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.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 hep-ph - 高能物理现象学 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.med-ph - 医学物理学 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Info Intervention
    • [cs.AI]Online Event Recognition from Moving Vehicles: Application Paper
    • [cs.AI]Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge
    • [cs.CL]Adaptive Noise Injection: A Structure-Expanding Regularization for RNN
    • [cs.CL]Bilingual Lexicon Induction through Unsupervised Machine Translation
    • [cs.CL]Careful Selection of Knowledge to solve Open Book Question Answering
    • [cs.CL]Cross-Lingual Transfer for Distantly Supervised and Low-resources Indonesian NER
    • [cs.CL]DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks
    • [cs.CL]Grammatical Sequence Prediction for Real-Time Neural Semantic Parsing
    • [cs.CL]HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop
    • [cs.CL]HireNet: a Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews
    • [cs.CL]INS: An Interactive Chinese News Synthesis System
    • [cs.CL]Summary Refinement through Denoising
    • [cs.CL]WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale
    • [cs.CR]Machine learning and semantic analysis of in-game chat for cyberbullying
    • [cs.CV]A Compact Light Field Camera for Real-Time Depth Estimation
    • [cs.CV]A Fine-Grained Facial Expression Database for End-to-End Multi-Pose Facial Expression Recognition
    • [cs.CV]Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks
    • [cs.CV]Co-Evolutionary Compression for Unpaired Image Translation
    • [cs.CV]Composition-Aware Image Aesthetics Assessment
    • [cs.CV]Convolutional Neural Networks on Randomized Data
    • [cs.CV]Cross Attention Network for Semantic Segmentation
    • [cs.CV]Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
    • [cs.CV]Don’t Worry About the Weather: Unsupervised Condition-Dependent Domain Adaptation
    • [cs.CV]Dual Grid Net: hand mesh vertex regression from single depth maps
    • [cs.CV]ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation
    • [cs.CV]Enhancing Underexposed Photos using Perceptually Bidirectional Similarity
    • [cs.CV]From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
    • [cs.CV]Hard-Aware Fashion Attribute Classification
    • [cs.CV]How to Manipulate CNNs to Make Them Lie: the GradCAM Case
    • [cs.CV]Importance-Aware Semantic Segmentation with Efficient Pyramidal Context Network for Navigational Assistant Systems
    • [cs.CV]Interpretability Beyond Classification Output: Semantic Bottleneck Networks
    • [cs.CV]Interpreting the Latent Space of GANs for Semantic Face Editing
    • [cs.CV]Joint Adversarial Training: Incorporating both Spatial and Pixel Attacks
    • [cs.CV]LayoutVAE: Stochastic Scene Layout Generation from a Label Set
    • [cs.CV]Learning Resolution-Invariant Deep Representations for Person Re-Identification
    • [cs.CV]Learning Visual Actions Using Multiple Verb-Only Labels
    • [cs.CV]MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification
    • [cs.CV]One-stage Shape Instantiation from a Single 2D Image to 3D Point Cloud
    • [cs.CV]PU-GAN: a Point Cloud Upsampling Adversarial Network
    • [cs.CV]SDNet: Semantically Guided Depth Estimation Network
    • [cs.CV]Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking
    • [cs.CV]Self-supervised Domain Adaptation for Computer Vision Tasks
    • [cs.CV]Semi-parametric Object Synthesis
    • [cs.CV]SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications
    • [cs.CV]Submission to ActivityNet Challenge 2019: Task B Spatio-temporal Action Localization
    • [cs.CV]U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
    • [cs.CV]Uncalibrated Deflectometry with a Mobile Device on Extended Specular Surfaces
    • [cs.CV]Y-Autoencoders: disentangling latent representations via sequential-encoding
    • [cs.CY]Electronic health record in the era of industry 4.0: the French example
    • [cs.CY]Green AI
    • [cs.DB]Applying Constraint Logic Programming to SQL Semantic Analysis
    • [cs.DC]A Self-Stabilizing Minimal k-Grouping Algorithm
    • [cs.DC]Collaborative Heterogeneous Computing on MPSoCs
    • [cs.DC]DeFog: Fog Computing Benchmarks
    • [cs.DC]Fast Deterministic Constructions of Linear-Size Spanners and Skeletons
    • [cs.DC]OPPLOAD: Offloading Computational Workflows in Opportunistic Networks
    • [cs.DC]Scalable and Secure Computation Among Strangers: Resource-Competitive Byzantine Protocols
    • [cs.DS]Enumerating Range Modes
    • [cs.DS]How to Store a Random Walk
    • [cs.DS]Polylogarithmic-Time Deterministic Network Decomposition and Distributed Derandomization
    • [cs.HC]Accurate and Robust Eye Contact Detection During Everyday Mobile Device Interactions
    • [cs.HC]How far are we from quantifying visual attention in mobile HCI?
    • [cs.HC]Visual Interaction with Deep Learning Models through Collaborative Semantic Inference
    • [cs.IR]Generic Intent Representation in Web Search
    • [cs.IR]Modelling Dynamic Interactions between Relevance Dimensions
    • [cs.IR]Personalised novel and explainable matrix factorisation
    • [cs.IT]Factored LT and Factored Raptor Codes for Large-Scale Distributed Matrix Multiplication
    • [cs.IT]Improving HD-FEC decoding via bit marking
    • [cs.IT]Private Proximity Retrieval Codes
    • [cs.IT]Time-Invariant Feedback Strategies Do Not Increase Capacity of AGN Channels Driven by Stable and Certain Unstable Autoregressive Noise
    • [cs.LG]Automated Discovery and Classification of Training Videos for Career Progression
    • [cs.LG]Automatic crack detection and classification by exploiting statistical event descriptors for Deep Learning
    • [cs.LG]Benchmarking TPU, GPU, and CPU Platforms for Deep Learning
    • [cs.LG]Curriculum based Dropout Discriminator for Domain Adaptation
    • [cs.LG]Dynamic Input for Deep Reinforcement Learning in Autonomous Driving
    • [cs.LG]Enhancing Adversarial Example Transferability with an Intermediate Level Attack
    • [cs.LG]Filter Bank Regularization of Convolutional Neural Networks
    • [cs.LG]Framelet Pooling Aided Deep Learning Network : The Method to Process High Dimensional Medical Data
    • [cs.LG]Google Research Football: A Novel Reinforcement Learning Environment
    • [cs.LG]Graph Neural Lasso for Dynamic Network Regression
    • [cs.LG]GraphX$^{NET}-$ Chest X-Ray Classification Under Extreme Minimal Supervision
    • [cs.LG]HUGE2: a Highly Untangled Generative-model Engine for Edge-computing
    • [cs.LG]Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization
    • [cs.LG]Learning higher-order logic programs
    • [cs.LG]Logical reduction of metarules
    • [cs.LG]Machine learning approach to remove ion interference effect in agricultural nutrient solutions
    • [cs.LG]Optuna: A Next-generation Hyperparameter Optimization Framework
    • [cs.LG]Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation
    • [cs.LG]Prediction of Highway Lane Changes Based on Prototype Trajectories
    • [cs.LG]Sampled Softmax with Random Fourier Features
    • [cs.LG]Self-attention based BiLSTM-CNN classifier for the prediction of ischemic and non-ischemic cardiomyopathy
    • [cs.LG]Semisupervised Adversarial Neural Networks for Cyber Security Transfer Learning
    • [cs.LG]Simultaneous multi-view instance detection with learned geometric soft-constraints
    • [cs.LG]Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning
    • [cs.LG]The Good, the Bad and the Ugly: Augmenting a black-box model with expert knowledge
    • [cs.LG]The Truly Deep Graph Convolutional Networks for Node Classification
    • [cs.LG]Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph
    • [cs.LG]Towards AutoML in the presence of Drift: first results
    • [cs.LG]Towards Generalizing Sensorimotor Control Across Weather Conditions
    • [cs.LG]Unsupervised Domain Adaptation via Calibrating Uncertainties
    • [cs.LO]On Uniform Equivalence of Epistemic Logic Programs
    • [cs.MA]A Framework for Monitoring Human Physiological Response during Human Robot Collaborative Task
    • [cs.NE]Benchmarking HillVallEA for the GECCO 2019 Competition on Multimodal Optimization
    • [cs.RO]Experimentation on the motion of an obstacle avoiding robot
    • [cs.RO]Object Perception and Grasping in Open-Ended Domains
    • [cs.RO]Overview of Guidance, Navigation and Control System of the TeamIndus lunar lander
    • [cs.RO]Robot Learning of Shifting Objects for Grasping in Cluttered Environments
    • [cs.RO]TuneNet: One-Shot Residual Tuning for System Identification and Sim-to-Real Robot Task Transfer
    • [cs.RO]Weakly Supervised Recognition of Surgical Gestures
    • [cs.SE]An Empirical Analysis of the Python Package Index (PyPI)
    • [cs.SI]Does Facebook Use Sensitive Data for Advertising Purposes? Worldwide Analysis and GDPR Impact
    • [cs.SI]Real-time Event Detection on Social Data Streams
    • [eess.AS]Cross-Attention End-to-End ASR for Two-Party Conversations
    • [eess.IV]Hetero-Modal Variational Encoder-Decoder for Joint Modality Completion and Segmentation
    • [eess.IV]Is Texture Predictive for Age and Sex in Brain MRI?
    • [eess.IV]Performance Evaluation of Two-layer lossless HDR Coding using Histogram Packing Technique under Various Tone-mapping Operators
    • [eess.IV]Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification
    • [eess.SP]An Overview of Enhanced Massive MIMO with Array Signal Processing Techniques
    • [hep-ph]MadMiner: Machine learning-based inference for particle physics
    • [math.OC]Safe Feature Elimination for Non-Negativity Constrained Convex Optimization
    • [math.PR]Conditional probability in Renyi spaces
    • [math.ST]Bootstrapping Networks with Latent Space Structure
    • [math.ST]Density deconvolution under general assumptions on the distribution of measurement errors
    • [physics.med-ph]Body-worn triaxial accelerometer coherence and reliability related to static posturography in unilateral vestibular failure
    • [physics.soc-ph]Influence and Betweenness in Flow Models of Complex Network Systems
    • [q-bio.NC]The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging
    • [q-bio.PE]Complete maximum likelihood estimation for SEIR epidemic models: theoretical development
    • [quant-ph]Quantum Walk over a triangular lattice subject to Pachner move
    • [stat.AP]Bayesian Analysis of Spatial Generalized Linear Mixed Models with Laplace Random Fields
    • [stat.AP]Computational Phenotype Discovery via Probabilistic Independence
    • [stat.AP]Fitting motion models to contextual player behavior
    • [stat.AP]Teaching Split Plot Experiments With a Boomerang Tin
    • [stat.CO]BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic Likelihood
    • [stat.CO]Particle Methods for Stochastic Differential Equation Mixed Effects Models
    • [stat.CO]Transport Monte Carlo
    • [stat.ME]Functional Models for Time-Varying Random Objects
    • [stat.ME]JointAI: Joint Analysis and Imputation of Incomplete Data in R
    • [stat.ME]Learning binary undirected graph in low dimensional regime
    • [stat.ME]New frontiers in Bayesian modeling using the INLA package in R
    • [stat.ME]Non-constant hazard ratios in randomized controlled trials with composite endpoints
    • [stat.ME]On the bias of H-scores for comparing biclusters, and how to correct it
    • [stat.ME]Transportability of Outcome Measurement Error Correction: from Validation Studies to Intervention Trials
    • [stat.ML]Deep Generative Quantile-Copula Models for Probabilistic Forecasting
    • [stat.ML]Deep Learning Models to Predict Pediatric Asthma Emergency Department Visits
    • [stat.ML]Domain Generalization via Multidomain Discriminant Analysis
    • [stat.ML]Fast generalization error bound of deep learning without scale invariance of activation functions
    • [stat.ML]Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method
    • [stat.ML]Invariance reduces Variance: Understanding Data Augmentation in Deep Learning and Beyond

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

    • [cs.AI]Info Intervention
    Gong Heyang, Zhu Ke
    http://arxiv.org/abs/1907.11090v1

    • [cs.AI]Online Event Recognition from Moving Vehicles: Application Paper
    Efthimis Tsilionis, Nikolaos Koutroumanis, Panagiotis Nikitopoulos, Christos Doulkeridis, Alexander Artikis
    http://arxiv.org/abs/1907.11007v1

    • [cs.AI]Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge
    Arpit Sharma
    http://arxiv.org/abs/1907.11112v1

    • [cs.CL]Adaptive Noise Injection: A Structure-Expanding Regularization for RNN
    Rui Li, Kai Shuang, Mengyu Gu, Sen Su
    http://arxiv.org/abs/1907.10885v1

    • [cs.CL]Bilingual Lexicon Induction through Unsupervised Machine Translation
    Mikel Artetxe, Gorka Labaka, Eneko Agirre
    http://arxiv.org/abs/1907.10761v1

    • [cs.CL]Careful Selection of Knowledge to solve Open Book Question Answering
    Pratyay Banerjee, Kuntal Kumar Pal, Arindam Mitra, Chitta Baral
    http://arxiv.org/abs/1907.10738v1

    • [cs.CL]Cross-Lingual Transfer for Distantly Supervised and Low-resources Indonesian NER
    Fariz Ikhwantri
    http://arxiv.org/abs/1907.11158v1

    • [cs.CL]DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks
    Lin Zehui, Pengfei Liu, Luyao Huang, Jie Fu, Junkun Chen, Xipeng Qiu, Xuanjing Huang
    http://arxiv.org/abs/1907.11065v1

    • [cs.CL]Grammatical Sequence Prediction for Real-Time Neural Semantic Parsing
    Chunyang Xiao, Christoph Teichmann, Konstantine Arkoudas
    http://arxiv.org/abs/1907.11049v1

    • [cs.CL]HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop
    Yiwei Yang, Eser Kandogan, Yunyao Li, Walter S. Lasecki, Prithviraj Sen
    http://arxiv.org/abs/1907.11184v1

    • [cs.CL]HireNet: a Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews
    Léo Hemamou, Ghazi Felhi, Vincent Vandenbussche, Jean-Claude Martin, Chloé Clavel
    http://arxiv.org/abs/1907.11062v1

    • [cs.CL]INS: An Interactive Chinese News Synthesis System
    Hui Liu, Wentao Qin, Xiaojun Wan
    http://arxiv.org/abs/1907.10781v1

    • [cs.CL]Summary Refinement through Denoising
    Nikola I. Nikolov, Alessandro Calmanovici, Richard H. R. Hahnloser
    http://arxiv.org/abs/1907.10873v1

    • [cs.CL]WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale
    Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
    http://arxiv.org/abs/1907.10641v1

    • [cs.CR]Machine learning and semantic analysis of in-game chat for cyberbullying
    Shane Murnion, William J. Buchanan, Adrian Smales, Gordon Russell
    http://arxiv.org/abs/1907.10855v1

    • [cs.CV]A Compact Light Field Camera for Real-Time Depth Estimation
    Yuriy Anisimov, Oliver Wasenmüller, Didier Stricker
    http://arxiv.org/abs/1907.10880v1

    • [cs.CV]A Fine-Grained Facial Expression Database for End-to-End Multi-Pose Facial Expression Recognition
    Wenxuan Wang, Qiang Sun, Tao Chen, Chenjie Cao, Ziqi Zheng, Guoqiang Xu, Han Qiu, Yanwei Fu
    http://arxiv.org/abs/1907.10838v1

    • [cs.CV]Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks
    Mattias P. Heinrich
    http://arxiv.org/abs/1907.10931v1

    • [cs.CV]Co-Evolutionary Compression for Unpaired Image Translation
    Han Shu, Yunhe Wang, Xu Jia, Kai Han, Hanting Chen, Chunjing Xu, Qi Tian, Chang Xu
    http://arxiv.org/abs/1907.10804v1

    • [cs.CV]Composition-Aware Image Aesthetics Assessment
    Dong Liu, Rohit Puri, Nagendra Kamath, Subhabrata Bhattachary
    http://arxiv.org/abs/1907.10801v1

    • [cs.CV]Convolutional Neural Networks on Randomized Data
    Cristian Ivan
    http://arxiv.org/abs/1907.10935v1

    • [cs.CV]Cross Attention Network for Semantic Segmentation
    Mengyu Liu, Hujun Yin
    http://arxiv.org/abs/1907.10958v1

    • [cs.CV]Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
    Haichao Zhang, Jianyu Wang
    http://arxiv.org/abs/1907.10764v1

    • [cs.CV]Don’t Worry About the Weather: Unsupervised Condition-Dependent Domain Adaptation
    Horia Porav, Tom Bruls, Paul Newman
    http://arxiv.org/abs/1907.11004v1

    • [cs.CV]Dual Grid Net: hand mesh vertex regression from single depth maps
    Chengde Wan, Thomas Probst, Luc Van Gool, Angela Yao
    http://arxiv.org/abs/1907.10695v1

    • [cs.CV]ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation
    Zhijie Zhang, Huazhu Fu, Hang Dai, Jianbing Shen, Yanwei Pang, Ling Shao
    http://arxiv.org/abs/1907.10936v1

    • [cs.CV]Enhancing Underexposed Photos using Perceptually Bidirectional Similarity
    Qing Zhang, Yongwei Nie, Chunxia Xiao, Wei-Shi Zheng
    http://arxiv.org/abs/1907.10992v1

    • [cs.CV]From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
    Jin Han Lee, Myung-Kyu Han, Dong Wook Ko, Il Hong Suh
    http://arxiv.org/abs/1907.10326v2

    • [cs.CV]Hard-Aware Fashion Attribute Classification
    Yun Ye, Yixin Li, Bo Wu, Wei Zhang, Lingyu Duan, Tao Mei
    http://arxiv.org/abs/1907.10839v1

    • [cs.CV]How to Manipulate CNNs to Make Them Lie: the GradCAM Case
    Tom Viering, Ziqi Wang, Marco Loog, Elmar Eisemann
    http://arxiv.org/abs/1907.10901v1

    • [cs.CV]Importance-Aware Semantic Segmentation with Efficient Pyramidal Context Network for Navigational Assistant Systems
    Kaite Xiang, Kaiwei Wang, Kailun Yang
    http://arxiv.org/abs/1907.11066v1

    • [cs.CV]Interpretability Beyond Classification Output: Semantic Bottleneck Networks
    Max Losch, Mario Fritz, Bernt Schiele
    http://arxiv.org/abs/1907.10882v1

    • [cs.CV]Interpreting the Latent Space of GANs for Semantic Face Editing
    Yujun Shen, Jinjin Gu, Xiaoou Tang, Bolei Zhou
    http://arxiv.org/abs/1907.10786v1

    • [cs.CV]Joint Adversarial Training: Incorporating both Spatial and Pixel Attacks
    Haichao Zhang, Jianyu Wang
    http://arxiv.org/abs/1907.10737v1

    • [cs.CV]LayoutVAE: Stochastic Scene Layout Generation from a Label Set
    Akash Abdu Jyothi, Thibaut Durand, Jiawei He, Leonid Sigal, Greg Mori
    http://arxiv.org/abs/1907.10719v1

    • [cs.CV]Learning Resolution-Invariant Deep Representations for Person Re-Identification
    Yun-Chun Chen, Yu-Jhe Li, Xiaofei Du, Yu-Chiang Frank Wang
    http://arxiv.org/abs/1907.10843v1

    • [cs.CV]Learning Visual Actions Using Multiple Verb-Only Labels
    Michael Wray, Dima Damen
    http://arxiv.org/abs/1907.11117v1

    • [cs.CV]MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification
    Lukas Liebel, Marco Körner
    http://arxiv.org/abs/1907.11111v1

    • [cs.CV]One-stage Shape Instantiation from a Single 2D Image to 3D Point Cloud
    Xiao-Yun Zhou, Zhao-Yang Wang, Peichao Li, Jian-Qing Zheng, Guang-Zhong Yang
    http://arxiv.org/abs/1907.10763v1

    • [cs.CV]PU-GAN: a Point Cloud Upsampling Adversarial Network
    Ruihui Li, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng
    http://arxiv.org/abs/1907.10844v1

    • [cs.CV]SDNet: Semantically Guided Depth Estimation Network
    Matthias Ochs, Adrian Kretz, Rudolf Mester
    http://arxiv.org/abs/1907.10659v1

    • [cs.CV]Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking
    Jae Shin Yoon, Takaaki Shiratori, Shoou-I Yu, Hyun Soo Park
    http://arxiv.org/abs/1907.10815v1

    • [cs.CV]Self-supervised Domain Adaptation for Computer Vision Tasks
    Jiaolong Xu, Liang Xiao, Antonio M. Lopez
    http://arxiv.org/abs/1907.10915v1

    • [cs.CV]Semi-parametric Object Synthesis
    Andrea Palazzi, Luca Bergamini, Simone Calderara, Rita Cucchiara
    http://arxiv.org/abs/1907.10634v1

    • [cs.CV]SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications
    Pengyi Zhang, Yunxin Zhong, Xiaoqiong Li
    http://arxiv.org/abs/1907.11093v1

    • [cs.CV]Submission to ActivityNet Challenge 2019: Task B Spatio-temporal Action Localization
    Chunfei Ma, Joonhyang Choi, Byeongwon Lee, Seungji Yang
    http://arxiv.org/abs/1907.10837v1

    • [cs.CV]U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
    Junho Kim, Minjae Kim, Hyeonwoo Kang, Kwanghee Lee
    http://arxiv.org/abs/1907.10830v1

    • [cs.CV]Uncalibrated Deflectometry with a Mobile Device on Extended Specular Surfaces
    Florian Willomitzer, Chia-Kai Yeh, Vikas Gupta, William Spies, Florian Schiffers, Marc Walton, Oliver Cossairt
    http://arxiv.org/abs/1907.10700v1

    • [cs.CV]Y-Autoencoders: disentangling latent representations via sequential-encoding
    Massimiliano Patacchiola, Patrick Fox-Roberts, Edward Rosten
    http://arxiv.org/abs/1907.10949v1

    • [cs.CY]Electronic health record in the era of industry 4.0: the French example
    Sarah Manard, Nicolas Vergos, Simon Tamayo, Frédéric Fontane
    http://arxiv.org/abs/1907.10322v2

    • [cs.CY]Green AI
    Roy Schwartz, Jesse Dodge, Noah A. Smith, Oren Etzioni
    http://arxiv.org/abs/1907.10597v2

    • [cs.DB]Applying Constraint Logic Programming to SQL Semantic Analysis
    Fernando Sáenz-Pérez
    http://arxiv.org/abs/1907.10914v1

    • [cs.DC]A Self-Stabilizing Minimal k-Grouping Algorithm
    Ajoy K. Datta, Lawrence L. Larmore, Toshimitsu Masuzawa, Yuichi Sudo
    http://arxiv.org/abs/1907.10803v1

    • [cs.DC]Collaborative Heterogeneous Computing on MPSoCs
    Siqi Wang
    http://arxiv.org/abs/1907.10904v1

    • [cs.DC]DeFog: Fog Computing Benchmarks
    Jonathan McChesney, Nan Wang, Ashish Tanwer, Eyal de Lara, Blesson Varghese
    http://arxiv.org/abs/1907.10890v1

    • [cs.DC]Fast Deterministic Constructions of Linear-Size Spanners and Skeletons
    Michael Elkin, Shaked Matar
    http://arxiv.org/abs/1907.10895v1

    • [cs.DC]OPPLOAD: Offloading Computational Workflows in Opportunistic Networks
    Artur Sterz, Lars Baumgärtner, Jonas höchst, Patrick Lampe, Bernd Freisleben
    http://arxiv.org/abs/1907.10971v1

    • [cs.DC]Scalable and Secure Computation Among Strangers: Resource-Competitive Byzantine Protocols
    John Augustine, Valerie King, Anisur R. Molla, Gopal Pandurangan, Jared Saia
    http://arxiv.org/abs/1907.10308v2

    • [cs.DS]Enumerating Range Modes
    Kentaro Sumigawa, Sankardeep Chakraborty, Kunihiko Sadakane, Srinivasa Rao Satti
    http://arxiv.org/abs/1907.10984v1

    • [cs.DS]How to Store a Random Walk
    Emanuele Viola, Omri Weinstein, Huacheng Yu
    http://arxiv.org/abs/1907.10874v1

    • [cs.DS]Polylogarithmic-Time Deterministic Network Decomposition and Distributed Derandomization
    Václav Rozhoň, Mohsen Ghaffari
    http://arxiv.org/abs/1907.10937v1

    • [cs.HC]Accurate and Robust Eye Contact Detection During Everyday Mobile Device Interactions
    Mihai Bâce, Sander Staal, Andreas Bulling
    http://arxiv.org/abs/1907.11115v1

    • [cs.HC]How far are we from quantifying visual attention in mobile HCI?
    Mihai Bâce, Sander Staal, Andreas Bulling
    http://arxiv.org/abs/1907.11106v1

    • [cs.HC]Visual Interaction with Deep Learning Models through Collaborative Semantic Inference
    Sebastian Gehrmann, Hendrik Strobelt, Robert Krüger, Hanspeter Pfister, Alexander M. Rush
    http://arxiv.org/abs/1907.10739v1

    • [cs.IR]Generic Intent Representation in Web Search
    Hongfei Zhang, Xia Song, Chenyan Xiong, Corby Rosset, Paul N. Bennett, Nick Craswell, Saurabh Tiwary
    http://arxiv.org/abs/1907.10710v1

    • [cs.IR]Modelling Dynamic Interactions between Relevance Dimensions
    Sagar Uprety, Shahram Dehdashti, Lauren Fell, Peter Bruza, Dawei Song
    http://arxiv.org/abs/1907.10943v1

    • [cs.IR]Personalised novel and explainable matrix factorisation
    Ludovik Coba, Panagiotis Symeonidis, Markus Zanker
    http://arxiv.org/abs/1907.11000v1

    • [cs.IT]Factored LT and Factored Raptor Codes for Large-Scale Distributed Matrix Multiplication
    Asit Kumar Pradhan, Anoosheh Heidarzadeh, Krishna R. Narayanan
    http://arxiv.org/abs/1907.11018v1

    • [cs.IT]Improving HD-FEC decoding via bit marking
    Alex Alvarado, Gabriele Liga, Yi Lei, Bin Chen, Alexios Balatsoukas-Stimming
    http://arxiv.org/abs/1907.10918v1

    • [cs.IT]Private Proximity Retrieval Codes
    Yiwei Zhang, Eitan Yaakobi, Tuvi Etzion
    http://arxiv.org/abs/1907.10724v1

    • [cs.IT]Time-Invariant Feedback Strategies Do Not Increase Capacity of AGN Channels Driven by Stable and Certain Unstable Autoregressive Noise
    Charalambos D. Charalambous, Christos Kourtellaris, Sergey Loyka
    http://arxiv.org/abs/1907.10991v1

    • [cs.LG]Automated Discovery and Classification of Training Videos for Career Progression
    Alan Chern, Phuong Hoang, Madhav Sigdel, Janani Balaji, Mohammed Korayem
    http://arxiv.org/abs/1907.11086v1

    • [cs.LG]Automatic crack detection and classification by exploiting statistical event descriptors for Deep Learning
    Giulio Siracusano, Aurelio La Corte, Riccardo Tomasello, Francesco Lamonaca, Carmelo Scuro, Francesca Garescì, Mario Carpentieri, Giovanni Finocchio
    http://arxiv.org/abs/1907.10709v1

    • [cs.LG]Benchmarking TPU, GPU, and CPU Platforms for Deep Learning
    Yu, Wang, Gu-Yeon Wei, David Brooks
    http://arxiv.org/abs/1907.10701v1

    • [cs.LG]Curriculum based Dropout Discriminator for Domain Adaptation
    Vinod Kumar Kurmi, Vipul Bajaj, Venkatesh K Subramanian, Vinay P Namboodiri
    http://arxiv.org/abs/1907.10628v1

    • [cs.LG]Dynamic Input for Deep Reinforcement Learning in Autonomous Driving
    Maria Huegle, Gabriel Kalweit, Branka Mirchevska, Moritz Werling, Joschka Boedecker
    http://arxiv.org/abs/1907.10994v1

    • [cs.LG]Enhancing Adversarial Example Transferability with an Intermediate Level Attack
    Qian Huang, Isay Katsman, Horace He, Zeqi Gu, Serge Belongie, Ser-Nam Lim
    http://arxiv.org/abs/1907.10823v1

    • [cs.LG]Filter Bank Regularization of Convolutional Neural Networks
    Seyed Mehdi Ayyoubzadeh, Xiaolin Wu
    http://arxiv.org/abs/1907.11110v1

    • [cs.LG]Framelet Pooling Aided Deep Learning Network : The Method to Process High Dimensional Medical Data
    Chang Min Hyun, Kang Cheol Kim, Hyun Cheol Cho, Jae Kyu Cho, Jin Keun Seo
    http://arxiv.org/abs/1907.10834v1

    • [cs.LG]Google Research Football: A Novel Reinforcement Learning Environment
    Karol Kurach, Anton Raichuk, Piotr Stańczyk, Michał Zając, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly
    http://arxiv.org/abs/1907.11180v1

    • [cs.LG]Graph Neural Lasso for Dynamic Network Regression
    Yixin Chen, Lin Meng, Jiawei Zhang
    http://arxiv.org/abs/1907.11114v1

    • [cs.LG]GraphX$^{NET}-$ Chest X-Ray Classification Under Extreme Minimal Supervision
    Angelica I. Aviles-Rivero, Nicolas Papadakis, Ruoteng Li, Philip Sellars, Qingnan Fan, Robby T. Tan, Carola-Bibiane Schönlieb
    http://arxiv.org/abs/1907.10085v2

    • [cs.LG]HUGE2: a Highly Untangled Generative-model Engine for Edge-computing
    Feng Shi, Ziheng Xu, Tao Yuan, Song-Chun Zhu
    http://arxiv.org/abs/1907.11210v1

    • [cs.LG]Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization
    Xinyan Li, Qilong Gu, Yingxue Zhou, Tiancong Chen, Arindam Banerjee
    http://arxiv.org/abs/1907.10732v1

    • [cs.LG]Learning higher-order logic programs
    Andrew Cropper, Rolf Morel, Stephen H. Muggleton
    http://arxiv.org/abs/1907.10953v1

    • [cs.LG]Logical reduction of metarules
    Andrew Cropper, Sophie Tourret
    http://arxiv.org/abs/1907.10952v1

    • [cs.LG]Machine learning approach to remove ion interference effect in agricultural nutrient solutions
    Byunghyun Ban, Donghun Ryu, Minwoo Lee
    http://arxiv.org/abs/1907.10794v1

    • [cs.LG]Optuna: A Next-generation Hyperparameter Optimization Framework
    Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama
    http://arxiv.org/abs/1907.10902v1

    • [cs.LG]Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation
    Zeju Li, Konstantinos Kamnitsas, Ben Glocker
    http://arxiv.org/abs/1907.10982v1

    • [cs.LG]Prediction of Highway Lane Changes Based on Prototype Trajectories
    David Augustin, Marius Hofmann, Ulrich Konigorski
    http://arxiv.org/abs/1907.11208v1

    • [cs.LG]Sampled Softmax with Random Fourier Features
    Ankit Singh Rawat, Jiecao Chen, Felix Yu, Ananda Theertha Suresh, Sanjiv Kumar
    http://arxiv.org/abs/1907.10747v1

    • [cs.LG]Self-attention based BiLSTM-CNN classifier for the prediction of ischemic and non-ischemic cardiomyopathy
    Kavita Dubey, Anant Agarwal, Astitwa Sarthak Lathe, Ranjeet Kumar, Vishal Srivastava
    http://arxiv.org/abs/1907.10370v2

    • [cs.LG]Semisupervised Adversarial Neural Networks for Cyber Security Transfer Learning
    Casey Kneale, Kolia Sadeghi
    http://arxiv.org/abs/1907.11129v1

    • [cs.LG]Simultaneous multi-view instance detection with learned geometric soft-constraints
    Ahmed Samy Nassar, Sebastien Lefevre, Jan D. Wegner
    http://arxiv.org/abs/1907.10892v1

    • [cs.LG]Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning
    Bilal Kartal, Pablo Hernandez-Leal, Matthew E. Taylor
    http://arxiv.org/abs/1907.10827v1

    • [cs.LG]The Good, the Bad and the Ugly: Augmenting a black-box model with expert knowledge
    Raoul Heese, Michał Walczak, Lukas Morand, Dirk Helm, Michael Bortz
    http://arxiv.org/abs/1907.11105v1

    • [cs.LG]The Truly Deep Graph Convolutional Networks for Node Classification
    Yu Rong, Wenbing Huang, Tingyang Xu, Junzhou Huang
    http://arxiv.org/abs/1907.10903v1

    • [cs.LG]Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph
    Gen Li, Yuantao Gu
    http://arxiv.org/abs/1907.10906v1

    • [cs.LG]Towards AutoML in the presence of Drift: first results
    Jorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales, Wei-Wei Tu, Yang Yu, Lisheng Sun-Hosoya, Isabelle Guyon, Michele Sebag
    http://arxiv.org/abs/1907.10772v1

    • [cs.LG]Towards Generalizing Sensorimotor Control Across Weather Conditions
    Qadeer Khan, Patrick Wenzel, Daniel Cremers, Laura Leal-Taixé
    http://arxiv.org/abs/1907.11025v1

    • [cs.LG]Unsupervised Domain Adaptation via Calibrating Uncertainties
    Ligong Han, Yang Zou, Ruijiang Gao, Lezi Wang, Dimitris Metaxas
    http://arxiv.org/abs/1907.11202v1

    • [cs.LO]On Uniform Equivalence of Epistemic Logic Programs
    Wolfgang Faber, Michael Morak, Stefan Woltran
    http://arxiv.org/abs/1907.10925v1

    • [cs.MA]A Framework for Monitoring Human Physiological Response during Human Robot Collaborative Task
    Celal Savur, Shitij Kumar, Ferat Sahin
    http://arxiv.org/abs/1907.10782v1

    • [cs.NE]Benchmarking HillVallEA for the GECCO 2019 Competition on Multimodal Optimization
    S. C. Maree, T. Alderliesten, P. A. N. Bosman
    http://arxiv.org/abs/1907.10988v1

    • [cs.RO]Experimentation on the motion of an obstacle avoiding robot
    Rakhmanov Ochilbek, Nzurumike Obianuju, Amina Sani, Rukayya Umar
    http://arxiv.org/abs/1907.11021v1

    • [cs.RO]Object Perception and Grasping in Open-Ended Domains
    S. Hamidreza Kasaei
    http://arxiv.org/abs/1907.10932v1

    • [cs.RO]Overview of Guidance, Navigation and Control System of the TeamIndus lunar lander
    Vishesh Vatsal, C. Barath, J. Yogeshwaran, Deepana Gandhi, Chhavilata Sahu, Karthic Balasubramanian, Shyam Mohan, Midhun S. Menon, P. Natarajan, Vivek Raghavan
    http://arxiv.org/abs/1907.10955v1

    • [cs.RO]Robot Learning of Shifting Objects for Grasping in Cluttered Environments
    Lars Berscheid, Pascal Meißner, Torsten Kröger
    http://arxiv.org/abs/1907.11035v1

    • [cs.RO]TuneNet: One-Shot Residual Tuning for System Identification and Sim-to-Real Robot Task Transfer
    Adam Allevato, Elaine Schaertl Short, Mitch Pryor, Andrea L. Thomaz
    http://arxiv.org/abs/1907.11200v1

    • [cs.RO]Weakly Supervised Recognition of Surgical Gestures
    Beatrice van Amsterdam, Hirenkumar Nakawala, Elena De Momi, Danail Stoyanov
    http://arxiv.org/abs/1907.10993v1

    • [cs.SE]An Empirical Analysis of the Python Package Index (PyPI)
    Ethan Bommarito, Michael Bommarito
    http://arxiv.org/abs/1907.11073v1

    • [cs.SI]Does Facebook Use Sensitive Data for Advertising Purposes? Worldwide Analysis and GDPR Impact
    Ángel Cuevas, José González Cabañas, Aritz Arrate, Rubén Cuevas
    http://arxiv.org/abs/1907.10672v1

    • [cs.SI]Real-time Event Detection on Social Data Streams
    Mateusz Fedoryszak, Brent Frederick, Vijay Rajaram, Changtao Zhong
    http://arxiv.org/abs/1907.11229v1

    • [eess.AS]Cross-Attention End-to-End ASR for Two-Party Conversations
    Suyoun Kim, Siddharth Dalmia, Florian Metze
    http://arxiv.org/abs/1907.10726v1

    • [eess.IV]Hetero-Modal Variational Encoder-Decoder for Joint Modality Completion and Segmentation
    Reuben Dorent, Samuel Joutard, Marc Modat, Sébastien Ourselin, Tom Vercauteren
    http://arxiv.org/abs/1907.11150v1

    • [eess.IV]Is Texture Predictive for Age and Sex in Brain MRI?
    Nick Pawlowski, Ben Glocker
    http://arxiv.org/abs/1907.10961v1

    • [eess.IV]Performance Evaluation of Two-layer lossless HDR Coding using Histogram Packing Technique under Various Tone-mapping Operators
    Hiroyuki Kobayashi, Hitoshi Kiya
    http://arxiv.org/abs/1907.10889v1

    • [eess.IV]Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification
    Yuan Xue, Qianying Zhou, Jiarong Ye, L. Rodney Long, Sameer Antani, Carl Cornwell, Zhiyun Xue, Xiaolei Huang
    http://arxiv.org/abs/1907.10655v1

    • [eess.SP]An Overview of Enhanced Massive MIMO with Array Signal Processing Techniques
    Mingjin Wang, Feifei Gao, Shi Jin, Hai Lin
    http://arxiv.org/abs/1907.09944v2

    • [hep-ph]MadMiner: Machine learning-based inference for particle physics
    Johann Brehmer, Felix Kling, Irina Espejo, Kyle Cranmer
    http://arxiv.org/abs/1907.10621v1

    • [math.OC]Safe Feature Elimination for Non-Negativity Constrained Convex Optimization
    James Folberth, Stephen Becker
    http://arxiv.org/abs/1907.10831v1

    • [math.PR]Conditional probability in Renyi spaces
    Gunnar Taraldsen
    http://arxiv.org/abs/1907.11038v1

    • [math.ST]Bootstrapping Networks with Latent Space Structure
    Keith Levin, Elizaveta Levina
    http://arxiv.org/abs/1907.10821v1

    • [math.ST]Density deconvolution under general assumptions on the distribution of measurement errors
    Denis Belomestny, Alexander Goldenshluger
    http://arxiv.org/abs/1907.11024v1

    • [physics.med-ph]Body-worn triaxial accelerometer coherence and reliability related to static posturography in unilateral vestibular failure
    M. Alessandrini, A. Micarelli, A. Viziano, I. Pavone, G. Costantini, D. Casali, F. Paolizzo, G. Saggio
    http://arxiv.org/abs/1907.11166v1

    • [physics.soc-ph]Influence and Betweenness in Flow Models of Complex Network Systems
    Olexandr Polishchuk
    http://arxiv.org/abs/1907.10667v1

    • [q-bio.NC]The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging
    Andrew Warrington, Arthur Spencer, Frank Wood
    http://arxiv.org/abs/1907.11075v1

    • [q-bio.PE]Complete maximum likelihood estimation for SEIR epidemic models: theoretical development
    Divine Wanduku, Chinmoy Rahul
    http://arxiv.org/abs/1907.10679v1

    • [quant-ph]Quantum Walk over a triangular lattice subject to Pachner move
    Aristote Quentin, Di Molfetta Giuseppe
    http://arxiv.org/abs/1907.10717v1

    • [stat.AP]Bayesian Analysis of Spatial Generalized Linear Mixed Models with Laplace Random Fields
    Adam Walder, Ephraim M. Hanks
    http://arxiv.org/abs/1907.11077v1

    • [stat.AP]Computational Phenotype Discovery via Probabilistic Independence
    Thomas A. Lasko, Diego A. Mesa
    http://arxiv.org/abs/1907.11051v1

    • [stat.AP]Fitting motion models to contextual player behavior
    Bartholomew Spencer, Karl Jackson, Sam Robertson
    http://arxiv.org/abs/1907.10762v1

    • [stat.AP]Teaching Split Plot Experiments With a Boomerang Tin
    Thomas Muehlenstaedt, Maria Lanzerath
    http://arxiv.org/abs/1907.10684v1

    • [stat.CO]BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic Likelihood
    Ziwen An, Leah F South, Christopher Drovandi
    http://arxiv.org/abs/1907.10940v1

    • [stat.CO]Particle Methods for Stochastic Differential Equation Mixed Effects Models
    Imke Botha, Robert Kohn, Christopher Drovandi
    http://arxiv.org/abs/1907.11017v1

    • [stat.CO]Transport Monte Carlo
    Leo L. Duan
    http://arxiv.org/abs/1907.10448v2

    • [stat.ME]Functional Models for Time-Varying Random Objects
    Paromita Dubey, Hans-Georg Mueller
    http://arxiv.org/abs/1907.10829v1

    • [stat.ME]JointAI: Joint Analysis and Imputation of Incomplete Data in R
    Nicole S. Erler, Dimitris Rizopoulos, Emmanuel M. E. H. Lesaffre
    http://arxiv.org/abs/1907.10867v1

    • [stat.ME]Learning binary undirected graph in low dimensional regime
    Daniela De Canditiis
    http://arxiv.org/abs/1907.11033v1

    • [stat.ME]New frontiers in Bayesian modeling using the INLA package in R
    Janet van Niekerk, Haakon Bakka, Haavard Rue, Olaf Schenk
    http://arxiv.org/abs/1907.10426v2

    • [stat.ME]Non-constant hazard ratios in randomized controlled trials with composite endpoints
    Jordi Cortés Martínez, Moisès Gómez Mateu, KyungMann Kim, Guadalupe Gómez Melis
    http://arxiv.org/abs/1907.10976v1

    • [stat.ME]On the bias of H-scores for comparing biclusters, and how to correct it
    Jacopo Di Iorio, Francesca Chiaromonte, Marzia A. Cremona
    http://arxiv.org/abs/1907.11142v1

    • [stat.ME]Transportability of Outcome Measurement Error Correction: from Validation Studies to Intervention Trials
    Benjamin Ackerman, Juned Siddique, Elizabeth A. Stuart
    http://arxiv.org/abs/1907.10722v1

    • [stat.ML]Deep Generative Quantile-Copula Models for Probabilistic Forecasting
    Ruofeng Wen, Kari Torkkola
    http://arxiv.org/abs/1907.10697v1

    • [stat.ML]Deep Learning Models to Predict Pediatric Asthma Emergency Department Visits
    Xiao Wang, Zhijie Wang, Yolande M. Pengetnze, Barry S. Lachman, Vikas Chowdhry
    http://arxiv.org/abs/1907.11195v1

    • [stat.ML]Domain Generalization via Multidomain Discriminant Analysis
    Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan
    http://arxiv.org/abs/1907.11216v1

    • [stat.ML]Fast generalization error bound of deep learning without scale invariance of activation functions
    Yoshikazu Terada, Ryoma Hirose
    http://arxiv.org/abs/1907.10900v1

    • [stat.ML]Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method
    Guihong Wan, Crystal Maung, Haim Schweitzer
    http://arxiv.org/abs/1907.11094v1

    • [stat.ML]Invariance reduces Variance: Understanding Data Augmentation in Deep Learning and Beyond
    Shuxiao Chen, Edgar Dobriban, Jane H Lee
    http://arxiv.org/abs/1907.10905v1