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