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.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.GL - 一般文献 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.RO - 机器人学 cs.SD - 声音处理 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 math.FA - 泛函演算 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.ML - (统计)机器学习
• [cs.AI]An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types
• [cs.AI]Learning by Abstraction: The Neural State Machine
• [cs.AI]Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle
• [cs.CL]A Modular Task-oriented Dialogue System Using a Neural Mixture-of-Experts
• [cs.CL]Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition
• [cs.CL]Adaptive Margin Ranking Loss for Knowledge Graph Embeddings via a Correntropy Objective Function
• [cs.CL]Can Unconditional Language Models Recover Arbitrary Sentences?
• [cs.CL]Incrementalizing RASA’s Open-Source Natural Language Understanding Pipeline
• [cs.CL]Large Memory Layers with Product Keys
• [cs.CL]Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
• [cs.CL]MeetUp! A Corpus of Joint Activity Dialogues in a Visual Environment
• [cs.CL]Modelling the Socialization of Creative Agents in a Master-Apprentice Setting: The Case of Movie Title Puns
• [cs.CL]No Word is an Island — A Transformation Weighting Model for Semantic Composition
• [cs.CL]ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation
• [cs.CL]Self-Regulated Interactive Sequence-to-Sequence Learning
• [cs.CL]Semantic Parsing with Dual Learning
• [cs.CL]Vision-and-Dialog Navigation
• [cs.CR]Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
• [cs.CR]On Analysis of the Bitcoin and Prism Backbone Protocols
• [cs.CV]A Comparison of Super-Resolution and Nearest Neighbors Interpolation Applied to Object Detection on Satellite Data
• [cs.CV]A Deep Neural Network for Finger Counting and Numerosity Estimation
• [cs.CV]Activitynet 2019 Task 3: Exploring Contexts for Dense Captioning Events in Videos
• [cs.CV]Aesthetic Attributes Assessment of Images
• [cs.CV]Agile Domain Adaptation
• [cs.CV]BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
• [cs.CV]Cross-Domain Complementary Learning with Synthetic Data for Multi-Person Part Segmentation
• [cs.CV]Deep Active Learning for Axon-Myelin Segmentation on Histology Data
• [cs.CV]Diverse Trajectory Forecasting with Determinantal Point Processes
• [cs.CV]Dunhuang Grottoes Painting Dataset and Benchmark
• [cs.CV]Efficient Semantic Scene Completion Network with Spatial Group Convolution
• [cs.CV]Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces
• [cs.CV]FIRE: Unsupervised bi-directional inter-modality registration using deep networks
• [cs.CV]Fully Convolutional Networks for Handwriting Recognition
• [cs.CV]Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
• [cs.CV]Image-Based Size Analysis of Agglomerated and Partially Sintered Particles via Convolutional Neural Networks
• [cs.CV]Influence of Pointing on Learning to Count: A Neuro-Robotics Model
• [cs.CV]Micro-expression Action Unit Detection withSpatio-temporal Adaptive Pooling
• [cs.CV]Multifaceted Analysis of Fine-Tuning in Deep Model for Visual Recognition
• [cs.CV]My lips are concealed: Audio-visual speech enhancement through obstructions
• [cs.CV]Object Detection in Video with Spatial-temporal Context Aggregation
• [cs.CV]One Shot Learning for Deformable Medical Image Registration and Periodic Motion Tracking
• [cs.CV]Optimal Feature Transport for Cross-View Image Geo-Localization
• [cs.CV]Semi-supervised Feature-Level Attribute Manipulation for Fashion Image Retrieval
• [cs.CV]Single Image Super-Resolution via CNN Architectures and TV-TV Minimization
• [cs.CV]StrokeSave: A Novel, High-Performance Mobile Application for Stroke Diagnosis using Deep Learning and Computer Vision
• [cs.CV]Two-stream Spatiotemporal Feature for Video QA Task
• [cs.CY]Estimating Traffic Disruption Patterns with Volunteered Geographic Information
• [cs.DC]A Study of Network Congestion in Two Supercomputing High-Speed Interconnects
• [cs.DC]StakeCube: Combining Sharding and Proof-of-Stake to build Fork-free Secure Permissionless Distributed Ledgers
• [cs.DS]Analysis of Ward’s Method
• [cs.DS]Computational Concentration of Measure: Optimal Bounds, Reductions, and More
• [cs.DS]Quantum and Classical Algorithms for Approximate Submodular Function Minimization
• [cs.DS]Walking Randomly, Massively, and Efficiently
• [cs.GL]Kolmogorov complexity in the USSR (1975—1982): isolation and its end
• [cs.HC]Belief places and spaces: Mapping cognitive environments
• [cs.IR]Featured Snippets Results in Google Web Search: An Exploratory Study
• [cs.IR]Hierarchical Clustering Supported by Reciprocal Nearest Neighbors
• [cs.IR]Privileged Features Distillation for E-Commerce Recommendations
• [cs.IR]Productization Challenges of Contextual Multi-Armed Bandits
• [cs.IT]Computing sharp recovery structures for Locally Recoverable codes
• [cs.IT]Error Exponents for Asynchronous Multiple Access Channels. Controlled Asynchronism may Outperform Synchronism
• [cs.IT]Information-Centric Grant-Free Access for IoT Fog Networks: Edge vs Cloud Detection and Learning
• [cs.IT]Minimax Theorems for Finite Blocklength Lossy Joint Source-Channel Coding over an AVC
• [cs.IT]Recovery and Repair Schemes for Shift-XOR Regenerating Codes
• [cs.IT]Timely Cloud Computing: Preemption and Waiting
• [cs.IT]Using Chinese Characters To Generate Text-Based Passwords For Information Security
• [cs.LG]A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning
• [cs.LG]Amplifying Rényi Differential Privacy via Shuffling
• [cs.LG]Beyond Imitation: Generative and Variational Choreography via Machine Learning
• [cs.LG]Explaining an increase in predicted risk for clinical alerts
• [cs.LG]Fairness without Regret
• [cs.LG]Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
• [cs.LG]GraphSAINT: Graph Sampling Based Inductive Learning Method
• [cs.LG]Identifying Linear Models in Multi-Resolution Population Data using Minimum Description Length Principle to Predict Household Income
• [cs.LG]Interpretable Dynamics Models for Data-Efficient Reinforcement Learning
• [cs.LG]Making AI Forget You: Data Deletion in Machine Learning
• [cs.LG]Performance Boundary Identification for the Evaluation of Automated Vehicles using Gaussian Process Classification
• [cs.LG]Perturbation theory approach to study the latent space degeneracy of Variational Autoencoders
• [cs.LG]PreCall: A Visual Interface for Threshold Optimization in ML Model Selection
• [cs.LG]Profiling based Out-of-core Hybrid Method for Large Neural Networks
• [cs.LG]Provably Efficient Reinforcement Learning with Linear Function Approximation
• [cs.LG]Safe Policy Improvement with Soft Baseline Bootstrapping
• [cs.LG]Spatiotemporal Local Propagation
• [cs.LG]Time series cluster kernels to exploit informative missingness and incomplete label information
• [cs.LG]Time2Vec: Learning a Vector Representation of Time
• [cs.LG]Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology
• [cs.LG]Variance-Based Risk Estimations in Markov Processes via Transformation with State Lumping
• [cs.LO]ADDMC: Exact Weighted Model Counting with Algebraic Decision Diagrams
• [cs.MA]A Neural Architecture for Designing Truthful and Efficient Auctions
• [cs.RO]A Deep Reinforcement-Learning-based Driving Policy for Autonomous Road Vehicles
• [cs.RO]A Resource-Aware Approach to Collaborative Loop Closure Detection with Provable Performance Guarantees
• [cs.RO]Aerial Animal Biometrics: Individual Friesian Cattle Recovery and Visual Identification via an Autonomous UAV with Onboard Deep Inference
• [cs.RO]Incremental Semantic Mapping with Unsupervised On-line Learning
• [cs.RO]Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction
• [cs.RO]Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints
• [cs.RO]Online Inference and Detection of Curbs in Partially Occluded Scenes with Sparse LIDAR
• [cs.SD]Explicitly Conditioned Melody Generation: A Case Study with Interdependent RNNs
• [cs.SD]LakhNES: Improving multi-instrumental music generation with cross-domain pre-training
• [cs.SI]Evidential positive opinion influence measures for viral marketing
• [eess.AS]Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition
• [eess.IV]Assessing postural instability during cerebral hypoperfusion using sub-millimeter monocular 3D sway tracking
• [eess.IV]Deep-Learning for Tidemark Segmentation in Human Osteochondral Tissues Imaged with Micro-computed Tomography
• [eess.IV]Disease classification of macular Optical Coherence Tomography scans using deep learning software: validation on independent, multi-centre data
• [eess.IV]Edge Heuristic GAN for Non-uniform Blind Deblurring
• [eess.IV]Extension of Sinkhorn Method: Optimal Movement Estimation of Agents Moving at Constant Velocity
• [eess.IV]retina-VAE: Variationally Decoding the Spectrum of Macular Disease
• [eess.SP]Functional Brain Networks Discovery Using Dictionary Learning with Correlated Sparsity
• [eess.SP]Message passing-based link configuration in short range millimeter wave systems
• [eess.SP]Neural Network-based Equalizer by Utilizing Coding Gain in Advance
• [eess.SP]Terahertz Band: The Last Piece of RF Spectrum Puzzle for Communication Systems
• [eess.SP]Towards a Connected Sky: Performance of Beamforming with Down-tilted Antennas for Ground and UAV User Co-existence
• [math.FA]Super-resolution meets machine learning: approximation of measures
• [math.NA]Method of moments for 3-D single particle ab initio modeling with non-uniform distribution of viewing angles
• [math.NA]Three algorithms for solving high-dimensional fully-coupled FBSDEs through deep learning
• [math.OC]Adaptive Deep Learning for High Dimensional Hamilton-Jacobi-Bellman Equations
• [math.OC]Statistical inference for piecewise normal distributions and stochastic variational inequalities
• [math.ST]Directing Power Towards Sub-Alternatives
• [math.ST]Estimating the division rate from indirect measurements of single cells
• [math.ST]Nonparametric estimation of the conditional density function with right-censored and dependent data
• [q-bio.QM]Warfarin dose estimation on multiple datasets with automated hyperparameter optimisation and a novel software framework
• [quant-ph]Highly parallel algorithm for the Ising ground state searching problem
• [quant-ph]Learning to learn with quantum neural networks via classical neural networks
• [quant-ph]Machine Learning Kernel Method from a Quantum Generative Model
• [stat.AP]Fitting Prediction Rule Ensembles to Psychological Research Data: An Introduction and Tutorial
• [stat.AP]The HOG-FDA Approach with Mobile Phone Data to Modeling the Dynamic of People’s Presences in the City
• [stat.AP]The acute:chronic workload ratio: challenges and prospects for improvement
• [stat.ML]Change point detection for graphical models in presence of missing values
• [stat.ML]Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling
• [stat.ML]Low-rank matrix completion and denoising under Poisson noise
• [stat.ML]Multivariate Time Series Imputation with Variational Autoencoders
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• [cs.AI]An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types
Stefano V. Albrecht, Jacob W. Crandall, Subramanian Ramamoorthy
http://arxiv.org/abs/1907.05247v1
• [cs.AI]Learning by Abstraction: The Neural State Machine
Drew A. Hudson, Christopher D. Manning
http://arxiv.org/abs/1907.03950v2
• [cs.AI]Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle
Guojun Wu, Yanhua Li, Zhenming Liu, Jie Bao, Yu Zheng, Jieping Ye, Jun Luo
http://arxiv.org/abs/1907.05390v1
• [cs.CL]A Modular Task-oriented Dialogue System Using a Neural Mixture-of-Experts
Jiahuan Pei, Pengjie Ren, Maarten de Rijke
http://arxiv.org/abs/1907.05346v1
• [cs.CL]Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition
Xiaodong Cui, Michael Picheny
http://arxiv.org/abs/1907.04882v1
• [cs.CL]Adaptive Margin Ranking Loss for Knowledge Graph Embeddings via a Correntropy Objective Function
Mojtaba Nayyeri, Xiaotian Zhou, Sahar Vahdati, Hamed Shariat Yazdi, Jens Lehmann
http://arxiv.org/abs/1907.05336v1
• [cs.CL]Can Unconditional Language Models Recover Arbitrary Sentences?
Nishant Subramani, Sam Bowman, Kyunghyun Cho
http://arxiv.org/abs/1907.04944v1
• [cs.CL]Incrementalizing RASA’s Open-Source Natural Language Understanding Pipeline
Andrew Rafla, Casey Kennington
http://arxiv.org/abs/1907.05403v1
• [cs.CL]Large Memory Layers with Product Keys
Guillaume Lample, Alexandre Sablayrolles, Marc’Aurelio Ranzato, Ludovic Denoyer, Hervé Jégou
http://arxiv.org/abs/1907.05242v1
• [cs.CL]Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
Naveen Arivazhagan, Ankur Bapna, Orhan Firat, Dmitry Lepikhin, Melvin Johnson, Maxim Krikun, Mia Xu Chen, Yuan Cao, George Foster, Colin Cherry, Wolfgang Macherey, Zhifeng Chen, Yonghui Wu
http://arxiv.org/abs/1907.05019v1
• [cs.CL]MeetUp! A Corpus of Joint Activity Dialogues in a Visual Environment
Nikolai Ilinykh, Sina Zarrieß, David Schlangen
http://arxiv.org/abs/1907.05084v1
• [cs.CL]Modelling the Socialization of Creative Agents in a Master-Apprentice Setting: The Case of Movie Title Puns
Mika Hämäläinen, Khalid Alnajjar
http://arxiv.org/abs/1907.04954v1
• [cs.CL]No Word is an Island — A Transformation Weighting Model for Semantic Composition
Corina Dima, Daniël de Kok, Neele Witte, Erhard Hinrichs
http://arxiv.org/abs/1907.05048v1
• [cs.CL]ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation
Hainan Zhang, Yanyan Lan, Liang Pang, Jiafeng Guo, Xueqi Cheng
http://arxiv.org/abs/1907.05339v1
• [cs.CL]Self-Regulated Interactive Sequence-to-Sequence Learning
Julia Kreutzer, Stefan Riezler
http://arxiv.org/abs/1907.05190v1
• [cs.CL]Semantic Parsing with Dual Learning
Ruisheng Cao, Su Zhu, Chen Liu, Jieyu Li, Kai Yu
http://arxiv.org/abs/1907.05343v1
• [cs.CL]Vision-and-Dialog Navigation
Jesse Thomason, Michael Murray, Maya Cakmak, Luke Zettlemoyer
http://arxiv.org/abs/1907.04957v1
• [cs.CR]Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
Yulong Cao, Chaowei Xiao, Dawei Yang, Jing Fang, Ruigang Yang, Mingyan Liu, Bo Li
http://arxiv.org/abs/1907.05418v1
• [cs.CR]On Analysis of the Bitcoin and Prism Backbone Protocols
Jing Li, Dongning Guo
http://arxiv.org/abs/1907.05016v1
• [cs.CV]A Comparison of Super-Resolution and Nearest Neighbors Interpolation Applied to Object Detection on Satellite Data
Evan Koester, Cem Safak Sahin
http://arxiv.org/abs/1907.05283v1
• [cs.CV]A Deep Neural Network for Finger Counting and Numerosity Estimation
Leszek Pecyna, Angelo Cangelosi, Alessandro Di Nuovo
http://arxiv.org/abs/1907.05270v1
• [cs.CV]Activitynet 2019 Task 3: Exploring Contexts for Dense Captioning Events in Videos
Shizhe Chen, Yuqing Song, Yida Zhao, Qin Jin, Zhaoyang Zeng, Bei Liu, Jianlong Fu, Alexander Hauptmann
http://arxiv.org/abs/1907.05092v1
• [cs.CV]Aesthetic Attributes Assessment of Images
Xin Jin, Le Wu, Geng Zhao, Xiaodong Li, Xiaokun Zhang, Shiming Ge, Dongqing Zou, Bin Zhou, Xinghui Zhou
http://arxiv.org/abs/1907.04983v1
• [cs.CV]Agile Domain Adaptation
Jingjing Li, Mengmeng Jing, Yue Xie, Ke Lu, Zi Huang
http://arxiv.org/abs/1907.04978v1
• [cs.CV]BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
Valentin Bazarevsky, Yury Kartynnik, Andrey Vakunov, Karthik Raveendran, Matthias Grundmann
http://arxiv.org/abs/1907.05047v1
• [cs.CV]Cross-Domain Complementary Learning with Synthetic Data for Multi-Person Part Segmentation
Kevin Lin, Lijuan Wang, Kun Luo, Yinpeng Chen, Zicheng Liu, Ming-Ting Sun
http://arxiv.org/abs/1907.05193v1
• [cs.CV]Deep Active Learning for Axon-Myelin Segmentation on Histology Data
Melanie Lubrano di Scandalea, Christian S. Perone, Mathieu Boudreau, Julien Cohen-Adad
http://arxiv.org/abs/1907.05143v1
• [cs.CV]Diverse Trajectory Forecasting with Determinantal Point Processes
Ye Yuan, Kris Kitani
http://arxiv.org/abs/1907.04967v1
• [cs.CV]Dunhuang Grottoes Painting Dataset and Benchmark
Tianxiu Yu, Shijie Zhang, Cong Lin, Shaodi You, Jian Wu, Jiawan Zhang, Xiaohong Ding, Huili An
http://arxiv.org/abs/1907.04589v2
• [cs.CV]Efficient Semantic Scene Completion Network with Spatial Group Convolution
Jiahui Zhang, Hao Zhao, Anbang Yao, Yurong Chen, Li Zhang, Hongen Liao
http://arxiv.org/abs/1907.05091v1
• [cs.CV]Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces
Huazhu Fu, Boyang Wang, Jianbing Shen, Shanshan Cui, Yanwu Xu, Jiang Liu, Ling Shao
http://arxiv.org/abs/1907.05345v1
• [cs.CV]FIRE: Unsupervised bi-directional inter-modality registration using deep networks
Chengjia Wang, Giorgos Papanastasiou, Agisilaos Chartsias, Grzegorz Jacenkow, Sotirios A. Tsaftaris, Heye Zhang
http://arxiv.org/abs/1907.05062v1
• [cs.CV]Fully Convolutional Networks for Handwriting Recognition
Felipe Petroski Such, Dheeraj Peri, Frank Brockler, Paul Hutkowski, Raymond Ptucha
http://arxiv.org/abs/1907.04888v1
• [cs.CV]Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
Xiaolong Jiang, Peizhao Li, Yanjing Li, Xiantong Zhen
http://arxiv.org/abs/1907.05315v1
• [cs.CV]Image-Based Size Analysis of Agglomerated and Partially Sintered Particles via Convolutional Neural Networks
Max Frei, Frank Einar Kruis
http://arxiv.org/abs/1907.05112v1
• [cs.CV]Influence of Pointing on Learning to Count: A Neuro-Robotics Model
Leszek Pecyna, Angelo Cangelosi
http://arxiv.org/abs/1907.05269v1
• [cs.CV]Micro-expression Action Unit Detection withSpatio-temporal Adaptive Pooling
Yante Li, Xiaohua Huang, Guoying Zhao
http://arxiv.org/abs/1907.05023v1
• [cs.CV]Multifaceted Analysis of Fine-Tuning in Deep Model for Visual Recognition
Xiangyang Li, Luis Herranz, Shuqiang Jiang
http://arxiv.org/abs/1907.05099v1
• [cs.CV]My lips are concealed: Audio-visual speech enhancement through obstructions
Triantafyllos Afouras, Joon Son Chung, Andrew Zisserman
http://arxiv.org/abs/1907.04975v1
• [cs.CV]Object Detection in Video with Spatial-temporal Context Aggregation
Hao Luo, Lichao Huang, Han Shen, Yuan Li, Chang Huang, Xinggang Wang
http://arxiv.org/abs/1907.04988v1
• [cs.CV]One Shot Learning for Deformable Medical Image Registration and Periodic Motion Tracking
Tobias Fechter, Dimos Baltas
http://arxiv.org/abs/1907.04641v2
• [cs.CV]Optimal Feature Transport for Cross-View Image Geo-Localization
Yujiao Shi, Xin Yu, Liu Liu, Tong Zhang, Hongdong Li
http://arxiv.org/abs/1907.05021v1
• [cs.CV]Semi-supervised Feature-Level Attribute Manipulation for Fashion Image Retrieval
Minchul Shin, Sanghyuk Park, Taeksoo Kim
http://arxiv.org/abs/1907.05007v1
• [cs.CV]Single Image Super-Resolution via CNN Architectures and TV-TV Minimization
Marija Vella, João F. C. Mota
http://arxiv.org/abs/1907.05380v1
• [cs.CV]StrokeSave: A Novel, High-Performance Mobile Application for Stroke Diagnosis using Deep Learning and Computer Vision
Ankit Gupta
http://arxiv.org/abs/1907.05358v1
• [cs.CV]Two-stream Spatiotemporal Feature for Video QA Task
Chiwan Song, Woobin Im, Sung-eui Yoon
http://arxiv.org/abs/1907.05006v1
• [cs.CY]Estimating Traffic Disruption Patterns with Volunteered Geographic Information
Chico Q. Camargo, Jonathan Bright, Graham McNeill, Sridhar Raman, Scott A. Hale
http://arxiv.org/abs/1907.05162v1
• [cs.DC]A Study of Network Congestion in Two Supercomputing High-Speed Interconnects
Saurabh Jha, Archit Patke, Jim Brandt, Ann Gentile, Mike Showerman, Eric Roman, Zbigniew T. Kalbarczyk, William T. Kramer, Ravishankar K. Iyer
http://arxiv.org/abs/1907.05312v1
• [cs.DC]StakeCube: Combining Sharding and Proof-of-Stake to build Fork-free Secure Permissionless Distributed Ledgers
Antoine Durand, Emmanuelle Anceaume, Romaric Ludinard
http://arxiv.org/abs/1907.05314v1
• [cs.DS]Analysis of Ward’s Method
Anna Großwendt, Heiko Röglin, Melanie Schmidt
http://arxiv.org/abs/1907.05094v1
• [cs.DS]Computational Concentration of Measure: Optimal Bounds, Reductions, and More
Omid Etesami, Saeed Mahloujifar, Mohammad Mahmoody
http://arxiv.org/abs/1907.05401v1
• [cs.DS]Quantum and Classical Algorithms for Approximate Submodular Function Minimization
Yassine Hamoudi, Patrick Rebentrost, Ansis Rosmanis, Miklos Santha
http://arxiv.org/abs/1907.05378v1
• [cs.DS]Walking Randomly, Massively, and Efficiently
Jakub Łącki, Slobodan Mitrović, Krzysztof Onak, Piotr Sankowski
http://arxiv.org/abs/1907.05391v1
• [cs.GL]Kolmogorov complexity in the USSR (1975—1982): isolation and its end
V. V. V’yugin
http://arxiv.org/abs/1907.05056v1
• [cs.HC]Belief places and spaces: Mapping cognitive environments
Philip Feldman, Aaron Dant, Wayne Lutters
http://arxiv.org/abs/1907.04191v2
• [cs.IR]Featured Snippets Results in Google Web Search: An Exploratory Study
Artur Strzelecki, Paulina Rutecka
http://arxiv.org/abs/1907.04891v1
• [cs.IR]Hierarchical Clustering Supported by Reciprocal Nearest Neighbors
Wen-Bo Xie, Yan-Li Lee, Cong Wang, Duan-Bing Chen, Tao Zhou
http://arxiv.org/abs/1907.04915v1
• [cs.IR]Privileged Features Distillation for E-Commerce Recommendations
Chen Xu, Quan Li, Junfeng Ge, Jinyang Gao, Xiaoyong Yang, Changhua Pei, Hanxiao Sun, Wenwu Ou
http://arxiv.org/abs/1907.05171v1
• [cs.IR]Productization Challenges of Contextual Multi-Armed Bandits
David Abensur, Ivan Balashov, Shaked Bar, Ronny Lempel, Nurit Moscovici, Ilan Orlov, Danny Rosenstein, Ido Tamir
http://arxiv.org/abs/1907.04884v1
• [cs.IT]Computing sharp recovery structures for Locally Recoverable codes
Irene Marquez-Corbella, Edgar Martinez-Moro, Carlos Munuera
http://arxiv.org/abs/1907.05316v1
• [cs.IT]Error Exponents for Asynchronous Multiple Access Channels. Controlled Asynchronism may Outperform Synchronism
Lóránt Farkas, Tamás Kói
http://arxiv.org/abs/1907.05139v1
• [cs.IT]Information-Centric Grant-Free Access for IoT Fog Networks: Edge vs Cloud Detection and Learning
Rahif Kassab, Osvaldo Simeone, Petar Popovski
http://arxiv.org/abs/1907.05182v1
• [cs.IT]Minimax Theorems for Finite Blocklength Lossy Joint Source-Channel Coding over an AVC
Anuj S. Vora, Ankur A. Kulkarni
http://arxiv.org/abs/1907.05324v1
• [cs.IT]Recovery and Repair Schemes for Shift-XOR Regenerating Codes
Ximing Fu, Shenghao Yang, Zhiqing Xiao
http://arxiv.org/abs/1907.05058v1
• [cs.IT]Timely Cloud Computing: Preemption and Waiting
Ahmed Arafa, Roy D. Yates, H. Vincent Poor
http://arxiv.org/abs/1907.05408v1
• [cs.IT]Using Chinese Characters To Generate Text-Based Passwords For Information Security
Bing Yao, Yarong Mu, Yirong Sun, Hui Sun, Xiaohui Zhang, Hongyu Wang, Jing Su, Mingjun Zhang, Sihua Yang, Meimei Zhao, Xiaomin Wang, Fei Ma, Ming Yao, Chao Yang, Jianming Xie
http://arxiv.org/abs/1907.05406v1
• [cs.LG]A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning
Nicholas C. Landolfi, Garrett Thomas, Tengyu Ma
http://arxiv.org/abs/1907.04964v1
• [cs.LG]Amplifying Rényi Differential Privacy via Shuffling
Eloïse Berthier, Sai Praneeth Karimireddy
http://arxiv.org/abs/1907.05156v1
• [cs.LG]Beyond Imitation: Generative and Variational Choreography via Machine Learning
Mariel Pettee, Chase Shimmin, Douglas Duhaime, Ilya Vidrin
http://arxiv.org/abs/1907.05297v1
• [cs.LG]Explaining an increase in predicted risk for clinical alerts
Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew Dai, Michael Howell, Greg Corrado, Claire Cui, Moritz Hardt
http://arxiv.org/abs/1907.04911v1
• [cs.LG]Fairness without Regret
Marcus Hutter
http://arxiv.org/abs/1907.05159v1
• [cs.LG]Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
Mathias Kraus, Stefan Feuerriegel
http://arxiv.org/abs/1907.05146v1
• [cs.LG]GraphSAINT: Graph Sampling Based Inductive Learning Method
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna
http://arxiv.org/abs/1907.04931v1
• [cs.LG]Identifying Linear Models in Multi-Resolution Population Data using Minimum Description Length Principle to Predict Household Income
Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, Suttipong Thajchayapong
http://arxiv.org/abs/1907.05234v1
• [cs.LG]Interpretable Dynamics Models for Data-Efficient Reinforcement Learning
Markus Kaiser, Clemens Otte, Thomas Runkler, Carl Henrik Ek
http://arxiv.org/abs/1907.04902v1
• [cs.LG]Making AI Forget You: Data Deletion in Machine Learning
Antonio Ginart, Melody Guan, Gregory Valiant, James Zou
http://arxiv.org/abs/1907.05012v1
• [cs.LG]Performance Boundary Identification for the Evaluation of Automated Vehicles using Gaussian Process Classification
Felix Batsch, Alireza Daneshkhah, Madeline Cheah, Stratis Kanarachos, Anthony Baxendale
http://arxiv.org/abs/1907.05364v1
• [cs.LG]Perturbation theory approach to study the latent space degeneracy of Variational Autoencoders
Helena Andrés-Terré, Pietro Lió
http://arxiv.org/abs/1907.05267v1
• [cs.LG]PreCall: A Visual Interface for Threshold Optimization in ML Model Selection
Christoph Kinkeldey, Claudia Müller-Birn, Tom Gülenman, Jesse Josua Benjamin, Aaron Halfaker
http://arxiv.org/abs/1907.05131v1
• [cs.LG]Profiling based Out-of-core Hybrid Method for Large Neural Networks
Yuki Ito, Haruki Imai, Tung Le Duc, Yasushi Negishi, Kiyokuni Kawachiya, Ryo Matsumiya, Toshio Endo
http://arxiv.org/abs/1907.05013v1
• [cs.LG]Provably Efficient Reinforcement Learning with Linear Function Approximation
Chi Jin, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan
http://arxiv.org/abs/1907.05388v1
• [cs.LG]Safe Policy Improvement with Soft Baseline Bootstrapping
Kimia Nadjahi, Romain Laroche, Rémi Tachet des Combes
http://arxiv.org/abs/1907.05079v1
• [cs.LG]Spatiotemporal Local Propagation
Alessandro Betti, Marco Gori
http://arxiv.org/abs/1907.05106v1
• [cs.LG]Time series cluster kernels to exploit informative missingness and incomplete label information
Karl Øyvind Mikalsen, Cristina Soguero-Ruiz, Filippo Maria Bianchi, Arthur Revhaug, Robert Jenssen
http://arxiv.org/abs/1907.05251v1
• [cs.LG]Time2Vec: Learning a Vector Representation of Time
Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali, Janahan Ramanan, Jaspreet Sahota, Sanjay Thakur, Stella Wu, Cathal Smyth, Pascal Poupart, Marcus Brubaker
http://arxiv.org/abs/1907.05321v1
• [cs.LG]Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology
Nima Dehmamy, Albert-László Barabási, Rose Yu
http://arxiv.org/abs/1907.05008v1
• [cs.LG]Variance-Based Risk Estimations in Markov Processes via Transformation with State Lumping
Shuai Ma, Jia Yuan Yu
http://arxiv.org/abs/1907.05231v1
• [cs.LO]ADDMC: Exact Weighted Model Counting with Algebraic Decision Diagrams
Jeffrey M. Dudek, Vu H. N. Phan, Moshe Y. Vardi
http://arxiv.org/abs/1907.05000v1
• [cs.MA]A Neural Architecture for Designing Truthful and Efficient Auctions
Andrea Tacchetti, DJ Strouse, Marta Garnelo, Thore Graepel, Yoram Bachrach
http://arxiv.org/abs/1907.05181v1
• [cs.RO]A Deep Reinforcement-Learning-based Driving Policy for Autonomous Road Vehicles
Konstantinos Makantasis, Maria Kontorinaki, Ioannis Nikolos
http://arxiv.org/abs/1907.05246v1
• [cs.RO]A Resource-Aware Approach to Collaborative Loop Closure Detection with Provable Performance Guarantees
Yulun Tian, Kasra Khosoussi, Jonathan P. How
http://arxiv.org/abs/1907.04904v1
• [cs.RO]Aerial Animal Biometrics: Individual Friesian Cattle Recovery and Visual Identification via an Autonomous UAV with Onboard Deep Inference
William Andrew, Colin Greatwood, Tilo Burghardt
http://arxiv.org/abs/1907.05310v1
• [cs.RO]Incremental Semantic Mapping with Unsupervised On-line Learning
Ygor C. N. Sousa, Hansenclever F. Bassani
http://arxiv.org/abs/1907.04001v2
• [cs.RO]Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction
Weiming Zhi, Lionel Ott, Fabio Ramos
http://arxiv.org/abs/1907.05127v1
• [cs.RO]Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints
Arbaaz Khan, Chi Zhang, Shuo Li, Jiayue Wu, Brent Schlotfeldt, Sarah Y. Tang, Alejandro Ribeiro, Osbert Bastani, Vijay Kumar
http://arxiv.org/abs/1907.05300v1
• [cs.RO]Online Inference and Detection of Curbs in Partially Occluded Scenes with Sparse LIDAR
Tarlan Suleymanov, Lars Kunze, Paul Newman
http://arxiv.org/abs/1907.05375v1
• [cs.SD]Explicitly Conditioned Melody Generation: A Case Study with Interdependent RNNs
Benjamin Genchel, Ashis Pati, Alexander Lerch
http://arxiv.org/abs/1907.05208v1
• [cs.SD]LakhNES: Improving multi-instrumental music generation with cross-domain pre-training
Chris Donahue, Huanru Henry Mao, Yiting Ethan Li, Garrison W. Cottrell, Julian McAuley
http://arxiv.org/abs/1907.04868v1
• [cs.SI]Evidential positive opinion influence measures for viral marketing
Siwar Jendoubi, Arnaud Martin
http://arxiv.org/abs/1907.05028v1
• [eess.AS]Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition
Khoi-Nguyen C. Mac, Xiaodong Cui, Wei Zhang, Michael Picheny
http://arxiv.org/abs/1907.04887v1
• [eess.IV]Assessing postural instability during cerebral hypoperfusion using sub-millimeter monocular 3D sway tracking
Robert Amelard, Kevin R Murray, Eric T Hedge, Taylor W Cleworth, Mamiko Noguchi, Andrew Laing, Richard L Hughson
http://arxiv.org/abs/1907.05376v1
• [eess.IV]Deep-Learning for Tidemark Segmentation in Human Osteochondral Tissues Imaged with Micro-computed Tomography
Aleksei Tiulpin, Mikko Finnilä, Petri Lehenkari, Heikki J. Nieminen, Simo Saarakkala
http://arxiv.org/abs/1907.05089v1
• [eess.IV]Disease classification of macular Optical Coherence Tomography scans using deep learning software: validation on independent, multi-centre data
Kanwal K. Bhatia, Mark S. Graham, Louise Terry, Ashley Wood, Paris Tranos, Sameer Trikha, Nicolas Jaccard
http://arxiv.org/abs/1907.05164v1
• [eess.IV]Edge Heuristic GAN for Non-uniform Blind Deblurring
Shuai Zheng, Zhenfeng Zhu, Jian Cheng, Yandong Guo, Yao Zhao
http://arxiv.org/abs/1907.05185v1
• [eess.IV]Extension of Sinkhorn Method: Optimal Movement Estimation of Agents Moving at Constant Velocity
Daigo Okada, Naotoshi Nakamura, Takuya Wada, Ayako Iwasaki, Ryo Yamada
http://arxiv.org/abs/1907.05036v1
• [eess.IV]retina-VAE: Variationally Decoding the Spectrum of Macular Disease
Stephen G. Odaibo
http://arxiv.org/abs/1907.05195v1
• [eess.SP]Functional Brain Networks Discovery Using Dictionary Learning with Correlated Sparsity
Mohsen Joneidi
http://arxiv.org/abs/1907.03929v2
• [eess.SP]Message passing-based link configuration in short range millimeter wave systems
Nitin Jonathan Myers, Jarkko Kaleva, Antti Tölli, Robert W. Heath Jr
http://arxiv.org/abs/1907.05009v1
• [eess.SP]Neural Network-based Equalizer by Utilizing Coding Gain in Advance
Chieh-Fang Teng, Han-Mo Ou, An-Yeu Wu
http://arxiv.org/abs/1907.04980v1
• [eess.SP]Terahertz Band: The Last Piece of RF Spectrum Puzzle for Communication Systems
Hadeel Elayan, Osama Amin, Basem Shihada, Raed M. Shubair, Mohamed-Slim Alouini
http://arxiv.org/abs/1907.05043v1
• [eess.SP]Towards a Connected Sky: Performance of Beamforming with Down-tilted Antennas for Ground and UAV User Co-existence
Ramy Amer, Walid Saad, Nicola Marchetti
http://arxiv.org/abs/1907.05085v1
• [math.FA]Super-resolution meets machine learning: approximation of measures
H. N. Mhaskar
http://arxiv.org/abs/1907.04895v1
• [math.NA]Method of moments for 3-D single particle ab initio modeling with non-uniform distribution of viewing angles
Nir Sharon, Joe Kileel, Yuehaw Khoo, Boris Landa, Amit Singer
http://arxiv.org/abs/1907.05377v1
• [math.NA]Three algorithms for solving high-dimensional fully-coupled FBSDEs through deep learning
Shaolin Ji, Shige Peng, Ying Peng, Xichuan Zhang
http://arxiv.org/abs/1907.05327v1
• [math.OC]Adaptive Deep Learning for High Dimensional Hamilton-Jacobi-Bellman Equations
Tenavi Nakamura-Zimmerer, Qi Gong, Wei Kang
http://arxiv.org/abs/1907.05317v1
• [math.OC]Statistical inference for piecewise normal distributions and stochastic variational inequalities
Shu Lu, Hongsheng Liu
http://arxiv.org/abs/1907.05353v1
• [math.ST]Directing Power Towards Sub-Alternatives
Nick Koning
http://arxiv.org/abs/1907.05077v1
• [math.ST]Estimating the division rate from indirect measurements of single cells
Marie Doumic, Adélaïde Olivier, Lydia Robert
http://arxiv.org/abs/1907.05108v1
• [math.ST]Nonparametric estimation of the conditional density function with right-censored and dependent data
Xianzhu Xiong, Meijuan Ou
http://arxiv.org/abs/1907.04956v1
• [q-bio.QM]Warfarin dose estimation on multiple datasets with automated hyperparameter optimisation and a novel software framework
Gianluca Truda, Patrick Marais
http://arxiv.org/abs/1907.05363v1
• [quant-ph]Highly parallel algorithm for the Ising ground state searching problem
A. Yavorsky, L. A. Markovich, E. A. Polyakov, A. N. Rubtsov
http://arxiv.org/abs/1907.05124v1
• [quant-ph]Learning to learn with quantum neural networks via classical neural networks
Guillaume Verdon, Michael Broughton, Jarrod R. McClean, Kevin J. Sung, Ryan Babbush, Zhang Jiang, Hartmut Neven, Masoud Mohseni
http://arxiv.org/abs/1907.05415v1
• [quant-ph]Machine Learning Kernel Method from a Quantum Generative Model
Przemysław Sadowski
http://arxiv.org/abs/1907.05103v1
• [stat.AP]Fitting Prediction Rule Ensembles to Psychological Research Data: An Introduction and Tutorial
Marjolein Fokkema, Carolin Strobl
http://arxiv.org/abs/1907.05302v1
• [stat.AP]The HOG-FDA Approach with Mobile Phone Data to Modeling the Dynamic of People’s Presences in the City
Rodolfo Metulini, Maurizio Carpita
http://arxiv.org/abs/1907.05026v1
• [stat.AP]The acute:chronic workload ratio: challenges and prospects for improvement
Chinchin Wang, Jorge Trejo Vargas, Tyrel Stokes, Russell Steele, Ian Shrier
http://arxiv.org/abs/1907.05326v1
• [stat.ML]Change point detection for graphical models in presence of missing values
Malte Londschien, Solt Kovács, Peter Bühlmann
http://arxiv.org/abs/1907.05409v1
• [stat.ML]Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling
Nicholas Sterge, Bharath Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi
http://arxiv.org/abs/1907.05226v1
• [stat.ML]Low-rank matrix completion and denoising under Poisson noise
Andrew D. McRae, Mark A. Davenport
http://arxiv.org/abs/1907.05325v1
• [stat.ML]Multivariate Time Series Imputation with Variational Autoencoders
Vincent Fortuin, Gunnar Rätsch, Stephan Mandt
http://arxiv.org/abs/1907.04155v2