cs.AI - 人工智能

    cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.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 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.NA - 数值分析 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-bio.GN - 基因组学 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]A new direction to promote the implementation of artificial intelligence in natural clinical settings
    • [cs.AI]ArCo: the Italian Cultural Heritage Knowledge Graph
    • [cs.AI]Cyber-All-Intel: An AI for Security related Threat Intelligence
    • [cs.CL]Automatic Inference of Minimalist Grammars using an SMT-Solver
    • [cs.CL]Distributional Semantics and Linguistic Theory
    • [cs.CL]Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances
    • [cs.CL]MASS: Masked Sequence to Sequence Pre-training for Language Generation
    • [cs.CL]On the Feasibility of Automated Detection of Allusive Text Reuse
    • [cs.CL]RWTH ASR Systems for LibriSpeech: Hybrid vs Attention - w/o Data Augmentation
    • [cs.CL]ShapeGlot: Learning Language for Shape Differentiation
    • [cs.CL]Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations
    • [cs.CL]Unified Language Model Pre-training for Natural Language Understanding and Generation
    • [cs.CR]Convolutional Neural Network for Intrusion Detection System In Cyber Physical Systems
    • [cs.CR]From Sicilian mafia to Chinese “scam villages”
    • [cs.CR]The Art of Social Bots: A Review and a Refined Taxonomy
    • [cs.CV]A Genetic Algorithm Enabled Similarity-Based Attack on Cancellable Biometrics
    • [cs.CV]Algorithms for Grey-Weighted Distance Computations
    • [cs.CV]Automatic Video Colorization using 3D Conditional Generative Adversarial Networks
    • [cs.CV]Capture, Learning, and Synthesis of 3D Speaking Styles
    • [cs.CV]Convolutional Mesh Regression for Single-Image Human Shape Reconstruction
    • [cs.CV]Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence
    • [cs.CV]Deep Flow-Guided Video Inpainting
    • [cs.CV]DeepSWIR: A Deep Learning Based Approach for the Synthesis of Short-Wave InfraRed Band using Multi-Sensor Concurrent Datasets
    • [cs.CV]End-to-End Wireframe Parsing
    • [cs.CV]Endoscopy artifact detection (EAD 2019) challenge dataset
    • [cs.CV]FANTrack: 3D Multi-Object Tracking with Feature Association Network
    • [cs.CV]Frame-Recurrent Video Inpainting by Robust Optical Flow Inference
    • [cs.CV]Generalization ability of region proposal networks for multispectral person detection
    • [cs.CV]Goal-oriented Object Importance Estimation in On-road Driving Videos
    • [cs.CV]Interpretation of Feature Space using Multi-Channel Attentional Sub-Networks
    • [cs.CV]Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single Image
    • [cs.CV]Learning Cascaded Siamese Networks for High Performance Visual Tracking
    • [cs.CV]LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking
    • [cs.CV]Multi-task human analysis in still images: 2D/3D pose, depth map, and multi-part segmentation
    • [cs.CV]Multimodal Semantic Attention Network for Video Captioning
    • [cs.CV]Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation
    • [cs.CV]Oriented Point Sampling for Plane Detection in Unorganized Point Clouds
    • [cs.CV]Photometric Transformer Networks and Label Adjustment for Breast Density Prediction
    • [cs.CV]Robust Dense Mapping for Large-Scale Dynamic Environments
    • [cs.CV]Skin Lesion Classification Using CNNs with Patch-Based Attention and Diagnosis-Guided Loss Weighting
    • [cs.CV]Thinking Outside the Box: Generation of Unconstrained 3D Room Layouts
    • [cs.CV]Training a Fast Object Detector for LiDAR Range Images Using Labeled Data from Sensors with Higher Resolution
    • [cs.CV]Uncertainty Modeling of Contextual-Connection between Tracklets for Unconstrained Video-based Face Recognition
    • [cs.CV]Unsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial Images
    • [cs.CY]Redesigning Telecommunication Engineering Courses with CDIO geared for Polytechnic Education
    • [cs.DB]Atomic Commitment Across Blockchains
    • [cs.DC]Brief Announcement: Does Preprocessing Help under Congestion?
    • [cs.DC]Implementing Efficient Message Logging Protocols as MPI Application Extensions
    • [cs.DC]P3DFFT: a framework for parallel computations of Fourier transforms in three dimensions
    • [cs.DC]Parallel and Distributed Algorithms for the housing allocation Problem
    • [cs.DS]Network Coding Gaps for Completion Times of Multiple Unicasts
    • [cs.IR]Deep Landscape Forecasting for Real-time Bidding Advertising
    • [cs.IR]FAQ Retrieval using Query-Question Similarity and BERT-Based Query-Answer Relevance
    • [cs.IT]A Two-Stage Beam Alignment Framework for Hybrid MmWave Distributed Antenna Systems
    • [cs.IT]Adaptive Causal Network Coding with Feedback for Delay and Throughput Guarantees
    • [cs.IT]An Entropy Power Inequality for Discrete Random Variables
    • [cs.IT]Code Design Principles for Ultra-Reliable Random Access with Preassigned Patterns
    • [cs.IT]Deep Reinforcement Learning for Minimizing Age-of-Information in UAV-assisted Networks
    • [cs.IT]Multi-target Detection with an Arbitrary Spacing Distribution
    • [cs.IT]On Timely Channel Coding with Hybrid ARQ
    • [cs.IT]On recoverability of finite traces of square-summable sequences
    • [cs.IT]Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learning
    • [cs.IT]The Method of Conditional Expectations for Cubic Metric Reduction in OFDM
    • [cs.IT]Virtual Cell Clustering with Optimal Resource Allocation to Maximize Cellular System Capacity
    • [cs.LG]Accelerated Target Updates for Q-learning
    • [cs.LG]Adaptive image-feature learning for disease classification using inductive graph networks
    • [cs.LG]Adversarial Variational Embedding for Robust Semi-supervised Learning
    • [cs.LG]Batch-Size Independent Regret Bounds for the Combinatorial Multi-Armed Bandit Problem
    • [cs.LG]Collaborative and Privacy-Preserving Machine Teaching via Consensus Optimization
    • [cs.LG]Does Data Augmentation Lead to Positive Margin?
    • [cs.LG]Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review
    • [cs.LG]Forest Representation Learning Guided by Margin Distribution
    • [cs.LG]Generalized Dilation Neural Networks
    • [cs.LG]Generative Model with Dynamic Linear Flow
    • [cs.LG]Meta-learning of Sequential Strategies
    • [cs.LG]MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records
    • [cs.LG]Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets
    • [cs.LG]PiNet: A Permutation Invariant Graph Neural Network for Graph Classification
    • [cs.LG]Robust Federated Training via Collaborative Machine Teaching using Trusted Instances
    • [cs.LG]SAdam: A Variant of Adam for Strongly Convex Functions
    • [cs.LG]Smoothing Policies and Safe Policy Gradients
    • [cs.LG]Toybox: A Suite of Environments for Experimental Evaluation of Deep Reinforcement Learning
    • [cs.LG]Uncertainty-Aware Data Aggregation for Deep Imitation Learning
    • [cs.LG]Understanding attention in graph neural networks
    • [cs.LG]Unsupervised Learning through Temporal Smoothing and Entropy Maximization
    • [cs.NE]Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis
    • [cs.NE]Fast-DENSER++: Evolving Fully-Trained Deep Artificial Neural Networks
    • [cs.NE]Optimal Randomness in Swarm-based Search
    • [cs.NI]Locality-Sensitive Sketching for Resilient Network Flow Monitoring
    • [cs.RO]Adaptive neural network based dynamic surface control for uncertain dual arm robots
    • [cs.RO]Anytime Multi-arm Task and Motion Planning for Pick-and-Place of Individual Objects via Handoffs
    • [cs.RO]Bayesian Optimization for Polynomial Time Probabilistically Complete STL Trajectory Synthesis
    • [cs.RO]Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving
    • [cs.RO]Configuration-Space Flipper Planning for Rescue Robots
    • [cs.RO]LiStereo: Generate Dense Depth Maps from LIDAR and Stereo Imagery
    • [cs.SI]A hybrid recommendation algorithm based on weighted stochastic block model
    • [cs.SI]Displaying Things in Common to Encourage Friendship Formation: A Large Randomized Field Experiment
    • [cs.SI]Multi-class Twitter Data Categorization and Geocoding with a Novel Computing Framework
    • [cs.SI]Quantifying Triadic Closure in Multi-Edge Social Networks
    • [eess.IV]3d-SMRnet: Achieving a new quality of MPI system matrix recovery by deep learning
    • [eess.IV]Convolutional Neural Networks Considering Local and Global features for Image Enhancement
    • [eess.IV]Fast online 3D reconstruction of dynamic scenes from individual single-photon detection events
    • [eess.SP]A Hardware-Oriented and Memory-Efficient Method for CTC Decoding
    • [eess.SP]A Multistage Method for SCMA Codebook Design Based on MDS Codes
    • [eess.SP]Sparse multiresolution representations with adaptive kernels
    • [math.NA]Variational training of neural network approximations of solution maps for physical models
    • [math.ST]Bounding distributional errors via density ratios
    • [math.ST]Exact Largest Eigenvalue Distribution for Doubly Singular Beta Ensemble
    • [math.ST]Minimax Hausdorff estimation of density level sets
    • [math.ST]Sliced Latin hypercube designs with arbitrary run sizes
    • [physics.comp-ph]Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems
    • [physics.soc-ph]What do we see when we look at networks
    • [q-bio.GN]Somatic mutations render human exome and pathogen DNA more similar
    • [stat.ME]Conformalized Quantile Regression
    • [stat.ME]Consistent Fixed-Effects Selection in Ultra-high dimensional Linear Mixed Models with Error-Covariate Endogeneity
    • [stat.ME]Decision Making with Machine Learning and ROC Curves
    • [stat.ME]Predictive inference with the jackknife+
    • [stat.ME]Robust regression based on shrinkage estimators
    • [stat.ML]A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks
    • [stat.ML]Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up

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    • [cs.AI]A new direction to promote the implementation of artificial intelligence in natural clinical settings
    Yunyou Huang, Zhifei Zhang, Nana Wang, Nengquan Li, Mengjia Du, Tianshu Hao, Jianfeng Zhan
    http://arxiv.org/abs/1905.02940v1

    • [cs.AI]ArCo: the Italian Cultural Heritage Knowledge Graph
    Valentina Anita Carriero, Aldo Gangemi, Maria Letizia Mancinelli, Ludovica Marinucci, Andrea Giovanni Nuzzolese, Valentina Presutti, Chiara Veninata
    http://arxiv.org/abs/1905.02840v1

    • [cs.AI]Cyber-All-Intel: An AI for Security related Threat Intelligence
    Sudip Mittal, Anupam Joshi, Tim Finin
    http://arxiv.org/abs/1905.02895v1

    • [cs.CL]Automatic Inference of Minimalist Grammars using an SMT-Solver
    Sagar Indurkhya
    http://arxiv.org/abs/1905.02869v1

    • [cs.CL]Distributional Semantics and Linguistic Theory
    Gemma Boleda
    http://arxiv.org/abs/1905.01896v2

    • [cs.CL]Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances
    Soujanya Poria, Navonil Majumder, Rada Mihalcea, Eduard Hovy
    http://arxiv.org/abs/1905.02947v1

    • [cs.CL]MASS: Masked Sequence to Sequence Pre-training for Language Generation
    Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu
    http://arxiv.org/abs/1905.02450v2

    • [cs.CL]On the Feasibility of Automated Detection of Allusive Text Reuse
    Enrique Manjavacas, Brian Long, Mike Kestemont
    http://arxiv.org/abs/1905.02973v1

    • [cs.CL]RWTH ASR Systems for LibriSpeech: Hybrid vs Attention - w/o Data Augmentation
    Christoph Lüscher, Eugen Beck, Kazuki Irie, Markus Kitza, Wilfried Michel, Albert Zeyer, Ralf Schlüter, Hermann Ney
    http://arxiv.org/abs/1905.03072v1

    • [cs.CL]ShapeGlot: Learning Language for Shape Differentiation
    Panos Achlioptas, Judy Fan, Robert X. D. Hawkins, Noah D. Goodman, Leonidas J. Guibas
    http://arxiv.org/abs/1905.02925v1

    • [cs.CL]Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations
    Meishan Zhang, Zhenghua Li, Guohong Fu, Min Zhang
    http://arxiv.org/abs/1905.02878v1

    • [cs.CL]Unified Language Model Pre-training for Natural Language Understanding and Generation
    Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, Hsiao-Wuen Hon
    http://arxiv.org/abs/1905.03197v1

    • [cs.CR]Convolutional Neural Network for Intrusion Detection System In Cyber Physical Systems
    Gael Kamdem De Teyou, Junior Ziazet
    http://arxiv.org/abs/1905.03168v1

    • [cs.CR]From Sicilian mafia to Chinese “scam villages”
    Jeff Yan
    http://arxiv.org/abs/1905.03108v1

    • [cs.CR]The Art of Social Bots: A Review and a Refined Taxonomy
    Majd Latah
    http://arxiv.org/abs/1905.03240v1

    • [cs.CV]A Genetic Algorithm Enabled Similarity-Based Attack on Cancellable Biometrics
    Xingbo Dong, Zhe Jin, Andrew Teoh Beng Jin
    http://arxiv.org/abs/1905.03021v1

    • [cs.CV]Algorithms for Grey-Weighted Distance Computations
    Magnus Gedda
    http://arxiv.org/abs/1905.03017v1

    • [cs.CV]Automatic Video Colorization using 3D Conditional Generative Adversarial Networks
    Panagiotis Kouzouglidis, Giorgos Sfikas, Christophoros Nikou
    http://arxiv.org/abs/1905.03023v1

    • [cs.CV]Capture, Learning, and Synthesis of 3D Speaking Styles
    Daniel Cudeiro, Timo Bolkart, Cassidy Laidlaw, Anurag Ranjan, Michael J. Black
    http://arxiv.org/abs/1905.03079v1

    • [cs.CV]Convolutional Mesh Regression for Single-Image Human Shape Reconstruction
    Nikos Kolotouros, Georgios Pavlakos, Kostas Daniilidis
    http://arxiv.org/abs/1905.03244v1

    • [cs.CV]Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence
    Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon
    http://arxiv.org/abs/1905.02949v1

    • [cs.CV]Deep Flow-Guided Video Inpainting
    Rui Xu, Xiaoxiao Li, Bolei Zhou, Chen Change Loy
    http://arxiv.org/abs/1905.02884v1

    • [cs.CV]DeepSWIR: A Deep Learning Based Approach for the Synthesis of Short-Wave InfraRed Band using Multi-Sensor Concurrent Datasets
    Litu Rout, Yatharath Bhateja, Ankur Garg, Indranil Mishra, S Manthira Moorthi, Debjyoti Dhar
    http://arxiv.org/abs/1905.02749v1

    • [cs.CV]End-to-End Wireframe Parsing
    Yichao Zhou, Haozhi Qi, Yi Ma
    http://arxiv.org/abs/1905.03246v1

    • [cs.CV]Endoscopy artifact detection (EAD 2019) challenge dataset
    Sharib Ali, Felix Zhou, Christian Daul, Barbara Braden, Adam Bailey, Stefano Realdon, James East, Georges Wagnières, Victor Loschenov, Enrico Grisan, Walter Blondel, Jens Rittscher
    http://arxiv.org/abs/1905.03209v1

    • [cs.CV]FANTrack: 3D Multi-Object Tracking with Feature Association Network
    Erkan Baser, Venkateshwaran Balasubramanian, Prarthana Bhattacharyya, Krzysztof Czarnecki
    http://arxiv.org/abs/1905.02843v1

    • [cs.CV]Frame-Recurrent Video Inpainting by Robust Optical Flow Inference
    Yifan Ding, Chuan Wang, Haibin Huang, Jiaming Liu, Jue Wang, Liqiang Wang
    http://arxiv.org/abs/1905.02882v1

    • [cs.CV]Generalization ability of region proposal networks for multispectral person detection
    Kevin Fritz, Daniel König, Ulrich Klauck, Michael Teutsch
    http://arxiv.org/abs/1905.02758v1

    • [cs.CV]Goal-oriented Object Importance Estimation in On-road Driving Videos
    Mingfei Gao, Ashish Tawari, Sujitha Martin
    http://arxiv.org/abs/1905.02848v1

    • [cs.CV]Interpretation of Feature Space using Multi-Channel Attentional Sub-Networks
    Masanari Kimura, Masayuki Tanaka
    http://arxiv.org/abs/1905.02719v1

    • [cs.CV]Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single Image
    Zhengqin Li, Mohammad Shafiei, Ravi Ramamoorthi, Kalyan Sunkavalli, Manmohan Chandraker
    http://arxiv.org/abs/1905.02722v1

    • [cs.CV]Learning Cascaded Siamese Networks for High Performance Visual Tracking
    Peng Gao, Yipeng Ma, Ruyue Yuan, Liyi Xiao, Fei Wang
    http://arxiv.org/abs/1905.02857v1

    • [cs.CV]LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking
    Guanghan Ning, Heng Huang
    http://arxiv.org/abs/1905.02822v1

    • [cs.CV]Multi-task human analysis in still images: 2D/3D pose, depth map, and multi-part segmentation
    Daniel Sánchez, Marc Oliu, Meysam Madadi, Xavier Baró, Sergio Escalera
    http://arxiv.org/abs/1905.03003v1

    • [cs.CV]Multimodal Semantic Attention Network for Video Captioning
    Liang Sun, Bing Li, Chunfeng Yuan, Zhengjun Zha, Weiming Hu
    http://arxiv.org/abs/1905.02963v1

    • [cs.CV]Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation
    Giorgos Bouritsas, Sergiy Bokhnyak, Michael Bronstein, Stefanos Zafeiriou
    http://arxiv.org/abs/1905.02876v1

    • [cs.CV]Oriented Point Sampling for Plane Detection in Unorganized Point Clouds
    Bo Sun, Philippos Mordohai
    http://arxiv.org/abs/1905.02553v1

    • [cs.CV]Photometric Transformer Networks and Label Adjustment for Breast Density Prediction
    Jaehwan Lee, Donggeon Yoo, Jung Yin Huh, Hyo-Eun Kim
    http://arxiv.org/abs/1905.02906v1

    • [cs.CV]Robust Dense Mapping for Large-Scale Dynamic Environments
    Ioan Andrei Bârsan, Peidong Liu, Marc Pollefeys, Andreas Geiger
    http://arxiv.org/abs/1905.02781v1

    • [cs.CV]Skin Lesion Classification Using CNNs with Patch-Based Attention and Diagnosis-Guided Loss Weighting
    Nils Gessert, Thilo Sentker, Frederic Madesta, Rüdiger Schmitz, Helge Kniep, Ivo Baltruschat, René Werner
    http://arxiv.org/abs/1905.02793v1

    • [cs.CV]Thinking Outside the Box: Generation of Unconstrained 3D Room Layouts
    Henry Howard-Jenkins, Shuda Li, Victor Prisacariu
    http://arxiv.org/abs/1905.03105v1

    • [cs.CV]Training a Fast Object Detector for LiDAR Range Images Using Labeled Data from Sensors with Higher Resolution
    Manuel Herzog, Klaus Dietmayer
    http://arxiv.org/abs/1905.03066v1

    • [cs.CV]Uncertainty Modeling of Contextual-Connection between Tracklets for Unconstrained Video-based Face Recognition
    Jingxiao Zheng, Ruichi Yu, Jun-Cheng Chen, Boyu Lu, Carlos D. Castillo, Rama Chellappa
    http://arxiv.org/abs/1905.02756v1

    • [cs.CV]Unsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial Images
    Bilel Benjdira, Yakoub Bazi, Anis Koubaa, Kais Ouni
    http://arxiv.org/abs/1905.03198v1

    • [cs.CY]Redesigning Telecommunication Engineering Courses with CDIO geared for Polytechnic Education
    Mouhamed Abdulla, Zohreh Motamedi, Amjed Majeed
    http://arxiv.org/abs/1905.02951v1

    • [cs.DB]Atomic Commitment Across Blockchains
    Victor Zakhary, Divyakant Agrawal, Amr El Abbadi
    http://arxiv.org/abs/1905.02847v1

    • [cs.DC]Brief Announcement: Does Preprocessing Help under Congestion?
    Klaus-Tycho Foerster, Janne H. Korhonen, Joel Rybicki, Stefan Schmid
    http://arxiv.org/abs/1905.03012v1

    • [cs.DC]Implementing Efficient Message Logging Protocols as MPI Application Extensions
    Kiril Dichev, Dimitrios S. Nikolopoulos
    http://arxiv.org/abs/1905.03184v1

    • [cs.DC]P3DFFT: a framework for parallel computations of Fourier transforms in three dimensions
    Dmitry Pekurovsky
    http://arxiv.org/abs/1905.02803v1

    • [cs.DC]Parallel and Distributed Algorithms for the housing allocation Problem
    Xiong Zheng, Vijay Garg
    http://arxiv.org/abs/1905.03111v1

    • [cs.DS]Network Coding Gaps for Completion Times of Multiple Unicasts
    Bernhard Haeupler, David Wajc, Goran Zuzic
    http://arxiv.org/abs/1905.02805v1

    • [cs.IR]Deep Landscape Forecasting for Real-time Bidding Advertising
    Kan Ren, Jiarui Qin, Lei Zheng, Weinan Zhang, Yong Yu
    http://arxiv.org/abs/1905.03028v1

    • [cs.IR]FAQ Retrieval using Query-Question Similarity and BERT-Based Query-Answer Relevance
    Wataru Sakata, Tomohide Shibata, Ribeka Tanaka, Sadao Kurohashi
    http://arxiv.org/abs/1905.02851v1

    • [cs.IT]A Two-Stage Beam Alignment Framework for Hybrid MmWave Distributed Antenna Systems
    Zhiqiang Wei, Min Qiu, Derrick Wing Kwan Ng, Jinhong Yuan
    http://arxiv.org/abs/1905.02955v1

    • [cs.IT]Adaptive Causal Network Coding with Feedback for Delay and Throughput Guarantees
    Alejandro Cohen, Derya Malak, Vered Bar Bracha, Muriel Medard
    http://arxiv.org/abs/1905.02870v1

    • [cs.IT]An Entropy Power Inequality for Discrete Random Variables
    Ehsan Nekouei, Mikael Skoglund, Karl Henrik Johansson
    http://arxiv.org/abs/1905.03015v1

    • [cs.IT]Code Design Principles for Ultra-Reliable Random Access with Preassigned Patterns
    Christopher Boyd, Roope Vehkalahti, Olav Tirkkonen, Antti Laaksonen
    http://arxiv.org/abs/1905.02761v1

    • [cs.IT]Deep Reinforcement Learning for Minimizing Age-of-Information in UAV-assisted Networks
    Mohamed A. Abd-Elmagid, Aidin Ferdowsi, Harpreet S. Dhillon, Walid Saad
    http://arxiv.org/abs/1905.02993v1

    • [cs.IT]Multi-target Detection with an Arbitrary Spacing Distribution
    Ti-Yen Lan, Tamir Bendory, Nicolas Boumal, Amit Singer
    http://arxiv.org/abs/1905.03176v1

    • [cs.IT]On Timely Channel Coding with Hybrid ARQ
    Ahmed Arafa, Karim Banawan, Karim G. Seddik, H. Vincent Poor
    http://arxiv.org/abs/1905.03238v1

    • [cs.IT]On recoverability of finite traces of square-summable sequences
    Nikolai Dokuchaev
    http://arxiv.org/abs/1905.02905v1

    • [cs.IT]Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learning
    Le Liang, Hao Ye, Geoffrey Ye Li
    http://arxiv.org/abs/1905.02910v1

    • [cs.IT]The Method of Conditional Expectations for Cubic Metric Reduction in OFDM
    Saeed Afrasiabi-Gorgani, Gerhard Wunder
    http://arxiv.org/abs/1905.03019v1

    • [cs.IT]Virtual Cell Clustering with Optimal Resource Allocation to Maximize Cellular System Capacity
    Michal Yemini, Andrea J. Goldsmith
    http://arxiv.org/abs/1905.02891v1

    • [cs.LG]Accelerated Target Updates for Q-learning
    Bowen Weng, Huaqing Xiong, Wei Zhang
    http://arxiv.org/abs/1905.02841v1

    • [cs.LG]Adaptive image-feature learning for disease classification using inductive graph networks
    Hendrik Burwinkel, Anees Kazi, Gerome Vivar, Shadi Albarqouni, Guillaume Zahnd, Nassir Navab, Seyed-Ahmad Ahmadi
    http://arxiv.org/abs/1905.03036v1

    • [cs.LG]Adversarial Variational Embedding for Robust Semi-supervised Learning
    Xiang Zhang, Lina Yao, Feng Yuan
    http://arxiv.org/abs/1905.02361v2

    • [cs.LG]Batch-Size Independent Regret Bounds for the Combinatorial Multi-Armed Bandit Problem
    Nadav Merlis, Shie Mannor
    http://arxiv.org/abs/1905.03125v1

    • [cs.LG]Collaborative and Privacy-Preserving Machine Teaching via Consensus Optimization
    Yufei Han, Yuzhe Ma, Christopher Gates, Kevin Roundy, Yun Shen
    http://arxiv.org/abs/1905.02796v1

    • [cs.LG]Does Data Augmentation Lead to Positive Margin?
    Shashank Rajput, Zhili Feng, Zachary Charles, Po-Ling Loh, Dimitris Papailiopoulos
    http://arxiv.org/abs/1905.03177v1

    • [cs.LG]Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review
    Benyamin Ghojogh, Maria N. Samad, Sayema Asif Mashhadi, Tania Kapoor, Wahab Ali, Fakhri Karray, Mark Crowley
    http://arxiv.org/abs/1905.02845v1

    • [cs.LG]Forest Representation Learning Guided by Margin Distribution
    Shen-Huan Lv, Liang Yang, Zhi-Hua Zhou
    http://arxiv.org/abs/1905.03052v1

    • [cs.LG]Generalized Dilation Neural Networks
    Gavneet Singh Chadha, Jan Niclas Reimann, Andreas Schwung
    http://arxiv.org/abs/1905.02961v1

    • [cs.LG]Generative Model with Dynamic Linear Flow
    Huadong Liao, Jiawei He, Kunxian Shu
    http://arxiv.org/abs/1905.03239v1

    • [cs.LG]Meta-learning of Sequential Strategies
    Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alex Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin Miller, Mohammad Azar, Ian Osband, Neil Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew Botvinick, Shane Legg
    http://arxiv.org/abs/1905.03030v1

    • [cs.LG]MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records
    Xi Sheryl Zhang, Fengyi Tang, Hiroko Dodge, Jiayu Zhou, Fei Wang
    http://arxiv.org/abs/1905.03218v1

    • [cs.LG]Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets
    Gerome Vivar, Hendrik Burwinkel, Anees Kazi, Andreas Zwergal, Nassir Navab, Seyed-Ahmad Ahmadi
    http://arxiv.org/abs/1905.03053v1

    • [cs.LG]PiNet: A Permutation Invariant Graph Neural Network for Graph Classification
    Peter Meltzer, Marcelo Daniel Gutierrez Mallea, Peter J. Bentley
    http://arxiv.org/abs/1905.03046v1

    • [cs.LG]Robust Federated Training via Collaborative Machine Teaching using Trusted Instances
    Yufei Han, Xiangliang Zhang
    http://arxiv.org/abs/1905.02941v1

    • [cs.LG]SAdam: A Variant of Adam for Strongly Convex Functions
    Guanghui Wang, Shiyin Lu, Weiwei Tu, Lijun Zhang
    http://arxiv.org/abs/1905.02957v1

    • [cs.LG]Smoothing Policies and Safe Policy Gradients
    Matteo Papini, Matteo Pirotta, Marcello Restelli
    http://arxiv.org/abs/1905.03231v1

    • [cs.LG]Toybox: A Suite of Environments for Experimental Evaluation of Deep Reinforcement Learning
    Emma Tosch, Kaleigh Clary, John Foley, David Jensen
    http://arxiv.org/abs/1905.02825v1

    • [cs.LG]Uncertainty-Aware Data Aggregation for Deep Imitation Learning
    Yuchen Cui, David Isele, Scott Niekum, Kikuo Fujimura
    http://arxiv.org/abs/1905.02780v1

    • [cs.LG]Understanding attention in graph neural networks
    Boris Knyazev, Graham W. Taylor, Mohamed R. Amer
    http://arxiv.org/abs/1905.02850v1

    • [cs.LG]Unsupervised Learning through Temporal Smoothing and Entropy Maximization
    Per Rutquist
    http://arxiv.org/abs/1905.03100v1

    • [cs.NE]Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis
    Priyadarshini Panda, Efstathia Soufleri, Kaushik Roy
    http://arxiv.org/abs/1905.03219v1

    • [cs.NE]Fast-DENSER++: Evolving Fully-Trained Deep Artificial Neural Networks
    Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
    http://arxiv.org/abs/1905.02969v1

    • [cs.NE]Optimal Randomness in Swarm-based Search
    Jiamin Wei, Yangquan Chen, Yongguang Yu, Yuquan Chen
    http://arxiv.org/abs/1905.02776v1

    • [cs.NI]Locality-Sensitive Sketching for Resilient Network Flow Monitoring
    Yongquan Fu, Dongsheng Li, Siqi Shen, Yiming Zhang, Kai Chen
    http://arxiv.org/abs/1905.03113v1

    • [cs.RO]Adaptive neural network based dynamic surface control for uncertain dual arm robots
    Dung Tien Pham, Thai Van Nguyen, Hai Xuan Le, Linh Nguyen, Nguyen Huu Thai, Tuan Anh Phan, Hai Tuan Pham, Anh Hoai Duong
    http://arxiv.org/abs/1905.02914v1

    • [cs.RO]Anytime Multi-arm Task and Motion Planning for Pick-and-Place of Individual Objects via Handoffs
    Rahul Shome, Kostas E. Bekris
    http://arxiv.org/abs/1905.03179v1

    • [cs.RO]Bayesian Optimization for Polynomial Time Probabilistically Complete STL Trajectory Synthesis
    Vince Kurtz, Hai Lin
    http://arxiv.org/abs/1905.03051v1

    • [cs.RO]Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving
    Tobias Kessler, Julian Bernhard, Martin Buechel, Klemens Esterle, Patrick Hart, Daniel Malovetz, Michael Truong Le, Frederik Diehl, Thomas Brunner, Alois Knoll
    http://arxiv.org/abs/1905.02980v1

    • [cs.RO]Configuration-Space Flipper Planning for Rescue Robots
    Yijun Yuan, Letong Wang, Sören, Schwertfeger
    http://arxiv.org/abs/1905.02984v1

    • [cs.RO]LiStereo: Generate Dense Depth Maps from LIDAR and Stereo Imagery
    Junming Zhang, Manikandasriram Srinivasan Ramanagopalg, Ram Vasudevan, Matthew Johnson-Roberson
    http://arxiv.org/abs/1905.02744v1

    • [cs.SI]A hybrid recommendation algorithm based on weighted stochastic block model
    Yuchen Xiao, Ruzhe Zhong
    http://arxiv.org/abs/1905.03192v1

    • [cs.SI]Displaying Things in Common to Encourage Friendship Formation: A Large Randomized Field Experiment
    Tianshu Sun, Sean J. Taylor
    http://arxiv.org/abs/1905.02762v1

    • [cs.SI]Multi-class Twitter Data Categorization and Geocoding with a Novel Computing Framework
    Sakib Mahmud Khan, Mashrur Chowdhury, Linh B. Ngo, Amy Apon
    http://arxiv.org/abs/1905.02916v1

    • [cs.SI]Quantifying Triadic Closure in Multi-Edge Social Networks
    Laurence Brandenberger, Giona Casiraghi, Vahan Nanumyan, Frank Schweitzer
    http://arxiv.org/abs/1905.02990v1

    • [eess.IV]3d-SMRnet: Achieving a new quality of MPI system matrix recovery by deep learning
    Ivo Matteo Baltruschat, Patryk Szwargulski, Florian Griese, Mirco Grosser, René Werner, Tobias Knopp
    http://arxiv.org/abs/1905.03026v1

    • [eess.IV]Convolutional Neural Networks Considering Local and Global features for Image Enhancement
    Yuma Kinoshita, Hitoshi Kiya
    http://arxiv.org/abs/1905.02899v1

    • [eess.IV]Fast online 3D reconstruction of dynamic scenes from individual single-photon detection events
    Yoann Altmann, Stephen McLaughlin, Michael E. Davies
    http://arxiv.org/abs/1905.02944v1

    • [eess.SP]A Hardware-Oriented and Memory-Efficient Method for CTC Decoding
    Siyuan Lu, Jinming Lu, Jun Lin, Zhongfeng Wang
    http://arxiv.org/abs/1905.03175v1

    • [eess.SP]A Multistage Method for SCMA Codebook Design Based on MDS Codes
    Bruno Fontana da Silva, Danilo Silva, Bartolomeu F. Uchôa-Filho, Didier Le Ruyet
    http://arxiv.org/abs/1905.02533v1

    • [eess.SP]Sparse multiresolution representations with adaptive kernels
    Maria Peifer, Luiz. F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
    http://arxiv.org/abs/1905.02797v1

    • [math.NA]Variational training of neural network approximations of solution maps for physical models
    Yingzhou Li, Jianfeng Lu, Anqi Mao
    http://arxiv.org/abs/1905.02789v1

    • [math.ST]Bounding distributional errors via density ratios
    Lutz Duembgen, Richard Samworth, Jon Wellner
    http://arxiv.org/abs/1905.03009v1

    • [math.ST]Exact Largest Eigenvalue Distribution for Doubly Singular Beta Ensemble
    Stepan Grinek
    http://arxiv.org/abs/1905.01774v2

    • [math.ST]Minimax Hausdorff estimation of density level sets
    Alberto Rodríguez-Casal, Paula Saavedra-Nieves
    http://arxiv.org/abs/1905.02897v1

    • [math.ST]Sliced Latin hypercube designs with arbitrary run sizes
    Jin Xu, Xu He, Xiaojun Duan, Zhengming Wang
    http://arxiv.org/abs/1905.02721v1

    • [physics.comp-ph]Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems
    Jonathan P. Mailoa, Mordechai Kornbluth, Simon L. Batzner, Georgy Samsonidze, Stephen T. Lam, Chris Ablitt, Nicola Molinari, Boris Kozinsky
    http://arxiv.org/abs/1905.02791v1

    • [physics.soc-ph]What do we see when we look at networks
    Tommaso Venturini, Mathieu Jacomy, Pablo Jensen
    http://arxiv.org/abs/1905.02202v1

    • [q-bio.GN]Somatic mutations render human exome and pathogen DNA more similar
    Ehsan Ebrahimzadeh, Maggie Engler, David Tse, Razvan Cristescu, Aslan Tchamkerten
    http://arxiv.org/abs/1905.03138v1

    • [stat.ME]Conformalized Quantile Regression
    Yaniv Romano, Evan Patterson, Emmanuel J. Candès
    http://arxiv.org/abs/1905.03222v1

    • [stat.ME]Consistent Fixed-Effects Selection in Ultra-high dimensional Linear Mixed Models with Error-Covariate Endogeneity
    Abhik Ghosh, Magne Thoresen
    http://arxiv.org/abs/1905.02971v1

    • [stat.ME]Decision Making with Machine Learning and ROC Curves
    Kai Feng, Han Hong, Ke Tang, Jingyuan Wang
    http://arxiv.org/abs/1905.02810v1

    • [stat.ME]Predictive inference with the jackknife+
    Rina Foygel Barber, Emmanuel J. Candes, Aaditya Ramdas, Ryan J. Tibshirani
    http://arxiv.org/abs/1905.02928v1

    • [stat.ME]Robust regression based on shrinkage estimators
    Elisa Cabana, Rosa E. Lillo, Henry Laniado
    http://arxiv.org/abs/1905.02962v1

    • [stat.ML]A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks
    Lior Deutsch, Erik Nijkamp, Yu Yang
    http://arxiv.org/abs/1905.02898v1

    • [stat.ML]Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
    Dominic Richards, Patrick Rebeschini
    http://arxiv.org/abs/1905.03135v1