astro-ph.SR - 太阳和天体物理学恒星

    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.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.SD - 声音处理 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.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 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

    • [astro-ph.SR]Fast Solar Image Classification Using Deep Learning and its Importance for Automation in Solar Physics
    • [cs.AI]A Value-based Trust Assessment Model for Multi-agent Systems
    • [cs.AI]Foundations of Digital Archæoludology
    • [cs.AI]Multiple Policy Value Monte Carlo Tree Search
    • [cs.AI]Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation
    • [cs.CL]A Lightweight Recurrent Network for Sequence Modeling
    • [cs.CL]Assessing The Factual Accuracy of Generated Text
    • [cs.CL]Attention Is (not) All You Need for Commonsense Reasoning
    • [cs.CL]Constructive Type-Logical Supertagging with Self-Attention Networks
    • [cs.CL]Content Word-based Sentence Decoding and Evaluating for Open-domain Neural Response Generation
    • [cs.CL]Crowdsourcing and Validating Event-focused Emotion Corpora for German and English
    • [cs.CL]DiaBLa: A Corpus of Bilingual Spontaneous Written Dialogues for Machine Translation
    • [cs.CL]Do Human Rationales Improve Machine Explanations?
    • [cs.CL]Effective writing style imitation via combinatorial paraphrasing
    • [cs.CL]Fine-Grained Spoiler Detection from Large-Scale Review Corpora
    • [cs.CL]GSN: A Graph-Structured Network for Multi-Party Dialogues
    • [cs.CL]Grammar-based Neural Text-to-SQL Generation
    • [cs.CL]Improving Open Information Extraction via Iterative Rank-Aware Learning
    • [cs.CL]Information Minimization In Emergent Languages
    • [cs.CL]Investigating an Effective Character-level Embedding in Korean Sentence Classification
    • [cs.CL]Leveraging Pretrained Word Embeddings for Part-of-Speech Tagging of Code Switching Data
    • [cs.CL]MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
    • [cs.CL]Multi-modal Discriminative Model for Vision-and-Language Navigation
    • [cs.CL]MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension
    • [cs.CL]Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement Learning
    • [cs.CL]Symbol Emergence as an Interpersonal Multimodal Categorization
    • [cs.CL]Using Natural Language Processing to Develop an Automated Orthodontic Diagnostic System
    • [cs.CR]Privacy-Preserving Detection of IoT Devices Connected Behind a NAT in a Smart Home Setup
    • [cs.CR]Real-Time Adversarial Attacks
    • [cs.CR]Using Metrics Suites to Improve the Measurement of Privacy in Graphs
    • [cs.CV]3DPalsyNet: A Facial Palsy Grading and Motion Recognition Framework using Fully 3D Convolutional Neural Networks
    • [cs.CV]A Riemanian Approach to Blob Detection in Manifold-Valued Images
    • [cs.CV]A survey of advances in vision-based vehicle re-identification
    • [cs.CV]All-In-One Underwater Image Enhancement using Domain-Adversarial Learning
    • [cs.CV]Counting and Segmenting Sorghum Heads
    • [cs.CV]Deep Dual Relation Modeling for Egocentric Interaction Recognition
    • [cs.CV]Deep interpretable architecture for plant diseases classification
    • [cs.CV]Design Light-weight 3D Convolutional Networks for Video Recognition Temporal Residual, Fully Separable Block, and Fast Algorithm
    • [cs.CV]Joint Representation of Multiple Geometric Priors via a Shape Decomposition Model for Single Monocular 3D Pose Estimation
    • [cs.CV]Large Scale Incremental Learning
    • [cs.CV]Multi-Precision Quantized Neural Networks via Encoding Decomposition of -1 and +1
    • [cs.CV]Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams
    • [cs.CV]Multitask Text-to-Visual Embedding with Titles and Clickthrough Data
    • [cs.CV]Point Clouds Learning with Attention-based Graph Convolution Networks
    • [cs.CV]Rethinking Table Parsing using Graph Neural Networks
    • [cs.CV]Scene Text Visual Question Answering
    • [cs.CV]Supervised Online Hashing via Similarity Distribution Learning
    • [cs.CV]TACNet: Transition-Aware Context Network for Spatio-Temporal Action Detection
    • [cs.DB]Efficient Multiway Hash Join on Reconfigurable Hardware
    • [cs.DB]ParPaRaw: Massively Parallel Parsing of Delimiter-Separated Raw Data
    • [cs.DC]From Global Choreographies to Provably Correct and Efficient Distributed Implementations
    • [cs.DC]INFaaS: Managed & Model-less Inference Serving
    • [cs.DC]Isolation-Aware Timing Analysis and Design Space Exploration for Predictable and Composable Many-Core Systems
    • [cs.DC]The Bloom Clock
    • [cs.DC]Tracking in Order to Recover: Recoverable Lock-Free Data Structures
    • [cs.DS]Principal Fairness: \ Removing Bias via Projections
    • [cs.IR]Threshold-Based Retrieval and Textual Entailment Detection on Legal Bar Exam Questions
    • [cs.IT]Age of Information in G/G/1/1 Systems: Age Expressions, Bounds, Special Cases, and Optimization
    • [cs.IT]Collaborative Decoding of Polynomial Codes for Distributed Computation
    • [cs.IT]Deep Learning for Distributed Optimization: Applications to Wireless Resource Management
    • [cs.IT]Log-logarithmic Time Pruned Polar Coding
    • [cs.IT]Neural Entropic Estimation: A faster path to mutual information estimation
    • [cs.IT]Performance Analysis of Clustered LoRa Networks
    • [cs.IT]When Full Duplex Wireless Meets Non-Orthogonal Multiple Access: Opportunities and Challenges
    • [cs.LG]A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting
    • [cs.LG]Are Labels Required for Improving Adversarial Robustness?
    • [cs.LG]Attentional Policies for Cross-Context Multi-Agent Reinforcement Learning
    • [cs.LG]Augmenting Transfer Learning with Semantic Reasoning
    • [cs.LG]Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models
    • [cs.LG]Bypassing Backdoor Detection Algorithms in Deep Learning
    • [cs.LG]Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit
    • [cs.LG]Combating the Compounding-Error Problem with a Multi-step Model
    • [cs.LG]Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing
    • [cs.LG]Deep Bayesian Optimization on Attributed Graphs
    • [cs.LG]DeepShift: Towards Multiplication-Less Neural Networks
    • [cs.LG]Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience
    • [cs.LG]Discriminative structural graph classification
    • [cs.LG]End to end learning and optimization on graphs
    • [cs.LG]Exact sampling of determinantal point processes with sublinear time preprocessing
    • [cs.LG]Explainability Techniques for Graph Convolutional Networks
    • [cs.LG]Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations
    • [cs.LG]Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series
    • [cs.LG]Fast Online “Next Best Offers” using Deep Learning
    • [cs.LG]GENO — GENeric Optimization for Classical Machine Learning
    • [cs.LG]Implicit Regularization in Deep Matrix Factorization
    • [cs.LG]Interval timing in deep reinforcement learning agents
    • [cs.LG]L0 Regularization Based Neural Network Design and Compression
    • [cs.LG]Learning Sparse Networks Using Targeted Dropout
    • [cs.LG]Leveraging Trust and Distrust in Recommender Systems via Deep Learning
    • [cs.LG]Luck Matters: Understanding Training Dynamics of Deep ReLU Networks
    • [cs.LG]Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds
    • [cs.LG]MolecularRNN: Generating realistic molecular graphs with optimized properties
    • [cs.LG]Neural Markov Logic Networks
    • [cs.LG]On Value Functions and the Agent-Environment Boundary
    • [cs.LG]On the Fairness of Disentangled Representations
    • [cs.LG]On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder
    • [cs.LG]Ordinal Regression as Structured Classification
    • [cs.LG]PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
    • [cs.LG]Pre-Training Graph Neural Networks for Generic Structural Feature Extraction
    • [cs.LG]Reinforcement Learning Experience Reuse with Policy Residual Representation
    • [cs.LG]Reinforcement Learning for Mean Field Game
    • [cs.LG]Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology
    • [cs.LG]Residual Networks as Nonlinear Systems: Stability Analysis using Linearization
    • [cs.LG]SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry
    • [cs.LG]Scaffold-based molecular design using graph generative model
    • [cs.LG]Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
    • [cs.LG]Subspace Networks for Few-shot Classification
    • [cs.LG]Sum-of-squares meets square loss: Fast rates for agnostic tensor completion
    • [cs.LG]Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence
    • [cs.LG]Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning
    • [cs.LG]Uncoupled Regression from Pairwise Comparison Data
    • [cs.LG]Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
    • [cs.NE]Epsilon-Lexicase Selection for Regression
    • [cs.NE]Improved memory in recurrent neural networks with sequential non-normal dynamics
    • [cs.NI]Maximizing Clearance Rate by Penalizing Redundant Task Assignment in Mobile Crowdsensing Auctions
    • [cs.NI]Reducing Tail Latency via Safe and Simple Duplication
    • [cs.RO]2.5D Image based Robotic Grasping
    • [cs.RO]Fast and Agile Vision-Based Flight with Teleoperation and Collision Avoidance on a Multirotor
    • [cs.RO]Graduated Fidelity Lattices for Motion Planning under Uncertainty
    • [cs.RO]Inverting Learned Dynamics Models for Aggressive Multirotor Control
    • [cs.RO]Recent Advances in Imitation Learning from Observation
    • [cs.RO]Taming Combinatorial Challenges in Optimal Clutter Removal Tasks
    • [cs.SD]What does a Car-ssette tape tell?
    • [cs.SI]Can We Derive Explicit and Implicit Bias from Corpus?
    • [cs.SI]Spotting Collusive Behaviour of Online Fraud Groups in Customer Reviews
    • [eess.IV]Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection
    • [eess.IV]Improving the resolution of CryoEM single particle analysis
    • [eess.IV]Known-plaintext attack and ciphertext-only attack for encrypted single-pixel imaging
    • [eess.IV]Partial Scan Electron Microscopy with Deep Learning
    • [eess.SP]A Block Diagonal Markov Model for Indoor Software-Defined Power Line Communication
    • [math.NA]Unified Analysis of Periodization-Based Sampling Methods for Matérn Covariances
    • [math.OC]ADMM for Efficient Deep Learning with Global Convergence
    • [math.OC]Distributed Submodular Minimization via Block-Wise Updates and Communications
    • [math.PR]KMT coupling for random walk bridges
    • [math.ST]Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation
    • [math.ST]State occupation probabilities in non-Markov models
    • [quant-ph]Quantum Mean Embedding of Probability Distributions
    • [stat.AP]Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models
    • [stat.CO]Component-wise approximate Bayesian computation via Gibbs-like steps
    • [stat.ME]Accumulation Bias in Meta-Analysis: The Need to Consider Time in Error Control
    • [stat.ME]Targeted Estimation of L2 Distance Between Densities and its Application to Geo-spatial Data
    • [stat.ML]A multi-series framework for demand forecasts in E-commerce
    • [stat.ML]Clustered Gaussian Graphical Model via Symmetric Convex Clustering
    • [stat.ML]High Dimensional Classification via Empirical Risk Minimization: Improvements and Optimality
    • [stat.ML]Neural Likelihoods for Multi-Output Gaussian Processes
    • [stat.ML]PAC-Bayesian Transportation Bound
    • [stat.ML]RKHSMetaMod : An R package to estimate the Hoeffding decomposition of an unknown function by solving RKHS Ridge Group Sparse optimization problem
    • [stat.ML]Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
    • [stat.ML]Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network
    • [stat.ML]Sparse Approximate Cross-Validation for High-Dimensional GLMs
    • [stat.ML]Training Dynamics of Deep Networks using Stochastic Gradient Descent via Neural Tangent Kernel
    • [stat.ML]Unlabeled Data Improves Adversarial Robustness

    ·····································

    • [astro-ph.SR]Fast Solar Image Classification Using Deep Learning and its Importance for Automation in Solar Physics
    John A. Armstrong, Lyndsay Fletcher
    http://arxiv.org/abs/1905.13575v1

    • [cs.AI]A Value-based Trust Assessment Model for Multi-agent Systems
    Kinzang Chhogyal, Abhaya Nayak, Aditya Ghose, Hoa Khanh Dam
    http://arxiv.org/abs/1905.13380v1

    • [cs.AI]Foundations of Digital Archæoludology
    Cameron Browne, Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson, Michael Conrad, Walter Crist, Thierry Depaulis, Eddie Duggan, Fred Horn, Steven Kelk, Simon M. Lucas, João Pedro Neto, David Parlett, Abdallah Saffidine, Ulrich Schädler, Jorge Nuno Silva, Alex de Voogt, Mark H. M. Winands
    http://arxiv.org/abs/1905.13516v1

    • [cs.AI]Multiple Policy Value Monte Carlo Tree Search
    Li-Cheng Lan, Wei Li, Ting-Han Wei, I-Chen Wu
    http://arxiv.org/abs/1905.13521v1

    • [cs.AI]Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation
    Tobias Joppen, Tilman Strübig, Johannes Fürnkranz
    http://arxiv.org/abs/1905.13449v1

    • [cs.CL]A Lightweight Recurrent Network for Sequence Modeling
    Biao Zhang, Rico Sennrich
    http://arxiv.org/abs/1905.13324v1

    • [cs.CL]Assessing The Factual Accuracy of Generated Text
    Ben Goodrich, Vinay Rao, Mohammad Saleh, Peter J Liu
    http://arxiv.org/abs/1905.13322v1

    • [cs.CL]Attention Is (not) All You Need for Commonsense Reasoning
    Tassilo Klein, Moin Nabi
    http://arxiv.org/abs/1905.13497v1

    • [cs.CL]Constructive Type-Logical Supertagging with Self-Attention Networks
    Konstantinos Kogkalidis, Michael Moortgat, Tejaswini Deoskar
    http://arxiv.org/abs/1905.13418v1

    • [cs.CL]Content Word-based Sentence Decoding and Evaluating for Open-domain Neural Response Generation
    Tianyu Zhao, Tatsuya Kawahara
    http://arxiv.org/abs/1905.13438v1

    • [cs.CL]Crowdsourcing and Validating Event-focused Emotion Corpora for German and English
    Enrica Troiano, Sebastian Padó, Roman Klinger
    http://arxiv.org/abs/1905.13618v1

    • [cs.CL]DiaBLa: A Corpus of Bilingual Spontaneous Written Dialogues for Machine Translation
    Rachel Bawden, Sophie Rosset, Thomas Lavergne, Eric Bilinski
    http://arxiv.org/abs/1905.13354v1

    • [cs.CL]Do Human Rationales Improve Machine Explanations?
    Julia Strout, Ye Zhang, Raymond J. Mooney
    http://arxiv.org/abs/1905.13714v1

    • [cs.CL]Effective writing style imitation via combinatorial paraphrasing
    Tommi Gröndahl, N. Asokan
    http://arxiv.org/abs/1905.13464v1

    • [cs.CL]Fine-Grained Spoiler Detection from Large-Scale Review Corpora
    Mengting Wan, Rishabh Misra, Ndapa Nakashole, Julian McAuley
    http://arxiv.org/abs/1905.13416v1

    • [cs.CL]GSN: A Graph-Structured Network for Multi-Party Dialogues
    Wenpeng Hu, Zhangming Chan, Bing Liu, Dongyan Zhao, Jinwen Ma, Rui Yan
    http://arxiv.org/abs/1905.13637v1

    • [cs.CL]Grammar-based Neural Text-to-SQL Generation
    Kevin Lin, Ben Bogin, Mark Neumann, Jonathan Berant, Matt Gardner
    http://arxiv.org/abs/1905.13326v1

    • [cs.CL]Improving Open Information Extraction via Iterative Rank-Aware Learning
    Zhengbao Jiang, Pengcheng Yin, Graham Neubig
    http://arxiv.org/abs/1905.13413v1

    • [cs.CL]Information Minimization In Emergent Languages
    Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni
    http://arxiv.org/abs/1905.13687v1

    • [cs.CL]Investigating an Effective Character-level Embedding in Korean Sentence Classification
    Won Ik Cho, Seok Min Kim, Nam Soo Kim
    http://arxiv.org/abs/1905.13656v1

    • [cs.CL]Leveraging Pretrained Word Embeddings for Part-of-Speech Tagging of Code Switching Data
    Fahad AlGhamdi, Mona Diab
    http://arxiv.org/abs/1905.13359v1

    • [cs.CL]MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
    Aida Amini, Saadia Gabriel, Peter Lin, Rik Koncel-Kedziorski, Yejin Choi, Hannaneh Hajishirzi
    http://arxiv.org/abs/1905.13319v1

    • [cs.CL]Multi-modal Discriminative Model for Vision-and-Language Navigation
    Haoshuo Huang, Vihan Jain, Harsh Mehta, Jason Baldridge, Eugene Ie
    http://arxiv.org/abs/1905.13358v1

    • [cs.CL]MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension
    Alon Talmor, Jonathan Berant
    http://arxiv.org/abs/1905.13453v1

    • [cs.CL]Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement Learning
    Tahira Naseem, Abhishek Shah, Hui Wan, Radu Florian, Salim Roukos, Miguel Ballesteros
    http://arxiv.org/abs/1905.13370v1

    • [cs.CL]Symbol Emergence as an Interpersonal Multimodal Categorization
    Yoshinobu Hagiwara, Hiroyoshi Kobayashi, Akira Taniguchi, Tadahiro Taniguchi
    http://arxiv.org/abs/1905.13443v1

    • [cs.CL]Using Natural Language Processing to Develop an Automated Orthodontic Diagnostic System
    Tomoyuki Kajiwara, Chihiro Tanikawa, Yuujin Shimizu, Chenhui Chu, Takashi Yamashiro, Hajime Nagahara
    http://arxiv.org/abs/1905.13601v1

    • [cs.CR]Privacy-Preserving Detection of IoT Devices Connected Behind a NAT in a Smart Home Setup
    Yair Meidan, Vinay Sachidananda, Yuval Elovici, Asaf Shabtai
    http://arxiv.org/abs/1905.13430v1

    • [cs.CR]Real-Time Adversarial Attacks
    Yuan Gong, Boyang Li, Christian Poellabauer, Yiyu Shi
    http://arxiv.org/abs/1905.13399v1

    • [cs.CR]Using Metrics Suites to Improve the Measurement of Privacy in Graphs
    Isabel Wagner, Yuchen Zhao
    http://arxiv.org/abs/1905.13264v1

    • [cs.CV]3DPalsyNet: A Facial Palsy Grading and Motion Recognition Framework using Fully 3D Convolutional Neural Networks
    Gary Storey, Richard Jiang, Shelagh Keogh, Ahmed Bouridane, Chang-Tsun Li
    http://arxiv.org/abs/1905.13607v1

    • [cs.CV]A Riemanian Approach to Blob Detection in Manifold-Valued Images
    Aleksei Shestov, Mikhail Kumskov
    http://arxiv.org/abs/1905.13653v1

    • [cs.CV]A survey of advances in vision-based vehicle re-identification
    Sultan Daud Khan, Habib Ullah
    http://arxiv.org/abs/1905.13258v1

    • [cs.CV]All-In-One Underwater Image Enhancement using Domain-Adversarial Learning
    Pritish Uplavikar, Zhenyu Wu, Zhangyang Wang
    http://arxiv.org/abs/1905.13342v1

    • [cs.CV]Counting and Segmenting Sorghum Heads
    Min-hwan Oh, Peder Olsen, Karthikeyan Natesan Ramamurthy
    http://arxiv.org/abs/1905.13291v1

    • [cs.CV]Deep Dual Relation Modeling for Egocentric Interaction Recognition
    Haoxin Li, Yijun Cai, Wei-Shi Zheng
    http://arxiv.org/abs/1905.13586v1

    • [cs.CV]Deep interpretable architecture for plant diseases classification
    Mohammed Brahimi, Said Mahmoudi, Kamel Boukhalfa, Abdelouhab Moussaoui
    http://arxiv.org/abs/1905.13523v1

    • [cs.CV]Design Light-weight 3D Convolutional Networks for Video Recognition Temporal Residual, Fully Separable Block, and Fast Algorithm
    Haonan Wang, Jun Lin, Zhongfeng Wang
    http://arxiv.org/abs/1905.13388v1

    • [cs.CV]Joint Representation of Multiple Geometric Priors via a Shape Decomposition Model for Single Monocular 3D Pose Estimation
    Mengxi Jiang, Zhuliang Yu, Cuihua Li, Yunqi Lei
    http://arxiv.org/abs/1905.13466v1

    • [cs.CV]Large Scale Incremental Learning
    Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, Yun Fu
    http://arxiv.org/abs/1905.13260v1

    • [cs.CV]Multi-Precision Quantized Neural Networks via Encoding Decomposition of -1 and +1
    Qigong Sun, Fanhua Shang, Kang Yang, Xiufang Li, Yan Ren, Licheng Jiao
    http://arxiv.org/abs/1905.13389v1

    • [cs.CV]Multimodal Joint Emotion and Game Context Recognition in League of Legends Livestreams
    Charles Ringer, James Alfred Walker, Mihalis A. Nicolaou
    http://arxiv.org/abs/1905.13694v1

    • [cs.CV]Multitask Text-to-Visual Embedding with Titles and Clickthrough Data
    Pranav Aggarwal, Zhe Lin, Baldo Faieta, Saeid Motiian
    http://arxiv.org/abs/1905.13339v1

    • [cs.CV]Point Clouds Learning with Attention-based Graph Convolution Networks
    Zhuyang Xie, Junzhou Chen, Bo Peng
    http://arxiv.org/abs/1905.13445v1

    • [cs.CV]Rethinking Table Parsing using Graph Neural Networks
    Shah Rukh Qasim, Hassan Mahmood, Faisal Shafait
    http://arxiv.org/abs/1905.13391v1

    • [cs.CV]Scene Text Visual Question Answering
    Ali Furkan Biten, Ruben Tito, Andres Mafla, Lluis Gomez, Marçal Rusiñol, Ernest Valveny, C. V. Jawahar, Dimosthenis Karatzas
    http://arxiv.org/abs/1905.13648v1

    • [cs.CV]Supervised Online Hashing via Similarity Distribution Learning
    Mingbao Lin, Rongrong Ji, Shen Chen, Feng Zheng, Xiaoshuai Sun, Baochang Zhang, Liujuan Cao, Guodong Guo, Feiyue Huang
    http://arxiv.org/abs/1905.13382v1

    • [cs.CV]TACNet: Transition-Aware Context Network for Spatio-Temporal Action Detection
    Lin Song, Shiwei Zhang, Gang Yu, Hongbin Sun
    http://arxiv.org/abs/1905.13417v1

    • [cs.DB]Efficient Multiway Hash Join on Reconfigurable Hardware
    Kunle Olukotun, Raghu Prabhakar, Rekha Singhal, Jeffrey D. Ullman, Yaqi Zhang
    http://arxiv.org/abs/1905.13376v1

    • [cs.DB]ParPaRaw: Massively Parallel Parsing of Delimiter-Separated Raw Data
    Elias Stehle, Hans-Arno Jacobsen
    http://arxiv.org/abs/1905.13415v1

    • [cs.DC]From Global Choreographies to Provably Correct and Efficient Distributed Implementations
    Mohamad Jaber, Yliès Falcone, Paul Attie, Al-Abbass Khalil, Rayan Hallal
    http://arxiv.org/abs/1905.13529v1

    • [cs.DC]INFaaS: Managed & Model-less Inference Serving
    Francisco Romero, Qian Li, Neeraja J. Yadwadkar, Christos Kozyrakis
    http://arxiv.org/abs/1905.13348v1

    • [cs.DC]Isolation-Aware Timing Analysis and Design Space Exploration for Predictable and Composable Many-Core Systems
    Behnaz Pourmohseni, Fedor Smirnov, Stefan Wildermann, Jürgen Teich
    http://arxiv.org/abs/1905.13503v1

    • [cs.DC]The Bloom Clock
    Lum Ramabaja
    http://arxiv.org/abs/1905.13064v2

    • [cs.DC]Tracking in Order to Recover: Recoverable Lock-Free Data Structures
    Hagit Attiya, Ohad Ben-Baruch, Panagiota Fatourou, Danny Hendler, Eleftherios Kosmas
    http://arxiv.org/abs/1905.13600v1

    • [cs.DS]Principal Fairness: \ Removing Bias via Projections
    Aris Anagnostopoulos, Luca Becchetti, Matteo Böhm, Adriano Fazzone, Stefano Leonardi, Cristina Menghini, Chris Schwiegelshohn
    http://arxiv.org/abs/1905.13651v1

    • [cs.IR]Threshold-Based Retrieval and Textual Entailment Detection on Legal Bar Exam Questions
    Sabine Wehnert, Sayed Anisul Hoque, Wolfram Fenske, Gunter Saake
    http://arxiv.org/abs/1905.13350v1

    • [cs.IT]Age of Information in G/G/1/1 Systems: Age Expressions, Bounds, Special Cases, and Optimization
    Alkan Soysal, Sennur Ulukus
    http://arxiv.org/abs/1905.13743v1

    • [cs.IT]Collaborative Decoding of Polynomial Codes for Distributed Computation
    Adarsh M. Subramaniam, Anoosheh Heiderzadeh, Krishna R. Narayanan
    http://arxiv.org/abs/1905.13685v1

    • [cs.IT]Deep Learning for Distributed Optimization: Applications to Wireless Resource Management
    Hoon Lee, Sang Hyun Lee, Tony Q. S. Quek
    http://arxiv.org/abs/1905.13378v1

    • [cs.IT]Log-logarithmic Time Pruned Polar Coding
    Hsin-Po Wang, Iwan Duursma
    http://arxiv.org/abs/1905.13340v1

    • [cs.IT]Neural Entropic Estimation: A faster path to mutual information estimation
    Chung Chan, Ali Al-Bashabsheh, Hing Pang Huang, Michael Lim, Da Sun Handason Tam, Chao Zhao
    http://arxiv.org/abs/1905.12957v2

    • [cs.IT]Performance Analysis of Clustered LoRa Networks
    Zhijin Qin, Yuanwei Liu, Geoffrey Ye Li, Julie A. McCann
    http://arxiv.org/abs/1905.13510v1

    • [cs.IT]When Full Duplex Wireless Meets Non-Orthogonal Multiple Access: Opportunities and Challenges
    Xianhao Chen, Gang Liu, Zheng Ma, Xi Zhang, Pingzhi Fan, Shanzhi Chen, F. Richard Yu
    http://arxiv.org/abs/1905.13605v1

    • [cs.LG]A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting
    Pei Du, Jianzhou Wang, Yan Hao, Tong Niu, Wendong Yang
    http://arxiv.org/abs/1905.13550v1

    • [cs.LG]Are Labels Required for Improving Adversarial Robustness?
    Jonathan Uesato, Jean-Baptiste Alayrac, Po-Sen Huang, Robert Stanforth, Alhussein Fawzi, Pushmeet Kohli*
    http://arxiv.org/abs/1905.13725v1

    • [cs.LG]Attentional Policies for Cross-Context Multi-Agent Reinforcement Learning
    Matthew A. Wright, Roberto Horowitz
    http://arxiv.org/abs/1905.13428v1

    • [cs.LG]Augmenting Transfer Learning with Semantic Reasoning
    Freddy Lecue, Jiaoyan Chen, Jeff Z. Pan, Huajun Chen
    http://arxiv.org/abs/1905.13672v1

    • [cs.LG]Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models
    Daniele Castellana, Davide Bacciu
    http://arxiv.org/abs/1905.13528v1

    • [cs.LG]Bypassing Backdoor Detection Algorithms in Deep Learning
    Te Juin Lester Tan, Reza Shokri
    http://arxiv.org/abs/1905.13409v1

    • [cs.LG]Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit
    Yi-Qi Hu, Yang Yu, Jun-Da Liao
    http://arxiv.org/abs/1905.13703v1

    • [cs.LG]Combating the Compounding-Error Problem with a Multi-step Model
    Kavosh Asadi, Dipendra Misra, Seungchan Kim, Michel L. Littman
    http://arxiv.org/abs/1905.13320v1

    • [cs.LG]Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing
    Jesus A. De Loera, Jamie Haddock, Anna Ma, Deanna Needell
    http://arxiv.org/abs/1905.13404v1

    • [cs.LG]Deep Bayesian Optimization on Attributed Graphs
    Jiaxu Cui, Bo Yang, Xia Hu
    http://arxiv.org/abs/1905.13403v1

    • [cs.LG]DeepShift: Towards Multiplication-Less Neural Networks
    Mostafa Elhoushi, Farhan Shafiq, Ye Tian, Joey Yiwei Li, Zihao Chen
    http://arxiv.org/abs/1905.13298v1

    • [cs.LG]Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience
    Vaishnavh Nagarajan, J. Zico Kolter
    http://arxiv.org/abs/1905.13344v1

    • [cs.LG]Discriminative structural graph classification
    Younjoo Seo, Andreas Loukas, Nathanael Peraudin
    http://arxiv.org/abs/1905.13422v1

    • [cs.LG]End to end learning and optimization on graphs
    Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe
    http://arxiv.org/abs/1905.13732v1

    • [cs.LG]Exact sampling of determinantal point processes with sublinear time preprocessing
    Michał Dereziński, Daniele Calandriello, Michal Valko
    http://arxiv.org/abs/1905.13476v1

    • [cs.LG]Explainability Techniques for Graph Convolutional Networks
    Federico Baldassarre, Hossein Azizpour
    http://arxiv.org/abs/1905.13686v1

    • [cs.LG]Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations
    Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg
    http://arxiv.org/abs/1905.13402v1

    • [cs.LG]Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series
    Zhi-Xuan Tan, Harold Soh, Desmond C. Ong
    http://arxiv.org/abs/1905.13570v1

    • [cs.LG]Fast Online “Next Best Offers” using Deep Learning
    Rekha Singhal, Gautam Shroff, Mukund Kumar, Sharod Roy, Sanket Kadarkar, Rupinder virk, Siddharth Verma, Vartika Tiwari
    http://arxiv.org/abs/1905.13368v1

    • [cs.LG]GENO — GENeric Optimization for Classical Machine Learning
    Sören Laue, Matthias Mitterreiter, Joachim Giesen
    http://arxiv.org/abs/1905.13587v1

    • [cs.LG]Implicit Regularization in Deep Matrix Factorization
    Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo
    http://arxiv.org/abs/1905.13655v1

    • [cs.LG]Interval timing in deep reinforcement learning agents
    Ben Deverett, Ryan Faulkner, Meire Fortunato, Greg Wayne, Joel Z. Leibo
    http://arxiv.org/abs/1905.13469v1

    • [cs.LG]L0 Regularization Based Neural Network Design and Compression
    S. Asim Ahmed
    http://arxiv.org/abs/1905.13652v1

    • [cs.LG]Learning Sparse Networks Using Targeted Dropout
    Aidan N. Gomez, Ivan Zhang, Kevin Swersky, Yarin Gal, Geoffrey E. Hinton
    http://arxiv.org/abs/1905.13678v1

    • [cs.LG]Leveraging Trust and Distrust in Recommender Systems via Deep Learning
    Dimitrios Rafailidis
    http://arxiv.org/abs/1905.13612v1

    • [cs.LG]Luck Matters: Understanding Training Dynamics of Deep ReLU Networks
    Yuandong Tian, Tina Jiang, Qucheng Gong, Ari Morcos
    http://arxiv.org/abs/1905.13405v1

    • [cs.LG]Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds
    Peng Cao, Yilun Xu, Yuqing Kong, Yizhou Wang
    http://arxiv.org/abs/1905.13436v1

    • [cs.LG]MolecularRNN: Generating realistic molecular graphs with optimized properties
    Mariya Popova, Mykhailo Shvets, Junier Oliva, Olexandr Isayev
    http://arxiv.org/abs/1905.13372v1

    • [cs.LG]Neural Markov Logic Networks
    Giuseppe Marra, Ondřej Kuželka
    http://arxiv.org/abs/1905.13462v1

    • [cs.LG]On Value Functions and the Agent-Environment Boundary
    Nan Jiang
    http://arxiv.org/abs/1905.13341v1

    • [cs.LG]On the Fairness of Disentangled Representations
    Francesco Locatello, Gabriele Abbati, Tom Rainforth, Stefan Bauer, Bernhard Schölkopf, Olivier Bachem
    http://arxiv.org/abs/1905.13662v1

    • [cs.LG]On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder
    Haowen Xu, Wenxiao Chen, Jinlin Lai, Zhihan Li, Youjian Zhao, Dan Pei
    http://arxiv.org/abs/1905.13452v1

    • [cs.LG]Ordinal Regression as Structured Classification
    Niall Twomey, Rafael Poyiadzi, Callum Mann, Raúl Santos-Rodríguez
    http://arxiv.org/abs/1905.13658v1

    • [cs.LG]PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
    Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
    http://arxiv.org/abs/1905.13727v1

    • [cs.LG]Pre-Training Graph Neural Networks for Generic Structural Feature Extraction
    Ziniu Hu, Changjun Fan, Ting Chen, Kai-Wei Chang, Yizhou Sun
    http://arxiv.org/abs/1905.13728v1

    • [cs.LG]Reinforcement Learning Experience Reuse with Policy Residual Representation
    Wen-Ji Zhou, Yang Yu, Yingfeng Chen, Kai Guan, Tangjie Lv, Changjie Fan, Zhi-Hua Zhou
    http://arxiv.org/abs/1905.13719v1

    • [cs.LG]Reinforcement Learning for Mean Field Game
    Nilay Tiwari, Arnob Ghosh, Vaneet Aggarwal
    http://arxiv.org/abs/1905.13357v1

    • [cs.LG]Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology
    Eugene Ie, Vihan Jain, Jing Wang, Sanmit Narvekar, Ritesh Agarwal, Rui Wu, Heng-Tze Cheng, Morgane Lustman, Vince Gatto, Paul Covington, Jim McFadden, Tushar Chandra, Craig Boutilier
    http://arxiv.org/abs/1905.12767v2

    • [cs.LG]Residual Networks as Nonlinear Systems: Stability Analysis using Linearization
    Kai Rothauge, Zhewei Yao, Zixi Hu, Michael W. Mahoney
    http://arxiv.org/abs/1905.13386v1

    • [cs.LG]SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry
    Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik
    http://arxiv.org/abs/1905.13741v1

    • [cs.LG]Scaffold-based molecular design using graph generative model
    Jaechang Lim, Sang-Yeon Hwang, Seungsu Kim, Seokhyun Moon, Woo Youn Kim
    http://arxiv.org/abs/1905.13639v1

    • [cs.LG]Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
    Yang Liu, Yunan Luo, Yuanyi Zhong, Xi Chen, Qiang Liu, Jian Peng
    http://arxiv.org/abs/1905.13420v1

    • [cs.LG]Subspace Networks for Few-shot Classification
    Arnout Devos, Matthias Grossglauser
    http://arxiv.org/abs/1905.13613v1

    • [cs.LG]Sum-of-squares meets square loss: Fast rates for agnostic tensor completion
    Dylan J. Foster, Andrej Risteski
    http://arxiv.org/abs/1905.13283v1

    • [cs.LG]Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence
    Aditya Golatkar, Alessandro Achille, Stefano Soatto
    http://arxiv.org/abs/1905.13277v1

    • [cs.LG]Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning
    Tailai Wen, Roy Keyes
    http://arxiv.org/abs/1905.13628v1

    • [cs.LG]Uncoupled Regression from Pairwise Comparison Data
    Liyuan Xu, Junya Honda, Niu Gang, Masashi Sugiyama
    http://arxiv.org/abs/1905.13659v1

    • [cs.LG]Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input
    Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
    http://arxiv.org/abs/1905.13633v1

    • [cs.NE]Epsilon-Lexicase Selection for Regression
    William La Cava, Lee Spector, Kourosh Danai
    http://arxiv.org/abs/1905.13266v1

    • [cs.NE]Improved memory in recurrent neural networks with sequential non-normal dynamics
    A. Emin Orhan, Xaq Pitkow
    http://arxiv.org/abs/1905.13715v1

    • [cs.NI]Maximizing Clearance Rate by Penalizing Redundant Task Assignment in Mobile Crowdsensing Auctions
    Maggie E. Gendy, Ahmad Al-Kabbany, Ehab F. Badran
    http://arxiv.org/abs/1905.13563v1

    • [cs.NI]Reducing Tail Latency via Safe and Simple Duplication
    Hafiz Mohsin Bashir, Abdullah Bin Faisal, Muhammad Asim Jamshed, Peter Vondras, Ali Musa Iftikhar, Ihsan Ayyub Qazi, Fahad R. Dogar
    http://arxiv.org/abs/1905.13352v1

    • [cs.RO]2.5D Image based Robotic Grasping
    Song Yaoxian, Cheng Chun, Fei Yuejiao, Li Xiangqing, Yu Changbin
    http://arxiv.org/abs/1905.13675v1

    • [cs.RO]Fast and Agile Vision-Based Flight with Teleoperation and Collision Avoidance on a Multirotor
    Alex Spitzer, Xuning Yang, John Yao, Aditya Dhawale, Kshitij Goel, Mosam Dabhi, Matt Collins, Curtis Boirum, Nathan Michael
    http://arxiv.org/abs/1905.13419v1

    • [cs.RO]Graduated Fidelity Lattices for Motion Planning under Uncertainty
    Adrián González-Sieira, Manuel Mucientes, Alberto Bugarín
    http://arxiv.org/abs/1905.13531v1

    • [cs.RO]Inverting Learned Dynamics Models for Aggressive Multirotor Control
    Alexander Spitzer, Nathan Michael
    http://arxiv.org/abs/1905.13441v1

    • [cs.RO]Recent Advances in Imitation Learning from Observation
    Faraz Torabi, Garrett Warnell, Peter Stone
    http://arxiv.org/abs/1905.13566v1

    • [cs.RO]Taming Combinatorial Challenges in Optimal Clutter Removal Tasks
    Wei N. Tang, Jingjin Yu
    http://arxiv.org/abs/1905.13530v1

    • [cs.SD]What does a Car-ssette tape tell?
    Xuenan Xu, Heinrich Dinkel, Mengyue Wu, Kai Yu
    http://arxiv.org/abs/1905.13448v1

    • [cs.SI]Can We Derive Explicit and Implicit Bias from Corpus?
    Bo Wang, Baixiang Xue, Anthony G. Greenwald
    http://arxiv.org/abs/1905.13364v1

    • [cs.SI]Spotting Collusive Behaviour of Online Fraud Groups in Customer Reviews
    Sarthika Dhawan, Siva Charan Reddy Gangireddy, Shiv Kumar, Tanmoy Chakraborty
    http://arxiv.org/abs/1905.13649v1

    • [eess.IV]Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection
    Changhee Han, Leonardo Rundo, Ryosuke Araki, Yudai Nagano, Yujiro Furukawa, Giancarlo Mauri, Hideki Nakayama, Hideaki Hayashi
    http://arxiv.org/abs/1905.13456v1

    • [eess.IV]Improving the resolution of CryoEM single particle analysis
    Zhenwei Luo
    http://arxiv.org/abs/1905.13408v1

    • [eess.IV]Known-plaintext attack and ciphertext-only attack for encrypted single-pixel imaging
    Shuming Jiao, Yang Gao, Ting Lei, Zhenwei Xie, Xiaocong Yuan
    http://arxiv.org/abs/1905.13594v1

    • [eess.IV]Partial Scan Electron Microscopy with Deep Learning
    Jeffrey M. Ede, Richard Beanland
    http://arxiv.org/abs/1905.13667v1

    • [eess.SP]A Block Diagonal Markov Model for Indoor Software-Defined Power Line Communication
    Ayokunle Damilola Familua
    http://arxiv.org/abs/1905.13598v1

    • [math.NA]Unified Analysis of Periodization-Based Sampling Methods for Matérn Covariances
    Markus Bachmayr, Ivan G. Graham, Van Kien Nguyen, Robert Scheichl
    http://arxiv.org/abs/1905.13522v1

    • [math.OC]ADMM for Efficient Deep Learning with Global Convergence
    Junxiang Wang, Fuxun Yu, Xiang Chen, Liang Zhao
    http://arxiv.org/abs/1905.13611v1

    • [math.OC]Distributed Submodular Minimization via Block-Wise Updates and Communications
    Francesco Farina, Andrea Testa, Giuseppe Notarstefano
    http://arxiv.org/abs/1905.13682v1

    • [math.PR]KMT coupling for random walk bridges
    Evgeni Dimitrov, Xuan Wu
    http://arxiv.org/abs/1905.13691v1

    • [math.ST]Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation
    Ziv Goldfeld, Kristjan Greenewald, Yury Polyanskiy, Jonathan Weed
    http://arxiv.org/abs/1905.13576v1

    • [math.ST]State occupation probabilities in non-Markov models
    Morten Overgaard
    http://arxiv.org/abs/1905.13499v1

    • [quant-ph]Quantum Mean Embedding of Probability Distributions
    Jonas M. Kübler, Krikamol Muandet, Bernhard Schölkopf
    http://arxiv.org/abs/1905.13526v1

    • [stat.AP]Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models
    Jens Schreiber, Artjom Buschin, Bernhard Sick
    http://arxiv.org/abs/1905.13668v1

    • [stat.CO]Component-wise approximate Bayesian computation via Gibbs-like steps
    Grégoire Clarté, Christian P. Robert, Robin Ryder, Julien Stoehr
    http://arxiv.org/abs/1905.13599v1

    • [stat.ME]Accumulation Bias in Meta-Analysis: The Need to Consider Time in Error Control
    Judith ter Schure, Peter D. Grünwald
    http://arxiv.org/abs/1905.13494v1

    • [stat.ME]Targeted Estimation of L2 Distance Between Densities and its Application to Geo-spatial Data
    George Shan, Mark J. van der Laan
    http://arxiv.org/abs/1905.13414v1

    • [stat.ML]A multi-series framework for demand forecasts in E-commerce
    Rémy Garnier, Arnaud Belletoile
    http://arxiv.org/abs/1905.13614v1

    • [stat.ML]Clustered Gaussian Graphical Model via Symmetric Convex Clustering
    Tianyi Yao, Genevera I. Allen
    http://arxiv.org/abs/1905.13251v1

    • [stat.ML]High Dimensional Classification via Empirical Risk Minimization: Improvements and Optimality
    Xiaoyi Mai, Zhenyu Liao
    http://arxiv.org/abs/1905.13742v1

    • [stat.ML]Neural Likelihoods for Multi-Output Gaussian Processes
    Martin Jankowiak, Jacob Gardner
    http://arxiv.org/abs/1905.13697v1

    • [stat.ML]PAC-Bayesian Transportation Bound
    Kohei Miyaguchi
    http://arxiv.org/abs/1905.13435v1

    • [stat.ML]RKHSMetaMod : An R package to estimate the Hoeffding decomposition of an unknown function by solving RKHS Ridge Group Sparse optimization problem
    Halaleh Kamari, Sylvie Huet, Marie-Luce Taupin
    http://arxiv.org/abs/1905.13695v1

    • [stat.ML]Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
    Andrey Malinin, Mark Gales
    http://arxiv.org/abs/1905.13472v1

    • [stat.ML]Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network
    Jennifer L Cardona, Michael F Howland, John O Dabiri
    http://arxiv.org/abs/1905.13290v1

    • [stat.ML]Sparse Approximate Cross-Validation for High-Dimensional GLMs
    William Stephenson, Tamara Broderick
    http://arxiv.org/abs/1905.13657v1

    • [stat.ML]Training Dynamics of Deep Networks using Stochastic Gradient Descent via Neural Tangent Kernel
    Soufiane Hayou, Arnaud Doucet, Judith Rousseau
    http://arxiv.org/abs/1905.13654v1

    • [stat.ML]Unlabeled Data Improves Adversarial Robustness
    Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, Percy Liang, John C. Duchi
    http://arxiv.org/abs/1905.13736v1