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
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• [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