Xie
    http://arxiv.org/abs/2006.13597v1
    • [cs.RO]Efficient Sampling-Based Maximum Entropy Inverse Reinforcement Learning with Application to Autonomous Driving
    Zheng Wu, Liting Sun, Wei Zhan, Chenyu Yang, Masayoshi Tomizuka
    http://arxiv.org/abs/2006.13704v1
    • [cs.RO]Evaluation of Sampling Methods for Robotic Sediment Sampling Systems
    Jun Han Bae, Wonse Jo, Jee Hwan Park, Richard M. Voyles, Sara K. McMillan, Byung-Cheol Min
    http://arxiv.org/abs/2006.13360v1
    • [cs.RO]GMMLoc: Structure Consistent Visual Localization with Gaussian Mixture Models
    Huaiyang Huang, Haoyang Ye, Yuxiang Sun, Ming Liu
    http://arxiv.org/abs/2006.13670v1
    • [cs.RO]Multi-modal Trajectory Optimization for Impact-aware Manipulation
    Theodoros Stouraitis, Lei Yan, João Moura, Michael Gienger, Sethu Vijayakumar
    http://arxiv.org/abs/2006.13374v1
    • [cs.RO]Namira Soccer 2D Simulation Team Description Paper 2020
    Ehsan Asali, Farzin Negahbani, Shahriyar Bamaei, Zahra Abbasi
    http://arxiv.org/abs/2006.13534v1
    • [cs.RO]Robot Object Retrieval with Contextual Natural Language Queries
    Thao Nguyen, Nakul Gopalan, Roma Patel, Matt Corsaro, Ellie Pavlick, Stefanie Tellex
    http://arxiv.org/abs/2006.13253v1
    • [cs.SD]Bach or Mock? A Grading Function for Chorales in the Style of J.S. Bach
    Alisa Liu, Alexander Fang, Prem Seetharaman, Bryan Pardo
    http://arxiv.org/abs/2006.13329v1
    • [cs.SD]Incorporating Music Knowledge in Continual Dataset Augmentation for Music Generation
    Alisa Liu, Alexander Fang, Gaëtan Hadjeres, Prem Seetharaman, Bryan pardo
    http://arxiv.org/abs/2006.13331v1
    • [cs.SI]Competitive Balance in Team Sports Games
    Sofia M Nikolakaki, Ogheneovo Dibie, Ahmad Beirami, Nicholas Peterson, Navid Aghdaie, Kazi Zaman
    http://arxiv.org/abs/2006.13763v1
    • [cs.SI]Movie Box office Prediction via Joint Actor Representations and Social Media Sentiment
    Dezhou Shen
    http://arxiv.org/abs/2006.13417v1
    • [cs.SI]Network connectivity under a probabilistic node failure model
    Lucia Cavallaro, Stefania Costantini, Pasquale De Meo, Antonio Liotta, Giovanni Stilo
    http://arxiv.org/abs/2006.13551v1
    • [cs.SI]On Analyzing Annotation Consistency in Online Abusive Behavior Datasets
    Md Rabiul Awal, Rui Cao, Roy Ka-Wei Lee, Sandra Mitrović
    http://arxiv.org/abs/2006.13507v1
    • [cs.SI]Provably and Efficiently Approximating Near-cliques using the Turán Shadow: PEANUTS
    Shweta Jain, C. Seshadhri
    http://arxiv.org/abs/2006.13483v1
    • [cs.SI]Quantifying the influence of inter-county mobility patterns on the COVID-19 outbreak in the United States
    Qianqian Sun, Yixuan Pan, Weiyi Zhou, Chenfeng Xiong, Lei Zhang
    http://arxiv.org/abs/2006.13860v1
    • [cs.SI]Wikipedia and Westminster: Quality and Dynamics of Wikipedia Pages about UK Politicians
    Pushkal Agarwal, Miriam Redi, Nishanth Sastry, Edward Wood, Andrew Blick
    http://arxiv.org/abs/2006.13400v1
    • [cs.SI]Winning the competition: enhancing counter-contagion in SIS-like epidemic processes
    Argyris Kalogeratos, Stefano Sarao Mannelli
    http://arxiv.org/abs/2006.13395v1
    • [eess.AS]Black-box Adaptation of ASR for Accented Speech
    Kartik Khandelwal, Preethi Jyothi, Abhijeet Awasthi, Sunita Sarawagi
    http://arxiv.org/abs/2006.13519v1
    • [eess.AS]Face-to-Music Translation Using a Distance-Preserving Generative Adversarial Network with an Auxiliary Discriminator
    Chelhwon Kim, Andrew Port, Mitesh Patel
    http://arxiv.org/abs/2006.13469v1
    • [eess.AS]Gamma Boltzmann Machine for Simultaneously Modeling Linear- and Log-amplitude Spectra
    Toru Nakashika, Kohei Yatabe
    http://arxiv.org/abs/2006.13590v1
    • [eess.IV]A Novel Approach for Correcting Multiple Discrete Rigid In-Plane Motions Artefacts in MRI Scans
    Michael Rotman, Rafi Brada, Israel Beniaminy, Sangtae Ahn, Christopher J. Hardy, Lior Wolf
    http://arxiv.org/abs/2006.13804v1
    • [eess.IV]Automated Detection of COVID-19 from CT Scans Using Convolutional Neural Networks
    Rohit Lokwani, Ashrika Gaikwad, Viraj Kulkarni, Aniruddha Pant, Amit Kharat
    http://arxiv.org/abs/2006.13212v1
    • [eess.IV]Deep Generative Model-based Quality Control for Cardiac MRI Segmentation
    Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai
    http://arxiv.org/abs/2006.13379v1
    • [eess.IV]Does Non-COVID19 Lung Lesion Help? Investigating Transferability in COVID-19 CT Image Segmentation
    Yixin Wang, Yao Zhang, Yang Liu, Jiang Tian, Cheng Zhong, Zhongchao Shi, Yang Zhang, Zhiqiang He
    http://arxiv.org/abs/2006.13877v1
    • [eess.IV]Feedback Graph Attention Convolutional Network for Medical Image Enhancement
    Xiaobin Hu, Yanyang Yan, Wenqi Ren, Hongwei Li, Yu Zhao, Amirhossein Bayat, Bjoern Menze
    http://arxiv.org/abs/2006.13863v1
    • [eess.IV]Flexible Image Denoising with Multi-layer Conditional Feature Modulation
    Jiazhi Du, Xin Qiao, Zifei Yan, Hongzhi Zhang, Wangmeng Zuo
    http://arxiv.org/abs/2006.13500v1
    • [eess.IV]GIFnets: Differentiable GIF Encoding Framework
    Innfarn Yoo, Xiyang Luo, Yilin Wang, Feng Yang, Peyman Milanfar
    http://arxiv.org/abs/2006.13434v1
    • [eess.IV]Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction
    Esther Puyol-Antón, Chen Chen, James R. Clough, Bram Ruijsink, Baldeep S. Sidhu, Justin Gould, Bradley Porter, Mark Elliott, Vishal Mehta, Daniel Rueckert, Christopher A. Rinaldi, Andrew P. King
    http://arxiv.org/abs/2006.13811v1
    • [eess.IV]Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model
    Ren Yang, Fabian Mentzer, Luc Van Gool, Radu Timofte
    http://arxiv.org/abs/2006.13560v1
    • [eess.IV]MRI Image Reconstruction via Learning Optimization using Neural ODEs
    Eric Z. Chen, Terrence Chen, Shanhui Sun
    http://arxiv.org/abs/2006.13825v1
    • [eess.IV]Malignancy-Aware Follow-Up Volume Prediction for Lung Nodules
    Yamin Li, Jiancheng Yang, Yi Xu, Jingwei Xu, Xiaodan Ye, Guangyu Tao, Xueqian Xie, Guixue Liu
    http://arxiv.org/abs/2006.13890v1
    • [eess.IV]Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials
    Tim Hsu, William K. Epting, Hokon Kim, Harry W. Abernathy, Gregory A. Hackett, Anthony D. Rollett, Paul A. Salvador, Elizabeth A. Holm
    http://arxiv.org/abs/2006.13886v1
    • [eess.IV]NINEPINS: Nuclei Instance Segmentation with Point Annotations
    Ting-An Yen, Hung-Chun Hsu, Pushpak Pati, Maria Gabrani, Antonio Foncubierta-Rodríguez, Pau-Choo Chung
    http://arxiv.org/abs/2006.13556v1
    • [eess.IV]Realistic Adversarial Data Augmentation for MR Image Segmentation
    Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang, Shuo Wang, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert
    http://arxiv.org/abs/2006.13322v1
    • [eess.IV]Stacked Convolutional Neural Network for Diagnosis of COVID-19 Disease from X-ray Images
    Mahesh Gour, Sweta Jain
    http://arxiv.org/abs/2006.13817v1
    • [eess.IV]Was there COVID-19 back in 2012? Challenge for AI in Diagnosis with Similar Indications
    Imon Banerjee, Priyanshu Sinha, Saptarshi Purkayastha, Nazanin Mashhaditafreshi, Amara Tariq, Jiwoong Jeong, Hari Trivedi, Judy W. Gichoya
    http://arxiv.org/abs/2006.13262v1
    • [eess.SP]Autonomous Interference Mapping for Industrial IoT Networks over Unlicensed Bands
    Simone Grimaldi, Aamir Mahmood, Syed Ali Hassan, Gerhard Petrus Hancke, Mikael Gidlund
    http://arxiv.org/abs/2006.13643v1
    • [eess.SP]Clustering and Power Optimization for NOMA Multi-Objective Problems
    Zijian Wang, Mylene Pischella, Luc Vandendorpe
    http://arxiv.org/abs/2006.13649v1
    • [eess.SP]Energy Minimization in UAV-Aided Networks: Actor-Critic Learning for Constrained Scheduling Optimization
    Yaxiong Yuan, Lei Lei, Thang Xuan Vu, Symeon Chatzinotas, Sumei Sun, Bjorn Ottersten
    http://arxiv.org/abs/2006.13610v1
    • [eess.SP]JCR70: A Low-Complexity Millimeter-Wave Proof-of-Concept Platform for A Fully-Digital MIMO Joint Communication-Radar
    Preeti Kumari, Amine Mezghani, Robert W. Heath, Jr
    http://arxiv.org/abs/2006.13344v1
    • [eess.SP]Traffic congestion anomaly detection and prediction using deep learning
    Adriana-Simona Mihaita, Haowen Li, Marian-Andrei Rizoiu
    http://arxiv.org/abs/2006.13215v1
    • [eess.SY]Learning-to-Fly: Learning-based Collision Avoidance for Scalable Urban Air Mobility
    Alëna Rodionova, Yash Vardhan Pant, Kuk Jang, Houssam Abbas, Rahul Mangharam
    http://arxiv.org/abs/2006.13267v1
    • [math-ph]Exact variance of von Neumann entanglement entropy over the Bures-Hall measure
    Lu Wei
    http://arxiv.org/abs/2006.13746v1
    • [math.OC]Unified Reinforcement Q-Learning for Mean Field Game and Control Problems
    Andrea Angiuli, Jean-Pierre Fouque, Mathieu Laurière
    http://arxiv.org/abs/2006.13912v1
    • [math.ST]A Mean-Field Theory for Learning the Schönberg Measure of Radial Basis Functions
    Masoud Badiei Khuzani, Yinyu Ye, Sandy Napel, Lei Xing
    http://arxiv.org/abs/2006.13330v1
    • [math.ST]Gromov-Wasserstein Distance based Object Matching: Asymptotic Inference
    Christoph Alexander Weitkamp, Katharina Proksch, Carla Tameling, Axel Munk
    http://arxiv.org/abs/2006.12287v3
    • [math.ST]On the relationship between beta-Bartlett and Uhlig extended processes
    Víctor Peña, Kaoru Irie
    http://arxiv.org/abs/2006.13868v1
    • [math.ST]Second order asymptotic efficiency for a Poisson process
    Samvel Gasparyan
    http://arxiv.org/abs/2006.13516v1
    • [physics.soc-ph]A critique of the Mean Field Approximation in preferential attachment networks
    Matthijs Ruijgrok
    http://arxiv.org/abs/2006.13295v1
    • [physics.soc-ph]From form to information: Analysing built environments in different spatial cultures
    Vinicius M. Netto, Edgardo Brigatti, Caio Cacholas
    http://arxiv.org/abs/2006.13897v1
    • [physics.soc-ph]Quantifying Policy Responses to a Global Emergency: Insights from the COVID-19 Pandemic
    Jian Gao, Yian Yin, Benjamin F. Jones, Dashun Wang
    http://arxiv.org/abs/2006.13853v1
    • [q-bio.TO]Deep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primary
    Ming Y. Lu, Melissa Zhao, Maha Shady, Jana Lipkova, Tiffany Y. Chen, Drew F. K. Williamson, Faisal Mahmood
    http://arxiv.org/abs/2006.13932v1
    • [quant-ph]Uniqueness and Optimality of Dynamical Extensions of Divergences
    Gilad Gour
    http://arxiv.org/abs/2006.13340v1
    • [stat.AP]Diagnosis Prevalence vs. Efficacy in Machine-learning Based Diagnostic Decision Support
    Gil Alon, Elizabeth Chen, Guergana Savova, Carsten Eickhoff
    http://arxiv.org/abs/2006.13737v1
    • [stat.AP]Discrete distributions from a Markov chain
    Rose Baker
    http://arxiv.org/abs/2006.13766v1
    • [stat.AP]Dynamic Population Estimation Using Anonymized Mobility Data
    Xiang Liu, Philo Pöllmann
    http://arxiv.org/abs/2006.13786v1
    • [stat.AP]Spatial Pattern Recognition with Adjacency-Clustering: Improved Diagnostics for Semiconductor Wafer Bin Maps
    Ahmed Aziz Ezzat, Sheng Liu, Dorit S. Hochbaum, Yu Ding
    http://arxiv.org/abs/2006.13824v1
    • [stat.AP]Using social contact data to improve the overall effect estimate of a cluster-randomized influenza vaccination program in Senega
    Gail E. Potter, Nicole Bohme Carnegie, Jonathan D. Sugimoto, Aldiouma Diallo, John C. Victor, Kathleen Neuzil, M. Elizabeth Halloran
    http://arxiv.org/abs/2006.13455v1
    • [stat.CO]Fast computation of latent correlations
    Grace Yoon, Christian L. Müller, Irina Gaynanova
    http://arxiv.org/abs/2006.13875v1
    • [stat.CO]The Boomerang Sampler
    Joris Bierkens, Sebastiano Grazzi, Kengo Kamatani, Gareth Roberts
    http://arxiv.org/abs/2006.13777v1
    • [stat.ME]A Fast and Efficient Change-point Detection Framework for Modern Data
    Yi-Wei Liu, Hao Chen
    http://arxiv.org/abs/2006.13450v1
    • [stat.ME]A Robust Consistent Information Criterion for Model Selection based on Empirical Likelihood
    Chixiang Chen, Ming Wang, Rongling Wu, Runze Li
    http://arxiv.org/abs/2006.13281v1
    • [stat.ME]Bayesian Shrinkage for Functional Network Models with Intractable Normalizing Constants
    Jaewoo Park, Yeseul Jeon, Minsuk Shin, Minjeong Jeon, Ick Hoon Jin
    http://arxiv.org/abs/2006.13698v1
    • [stat.ME]Break Point Detection for Functional Covariance
    Shuhao Jiao, Ron D. Frostig, Hernando Ombao
    http://arxiv.org/abs/2006.13887v1
    • [stat.ME]Global Sensitivity and Domain-Selective Testing for Functional-Valued Responses: An Application to Climate Economy Models
    Matteo Fontana, Massimo Tavoni, Simone Vantini
    http://arxiv.org/abs/2006.13850v1
    • [stat.ME]Inference in Stochastic Epidemic Models via Multinomial Approximations
    Nick Whiteley, Lorenzo Rimella
    http://arxiv.org/abs/2006.13700v1
    • [stat.ME]Min-Mid-Max Scaling, Limits of Agreement, and Agreement Score
    Veli Safak
    http://arxiv.org/abs/2006.12904v2
    • [stat.ME]Sequential Gibbs Sampling Algorithm for Cognitive Diagnosis Models with Many Attributes
    Juntao Wang, Ningzhong Shi, Xue Zhang, Gongjun Xu
    http://arxiv.org/abs/2006.13790v1
    • [stat.ME]Unified Principal Component Analysis for Sparse and Dense Functional Data under Spatial Dependency
    Haozhe Zhang, Yehua Li
    http://arxiv.org/abs/2006.13489v1
    • [stat.ME]Uniform convergence of local Fréchet regression and time warping for metric-space-valued trajectories
    Yaqing Chen, Hans-Georg Müller
    http://arxiv.org/abs/2006.13548v1
    • [stat.ML]A General Class of Transfer Learning Regression without Implementation Cost
    Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida
    http://arxiv.org/abs/2006.13228v1
    • [stat.ML]Design and Evaluation of Personalized Free Trials
    Hema Yoganarasimhan, Ebrahim Barzegary, Abhishek Pani
    http://arxiv.org/abs/2006.13420v1
    • [stat.ML]Distribution-Based Invariant Deep Networks for Learning Meta-Features
    Gwendoline De Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michèle Sebag
    http://arxiv.org/abs/2006.13708v1
    • [stat.ML]Non-Parametric Graph Learning for Bayesian Graph Neural Networks
    Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates
    http://arxiv.org/abs/2006.13335v1
    • [stat.ML]Simple and Scalable Parallelized Bayesian Optimization
    Masahiro Nomura
    http://arxiv.org/abs/2006.13600v1
    • [stat.ML]Slice Sampling for General Completely Random Measures
    Peiyuan Zhu, Alexandre Bouchard-Côté, Trevor Campbell
    http://arxiv.org/abs/2006.13925v1
    • [stat.ML]When Do Neural Networks Outperform Kernel Methods?
    Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
    http://arxiv.org/abs/2006.13409v1