cs.AI - 人工智能

    cs.CG - 计算几何学 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.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.FA - 泛函演算 math.OC - 优化与控制 math.ST - 统计理论 nlin.AO - 适应和自组织系统 physics.data-an - 数据分析、 统计和概率 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]A flexible integer linear programming formulation for scheduling clinician on-call service in hospitals
    • [cs.AI]MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming
    • [cs.AI]Planning for Goal-Oriented Dialogue Systems
    • [cs.AI]Reflecting After Learning for Understanding
    • [cs.CG]Adaptive Partitioning for Template Functions on Persistence Diagrams
    • [cs.CL]A Mutual Information Maximization Perspective of Language Representation Learning
    • [cs.CL]Concept Pointer Network for Abstractive Summarization
    • [cs.CL]Controlling Utterance Length in NMT-based Word Segmentation with Attention
    • [cs.CL]End-to-End Speech Recognition: A review for the French Language
    • [cs.CL]Follow Alice into the Rabbit Hole: Giving Dialogue Agents Understanding of Human Level Attributes
    • [cs.CL]HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion
    • [cs.CL]Learning to Answer Subjective, Specific Product-Related Queries using Customer Reviews by Neural Domain Adaptation
    • [cs.CL]Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification
    • [cs.CL]Model Compression with Two-stage Multi-teacher Knowledge Distillation for Web Question Answering System
    • [cs.CL]RTFM: Generalising to Novel Environment Dynamics via Reading
    • [cs.CL]Relational Graph Representation Learning for Open-Domain Question Answering
    • [cs.CL]Towards Computing Inferences from English News Headlines
    • [cs.CL]Unsupervised Context Rewriting for Open Domain Conversation
    • [cs.CL]Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
    • [cs.CR]Analysis of Nakamoto Consensus, Revisited
    • [cs.CV]A Dataset of Multi-Illumination Images in the Wild
    • [cs.CV]A novel centroid update approach for clustering-based superpixel method and superpixel-based edge detection
    • [cs.CV]AFO-TAD: Anchor-free One-Stage Detector for Temporal Action Detection
    • [cs.CV]Automatic Data Augmentation by Learning the Deterministic Policy
    • [cs.CV]BOBBY2: Buffer Based Robust High-Speed Object Tracking
    • [cs.CV]Deep Weakly-Supervised Domain Adaptation for Pain Localization in Videos
    • [cs.CV]Diversity in Fashion Recommendation using Semantic Parsing
    • [cs.CV]Eye in the Sky: Drone-Based Object Tracking and 3D Localization
    • [cs.CV]Illumination-Based Data Augmentation for Robust Background Subtraction
    • [cs.CV]Image Deconvolution with Deep Image and Kernel Priors
    • [cs.CV]Investigating Task-driven Latent Feasibility for Nonconvex Image Modeling
    • [cs.CV]KerCNNs: biologically inspired lateral connections for classification of corrupted images
    • [cs.CV]Multimodal Image Super-resolution via Deep Unfolding with Side Information
    • [cs.CV]PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing
    • [cs.CV]RPBA — Robust Parallel Bundle Adjustment Based on Covariance Information
    • [cs.CV]Single and Cross-Dimensional Feature Detection and Description: An Evaluation
    • [cs.CV]Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data
    • [cs.CV]Toward 3D Object Reconstruction from Stereo Images
    • [cs.CV]Understanding Deep Networks via Extremal Perturbations and Smooth Masks
    • [cs.CV]Unsupervised Multi-Task Feature Learning on Point Clouds
    • [cs.DC]A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit
    • [cs.DC]Benefits of Stabilization versus Rollback in Eventually Consistent Key-Value Stores
    • [cs.DC]DLB: Deep Learning Based Load Balancing
    • [cs.DS]Weighted Edge Sampling for Static Graphs
    • [cs.IR]Attentive Knowledge Graph Embedding for Personalized Recommendation
    • [cs.IR]Entity Summarization: State of the Art and Future Challenges
    • [cs.IT]Distributed Hypothesis Testing with Variable-Length Coding
    • [cs.IT]Functional Epsilon Entropy
    • [cs.IT]Infinite families of near MDS codes holding $t$-designs
    • [cs.IT]Obfuscation via Information Density Estimation
    • [cs.IT]Secure Coded Caching with Colluding Users
    • [cs.LG]$b$-Bit Sketch Trie: Scalable Similarity Search on Integer Sketches
    • [cs.LG]A Deep Learning-based Framework for the Detection of Schools of Herring in Echograms
    • [cs.LG]A Topological “Reading” Lesson: Classification of MNIST using TDA
    • [cs.LG]Anatomically-Informed Data Augmentation for functional MRI with Applications to Deep Learning
    • [cs.LG]Autonomous exploration for navigating in non-stationary CMPs
    • [cs.LG]Deep Sub-Ensembles for Fast Uncertainty Estimation in Image Classification
    • [cs.LG]Enforcing Linearity in DNN succours Robustness and Adversarial Image Generation
    • [cs.LG]Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
    • [cs.LG]First-Order Preconditioning via Hypergradient Descent
    • [cs.LG]Fully Parallel Hyperparameter Search: Reshaped Space-Filling
    • [cs.LG]Graph Convolutional Policy for Solving Tree Decomposition via Reinforcement Learning Heuristics
    • [cs.LG]Implicit Context-aware Learning and Discovery for Streaming Data Analytics
    • [cs.LG]JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation
    • [cs.LG]Learning Compositional Koopman Operators for Model-Based Control
    • [cs.LG]Masked Gradient-Based Causal Structure Learning
    • [cs.LG]Mirror Descent View for Neural Network Quantization
    • [cs.LG]Multi Label Restricted Boltzmann Machine for Non-Intrusive Load Monitoring
    • [cs.LG]Multi-View Reinforcement Learning
    • [cs.LG]On Connections between Constrained Optimization and Reinforcement Learning
    • [cs.LG]On the Difficulty of Warm-Starting Neural Network Training
    • [cs.LG]On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation
    • [cs.LG]Point Process Flows
    • [cs.LG]Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data
    • [cs.LG]Scheduling the Learning Rate via Hypergradients: New Insights and a New Algorithm
    • [cs.LG]Scoring-Aggregating-Planning: Learning task-agnostic priors from interactions and sparse rewards for zero-shot generalization
    • [cs.LG]Supervised Learning Approach to Approximate Nearest Neighbor Search
    • [cs.LG]Texture Bias Of CNNs Limits Few-Shot Classification Performance
    • [cs.LG]VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
    • [cs.NE]Efficient Computation of Probabilistic Dominance in Robust Multi-Objective Optimization
    • [cs.NI]D2D-Enabled Mobile User Edge Caching: A Multi-Winner Auction Approach
    • [cs.NI]FLIP:FLexible IoT Path Programming Framework for Large-scale IoT
    • [cs.RO]Fast Local Planning and Mapping in Unknown Off-Road Terrain
    • [cs.RO]Learning Continuous Occupancy Maps with the Ising Process Model
    • [cs.RO]Map-Predictive Motion Planning in Unknown Environments
    • [cs.RO]Online Learning in Planar Pushing with Combined Prediction Model
    • [cs.RO]Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process
    • [cs.SI]SGP: Spotting Groups Polluting the Online Political Discourse
    • [eess.IV]Attention Mechanism Enhanced Kernel Prediction Networks for Denoising of Burst Images
    • [eess.IV]OpenDenoising: an Extensible Benchmark for Building Comparative Studies of Image Denoisers
    • [eess.IV]SDCNet: Smoothed Dense-Convolution Network for Restoring Low-Dose Cerebral CT Perfusion
    • [eess.SP]Cooperative Beamforming in Cognitive Radio Relay Networks Using Amplify-and-Forward Relaying Technique
    • [eess.SP]Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT
    • [math.FA]On the perturbation series for eigenvalues and eigenprojections
    • [math.OC]Bilinear Constraint based ADMM for Mixed Poisson-Gaussian Noise Removal
    • [math.ST]Center-Outward R-Estimation for Semiparametric VARMA Models
    • [math.ST]Density estimation on an unknown submanifold
    • [math.ST]Finite sample deviation and variance bounds for first order autoregressive processes
    • [math.ST]Optimization Hierarchy for Fair Statistical Decision Problems
    • [math.ST]Spectral representations of weakly stationary processes valued in a separable Hilbert space : a survey with applications on functional time series
    • [nlin.AO]Work sharing as a metric and productivity indicator for administrative workflows
    • [physics.data-an]Sampling strategy and statistical analysis for radioactive waste characterization
    • [quant-ph]Resource theories of communication with quantum superpositions of processes
    • [stat.AP]Application of three-dimensional weights of evidence in modeling concealed ore deposits: Case study of a porphyry Cu deposit in the Urmia-Dokhtar magmatic belt of Iran
    • [stat.AP]Generalized Mixed Modeling in Massive Electronic Health Record Databases: what is a healthy serum potassium?
    • [stat.AP]Inverse modeling of hydrologic parameters in CLM4 via generalized polynomial chaos in the Bayesian framework
    • [stat.ME]Anatomically informed Bayesian spatial priors for fMRI analysis
    • [stat.ME]Information Loss and Power Distortion from Standardizing in Multiple Hypothesis Testing
    • [stat.ML]Classification of spherical objects based on the form function of acoustic echoes
    • [stat.ML]Detecting multiple change-points in the time-varying Ising model
    • [stat.ML]Federated Generative Privacy
    • [stat.ML]Identification of Model Uncertainty via Optimal Design of Experiments applied to a Mechanical Press
    • [stat.ML]Multi-level conformal clustering: A distribution-free technique for clustering and anomaly detection
    • [stat.ML]Personalized Treatment for Coronary Artery Disease Patients: A Machine Learning Approach
    • [stat.ML]Robust modal regression with direct log-density derivative estimation

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

    • [cs.AI]A flexible integer linear programming formulation for scheduling clinician on-call service in hospitals
    David Landsman, Huiting Ma, Jesse Knight, Kevin Gough, Sharmistha Mishra
    http://arxiv.org/abs/1910.08526v1

    • [cs.AI]MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming
    Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri
    http://arxiv.org/abs/1910.08091v1

    • [cs.AI]Planning for Goal-Oriented Dialogue Systems
    Christian Muise, Tathagata Chakraborti, Shubham Agarwal, Ondrej Bajgar, Arunima Chaudhary, Luis A. Lastras-Montano, Josef Ondrej, Miroslav Vodolan, Charlie Wiecha
    http://arxiv.org/abs/1910.08137v1

    • [cs.AI]Reflecting After Learning for Understanding
    Lee Martie, Mohammad Arif Ul Alam, Gaoyuan Zhang, Ryan R. Anderson
    http://arxiv.org/abs/1910.08243v1

    • [cs.CG]Adaptive Partitioning for Template Functions on Persistence Diagrams
    Sarah Tymochko, Elizabeth Munch, Firas A. Khasawneh
    http://arxiv.org/abs/1910.08506v1

    • [cs.CL]A Mutual Information Maximization Perspective of Language Representation Learning
    Lingpeng Kong, Cyprien de Masson d’Autume, Wang Ling, Lei Yu, Zihang Dai, Dani Yogatama
    http://arxiv.org/abs/1910.08350v1

    • [cs.CL]Concept Pointer Network for Abstractive Summarization
    Wang Wenbo, Gao Yang, Huang Heyan, Zhou Yuxiang
    http://arxiv.org/abs/1910.08486v1

    • [cs.CL]Controlling Utterance Length in NMT-based Word Segmentation with Attention
    Pierre Godard, Laurent Besacier, Francois Yvon
    http://arxiv.org/abs/1910.08418v1

    • [cs.CL]End-to-End Speech Recognition: A review for the French Language
    Florian Boyer, Jean-Luc Rouas
    http://arxiv.org/abs/1910.08502v1

    • [cs.CL]Follow Alice into the Rabbit Hole: Giving Dialogue Agents Understanding of Human Level Attributes
    Aaron W. Li, Veronica Jiang, Steven Y. Feng, Julia Sprague, Wei Zhou, Jesse Hoey
    http://arxiv.org/abs/1910.08293v1

    • [cs.CL]HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansion
    Jiaming Shen, Zeqiu Wu, Dongming Lei, Chao Zhang, Xiang Ren, Michelle T. Vanni, Brian M. Sadler, Jiawei Han
    http://arxiv.org/abs/1910.08194v1

    • [cs.CL]Learning to Answer Subjective, Specific Product-Related Queries using Customer Reviews by Neural Domain Adaptation
    Manirupa Das, Zhen Wang, Evan Jaffe, Madhuja Chattopadhyay, Eric Fosler-Lussier, Rajiv Ramnath
    http://arxiv.org/abs/1910.08270v1

    • [cs.CL]Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification
    Vivian Lai, Jon Z. Cai, Chenhao Tan
    http://arxiv.org/abs/1910.08534v1

    • [cs.CL]Model Compression with Two-stage Multi-teacher Knowledge Distillation for Web Question Answering System
    Ze Yang, Linjun Shou, Ming Gong, Wutao Lin, Daxin Jiang
    http://arxiv.org/abs/1910.08381v1

    • [cs.CL]RTFM: Generalising to Novel Environment Dynamics via Reading
    Victor Zhong, Tim Rocktäschel, Edward Grefenstette
    http://arxiv.org/abs/1910.08210v1

    • [cs.CL]Relational Graph Representation Learning for Open-Domain Question Answering
    Salvatore Vivona, Kaveh Hassani
    http://arxiv.org/abs/1910.08249v1

    • [cs.CL]Towards Computing Inferences from English News Headlines
    Elizabeth Jasmi George, Radhika Mamidi
    http://arxiv.org/abs/1910.08294v1

    • [cs.CL]Unsupervised Context Rewriting for Open Domain Conversation
    Kun Zhou, Kai Zhang, Yu Wu, Shujie Liu, Jingsong Yu
    http://arxiv.org/abs/1910.08282v1

    • [cs.CL]Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
    Angela Fan, Claire Gardent, Chloe Braud, Antoine Bordes
    http://arxiv.org/abs/1910.08435v1

    • [cs.CR]Analysis of Nakamoto Consensus, Revisited
    Jianyu Niu, Chen Feng, Hoang Dau, Yu-Chih Huang, Jingge Zhu
    http://arxiv.org/abs/1910.08510v1

    • [cs.CV]A Dataset of Multi-Illumination Images in the Wild
    Lukas Murmann, Michael Gharbi, Miika Aittala, Fredo Durand
    http://arxiv.org/abs/1910.08131v1

    • [cs.CV]A novel centroid update approach for clustering-based superpixel method and superpixel-based edge detection
    Houwang Zhang, Chong Wu, Le Zhang, Hanying Zheng
    http://arxiv.org/abs/1910.08439v1

    • [cs.CV]AFO-TAD: Anchor-free One-Stage Detector for Temporal Action Detection
    Yiping Tang, Chuang Niu, Minghao Dong, Shenghan Ren, Jimin Liang
    http://arxiv.org/abs/1910.08250v1

    • [cs.CV]Automatic Data Augmentation by Learning the Deterministic Policy
    Yinghuan Shi, Tiexin Qin, Yong Liu, Jiwen Lu, Yang Gao, Dinggang Shen
    http://arxiv.org/abs/1910.08343v1

    • [cs.CV]BOBBY2: Buffer Based Robust High-Speed Object Tracking
    Keifer Lee, Jun Jet Tai, Swee King Phang
    http://arxiv.org/abs/1910.08263v1

    • [cs.CV]Deep Weakly-Supervised Domain Adaptation for Pain Localization in Videos
    Gnana Praveen R, Eric Granger, Patrick Cardinal
    http://arxiv.org/abs/1910.08173v1

    • [cs.CV]Diversity in Fashion Recommendation using Semantic Parsing
    Sagar Verma, Sukhad Anand, Chetan Arora, Atul Rai
    http://arxiv.org/abs/1910.08292v1

    • [cs.CV]Eye in the Sky: Drone-Based Object Tracking and 3D Localization
    Haotian Zhang, Gaoang Wang, Zhichao Lei, Jenq-Neng Hwang
    http://arxiv.org/abs/1910.08259v1

    • [cs.CV]Illumination-Based Data Augmentation for Robust Background Subtraction
    Dimitrios Sakkos, Hubert P. H. Shum, Edmond S. L. Ho
    http://arxiv.org/abs/1910.08470v1

    • [cs.CV]Image Deconvolution with Deep Image and Kernel Priors
    Zhunxuan Wang, Zipei Wang, Qiqi Li, Hakan Bilen
    http://arxiv.org/abs/1910.08386v1

    • [cs.CV]Investigating Task-driven Latent Feasibility for Nonconvex Image Modeling
    Risheng Liu, Pan Mu, Jian Chen, Xin Fan, Zhongxuan Luo
    http://arxiv.org/abs/1910.08242v1

    • [cs.CV]KerCNNs: biologically inspired lateral connections for classification of corrupted images
    Noemi Montobbio, Laurent Bonnasse-Gahot, Giovanna Citti, Alessandro Sarti
    http://arxiv.org/abs/1910.08336v1

    • [cs.CV]Multimodal Image Super-resolution via Deep Unfolding with Side Information
    Iman Marivani, Evaggelia Tsiligianni, Bruno Cornelis, Nikos Deligiannis
    http://arxiv.org/abs/1910.08320v1

    • [cs.CV]PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing
    Hehe Fan, Yi Yang
    http://arxiv.org/abs/1910.08287v1

    • [cs.CV]RPBA — Robust Parallel Bundle Adjustment Based on Covariance Information
    Helmut Mayer
    http://arxiv.org/abs/1910.08138v1

    • [cs.CV]Single and Cross-Dimensional Feature Detection and Description: An Evaluation
    Odysseas Kechagias-Stamatis, Nabil Aouf, Mark A. Richardson
    http://arxiv.org/abs/1910.08515v1

    • [cs.CV]Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data
    Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun
    http://arxiv.org/abs/1910.08233v1

    • [cs.CV]Toward 3D Object Reconstruction from Stereo Images
    Haozhe Xie, Hongxun Yao, Shangchen Zhou, Shengping Zhang, Xiaoshuai Sun, Wenxiu Sun
    http://arxiv.org/abs/1910.08223v1

    • [cs.CV]Understanding Deep Networks via Extremal Perturbations and Smooth Masks
    Ruth Fong, Mandela Patrick, Andrea Vedaldi
    http://arxiv.org/abs/1910.08485v1

    • [cs.CV]Unsupervised Multi-Task Feature Learning on Point Clouds
    Kaveh Hassani, Mike Haley
    http://arxiv.org/abs/1910.08207v1

    • [cs.DC]A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit
    Filip Petrovič, David Střelák, Jana Hozzová, Jaroslav Oľha, Richard Trembecký, Siegfried Benkner, Jiří Filipovič
    http://arxiv.org/abs/1910.08498v1

    • [cs.DC]Benefits of Stabilization versus Rollback in Eventually Consistent Key-Value Stores
    Duong Nguyen, Sandeep S. Kulkarni
    http://arxiv.org/abs/1910.08248v1

    • [cs.DC]DLB: Deep Learning Based Load Balancing
    Xiaoke Zhu, Qi Zhang, Ling Liu, Taining Cheng, Shaowen Yao, Wei Zhou, and Jing He
    http://arxiv.org/abs/1910.08494v1

    • [cs.DS]Weighted Edge Sampling for Static Graphs
    Muhammad Irfan Yousuf, Raheel Anwar
    http://arxiv.org/abs/1910.08283v1

    • [cs.IR]Attentive Knowledge Graph Embedding for Personalized Recommendation
    Xiao Sha, Zhu Sun, Jie Zhang
    http://arxiv.org/abs/1910.08288v1

    • [cs.IR]Entity Summarization: State of the Art and Future Challenges
    Qingxia Liu, Gong Cheng, Kalpa Gunaratna, Yuzhong Qu
    http://arxiv.org/abs/1910.08252v1

    • [cs.IT]Distributed Hypothesis Testing with Variable-Length Coding
    Sadaf Salehkalaibar, Michele Wigger
    http://arxiv.org/abs/1910.08261v1

    • [cs.IT]Functional Epsilon Entropy
    Sourya Basu, Daewon Seo, Lav R. Varshney
    http://arxiv.org/abs/1910.08276v1

    • [cs.IT]Infinite families of near MDS codes holding $t$-designs
    Cunsheng Ding, Chunming Tang
    http://arxiv.org/abs/1910.08265v1

    • [cs.IT]Obfuscation via Information Density Estimation
    Hsiang Hsu, Shahab Asoodeh, Flavio du Pin Calmon
    http://arxiv.org/abs/1910.08109v1

    • [cs.IT]Secure Coded Caching with Colluding Users
    Kangning Ma, Shuo Shao
    http://arxiv.org/abs/1910.08268v1

    • [cs.LG]$b$-Bit Sketch Trie: Scalable Similarity Search on Integer Sketches
    Shunsuke Kanda, Yasuo Tabei
    http://arxiv.org/abs/1910.08278v1

    • [cs.LG]A Deep Learning-based Framework for the Detection of Schools of Herring in Echograms
    Alireza Rezvanifar, Tunai Porto Marques, Melissa Cote, Alexandra Branzan Albu, Alex Slonimer, Thomas Tolhurst, Kaan Ersahin, Todd Mudge, Stephane Gauthier
    http://arxiv.org/abs/1910.08215v1

    • [cs.LG]A Topological “Reading” Lesson: Classification of MNIST using TDA
    Adélie Garin, Guillaume Tauzin
    http://arxiv.org/abs/1910.08345v1

    • [cs.LG]Anatomically-Informed Data Augmentation for functional MRI with Applications to Deep Learning
    Kevin P. Nguyen, Cherise Chin Fatt, Alex Treacher, Cooper Mellema, Madhukar H. Trivedi, Albert Montillo
    http://arxiv.org/abs/1910.08112v1

    • [cs.LG]Autonomous exploration for navigating in non-stationary CMPs
    Pratik Gajane, Ronald Ortner, Peter Auer, Csaba Szepesvari
    http://arxiv.org/abs/1910.08446v1

    • [cs.LG]Deep Sub-Ensembles for Fast Uncertainty Estimation in Image Classification
    Matias Valdenegro-Toro
    http://arxiv.org/abs/1910.08168v1

    • [cs.LG]Enforcing Linearity in DNN succours Robustness and Adversarial Image Generation
    Anindya Sarkar, Nikhil Kumar Gupta, Raghu Iyengar
    http://arxiv.org/abs/1910.08108v1

    • [cs.LG]Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
    Xin Yao, Tianchi Huang, Rui-Xiao Zhang, Ruiyu Li, Lifeng Sun
    http://arxiv.org/abs/1910.08234v1

    • [cs.LG]First-Order Preconditioning via Hypergradient Descent
    Ted Moskovitz, Rui Wang, Janice Lan, Sanyam Kapoor, Thomas Miconi, Jason Yosinski, Aditya Rawal
    http://arxiv.org/abs/1910.08461v1

    • [cs.LG]Fully Parallel Hyperparameter Search: Reshaped Space-Filling
    M. -L. Cauwet, C. Couprie, J. Dehos, P. Luc, J. Rapin, M. Riviere, F. Teytaud, O. Teytaud
    http://arxiv.org/abs/1910.08406v1

    • [cs.LG]Graph Convolutional Policy for Solving Tree Decomposition via Reinforcement Learning Heuristics
    Taras Khakhulin, Roman Schutski, Ivan Oseledets
    http://arxiv.org/abs/1910.08371v1

    • [cs.LG]Implicit Context-aware Learning and Discovery for Streaming Data Analytics
    Kin Gwn Lore, Kishore K. Reddy
    http://arxiv.org/abs/1910.08438v1

    • [cs.LG]JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation
    Zhiwei Liu, Lei Zheng, Jiawei Zhang, Jiayu Han, Philip S. Yu
    http://arxiv.org/abs/1910.08219v1

    • [cs.LG]Learning Compositional Koopman Operators for Model-Based Control
    Yunzhu Li, Hao He, Jiajun Wu, Dina Katabi, Antonio Torralba
    http://arxiv.org/abs/1910.08264v1

    • [cs.LG]Masked Gradient-Based Causal Structure Learning
    Ignavier Ng, Zhuangyan Fang, Shengyu Zhu, Zhitang Chen
    http://arxiv.org/abs/1910.08527v1

    • [cs.LG]Mirror Descent View for Neural Network Quantization
    Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania
    http://arxiv.org/abs/1910.08237v1

    • [cs.LG]Multi Label Restricted Boltzmann Machine for Non-Intrusive Load Monitoring
    Sagar Verma, Shikha Singh, Angshul Majumdar
    http://arxiv.org/abs/1910.08149v1

    • [cs.LG]Multi-View Reinforcement Learning
    Minne Li, Lisheng Wu, Haitham Bou Ammar, Jun Wang
    http://arxiv.org/abs/1910.08285v1

    • [cs.LG]On Connections between Constrained Optimization and Reinforcement Learning
    Nino Vieillard, Olivier Pietquin, Matthieu Geist
    http://arxiv.org/abs/1910.08476v1

    • [cs.LG]On the Difficulty of Warm-Starting Neural Network Training
    Jordan T. Ash, Ryan P. Adams
    http://arxiv.org/abs/1910.08475v1

    • [cs.LG]On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation
    Harshat Kumar, Alec Koppel, Alejandro Ribeiro
    http://arxiv.org/abs/1910.08412v1

    • [cs.LG]Point Process Flows
    Nazanin Mehrasa, Ruizhi Deng, Mohamed Osama Ahmed, Bo Chang, Jiawei He, Thibaut Durand, Marcus Brubaker, Greg Mori
    http://arxiv.org/abs/1910.08281v1

    • [cs.LG]Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data
    Seok-Ju Hahn, Junghye Lee
    http://arxiv.org/abs/1910.08489v1

    • [cs.LG]Scheduling the Learning Rate via Hypergradients: New Insights and a New Algorithm
    Michele Donini, Luca Franceschi, Massimiliano Pontil, Orchid Majumder, Paolo Frasconi
    http://arxiv.org/abs/1910.08525v1

    • [cs.LG]Scoring-Aggregating-Planning: Learning task-agnostic priors from interactions and sparse rewards for zero-shot generalization
    Huazhe Xu, Boyuan Chen, Yang Gao, Trevor Darrell
    http://arxiv.org/abs/1910.08143v1

    • [cs.LG]Supervised Learning Approach to Approximate Nearest Neighbor Search
    Ville Hyvönen, Elias Jääsaari, Teemu Roos
    http://arxiv.org/abs/1910.08322v1

    • [cs.LG]Texture Bias Of CNNs Limits Few-Shot Classification Performance
    Sam Ringer, Will Williams, Tom Ash, Remi Francis, David MacLeod
    http://arxiv.org/abs/1910.08519v1

    • [cs.LG]VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
    Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
    http://arxiv.org/abs/1910.08348v1

    • [cs.NE]Efficient Computation of Probabilistic Dominance in Robust Multi-Objective Optimization
    Faramarz Khosravi, Alexander Raß, Jürgen Teich
    http://arxiv.org/abs/1910.08413v1

    • [cs.NI]D2D-Enabled Mobile User Edge Caching: A Multi-Winner Auction Approach
    Tiankui Zhang, Xinyuan Fang, Yuanwei Liu, Geoffrey Ye Li, Wenjun Xu
    http://arxiv.org/abs/1910.08291v1

    • [cs.NI]FLIP:FLexible IoT Path Programming Framework for Large-scale IoT
    Shahzad, Eun-Sung Jung
    http://arxiv.org/abs/1910.08232v1

    • [cs.RO]Fast Local Planning and Mapping in Unknown Off-Road Terrain
    Timothy Overbye, Srikanth Saripalli
    http://arxiv.org/abs/1910.08521v1

    • [cs.RO]Learning Continuous Occupancy Maps with the Ising Process Model
    Nicholas O’Dell, Christopher Renton, Adrian Wills
    http://arxiv.org/abs/1910.08225v1

    • [cs.RO]Map-Predictive Motion Planning in Unknown Environments
    Amine Elhafsi, Boris Ivanovic, Lucas Janson, Marco Pavone
    http://arxiv.org/abs/1910.08184v1

    • [cs.RO]Online Learning in Planar Pushing with Combined Prediction Model
    Huidong Gao, Yi Ouyang, Masayoshi Tomizuka
    http://arxiv.org/abs/1910.08181v1

    • [cs.RO]Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process
    Jiacheng Zhu, Shenghao Qin, Wenshuo Wang, Ding Zhao
    http://arxiv.org/abs/1910.08102v1

    • [cs.SI]SGP: Spotting Groups Polluting the Online Political Discourse
    Junhao Wang, Sacha Levy, Ren Wang, Aayushi Kulshrestha, Reihaneh Rabbany
    http://arxiv.org/abs/1910.07130v3

    • [eess.IV]Attention Mechanism Enhanced Kernel Prediction Networks for Denoising of Burst Images
    Bin Zhang, Shenyao Jin, Yili Xia, Yongming Huang, Zixiang Xiong
    http://arxiv.org/abs/1910.08313v1

    • [eess.IV]OpenDenoising: an Extensible Benchmark for Building Comparative Studies of Image Denoisers
    Florian Lemarchand, Eduardo Fernandes Montesuma, Maxime Pelcat, Erwan Nogues
    http://arxiv.org/abs/1910.08328v1

    • [eess.IV]SDCNet: Smoothed Dense-Convolution Network for Restoring Low-Dose Cerebral CT Perfusion
    Peng Liu, Ruogu Fang
    http://arxiv.org/abs/1910.08364v1

    • [eess.SP]Cooperative Beamforming in Cognitive Radio Relay Networks Using Amplify-and-Forward Relaying Technique
    Amir Behrouzi-Far, Saeideh Mohammadkhani
    http://arxiv.org/abs/1910.08230v1

    • [eess.SP]Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT
    Tiankui Zhang, Yu Xu, Jonathan Loo, Dingcheng Yang, Lin Xiao
    http://arxiv.org/abs/1910.08296v1

    • [math.FA]On the perturbation series for eigenvalues and eigenprojections
    Martin Wahl
    http://arxiv.org/abs/1910.08460v1

    • [math.OC]Bilinear Constraint based ADMM for Mixed Poisson-Gaussian Noise Removal
    Jie Zhang, Yuping Duan, Yue Lu, Michael K. Ng, Huibin Chang
    http://arxiv.org/abs/1910.08206v1

    • [math.ST]Center-Outward R-Estimation for Semiparametric VARMA Models
    Marc Hallin, Davide La Vecchia, Hang Liu
    http://arxiv.org/abs/1910.08442v1

    • [math.ST]Density estimation on an unknown submanifold
    Clément Berenfeld, Marc Hoffmann
    http://arxiv.org/abs/1910.08477v1

    • [math.ST]Finite sample deviation and variance bounds for first order autoregressive processes
    Rodrigo A. González, Cristian R. Rojas
    http://arxiv.org/abs/1910.08390v1

    • [math.ST]Optimization Hierarchy for Fair Statistical Decision Problems
    Anil Aswani, Matt Olfat
    http://arxiv.org/abs/1910.08520v1

    • [math.ST]Spectral representations of weakly stationary processes valued in a separable Hilbert space : a survey with applications on functional time series
    Amaury Durand, François Roueff
    http://arxiv.org/abs/1910.08491v1

    • [nlin.AO]Work sharing as a metric and productivity indicator for administrative workflows
    Charles Roberto Telles
    http://arxiv.org/abs/1910.08380v1

    • [physics.data-an]Sampling strategy and statistical analysis for radioactive waste characterization
    Nadia Perot, Alexandre Le Cocguen, Dominique Carré, Hervé Lamotte, Anne Duhart-Barone, Ingmar Pointeau
    http://arxiv.org/abs/1910.08468v1

    • [quant-ph]Resource theories of communication with quantum superpositions of processes
    Hlér Kristjánsson, Sina Salek, Daniel Ebler, Giulio Chiribella
    http://arxiv.org/abs/1910.08197v1

    • [stat.AP]Application of three-dimensional weights of evidence in modeling concealed ore deposits: Case study of a porphyry Cu deposit in the Urmia-Dokhtar magmatic belt of Iran
    Ehsan Farahbakhsh, Ardeshir Hezarkhani, Taymour Eslamkish, Abbas Bahroudi, Rohitash Chandra
    http://arxiv.org/abs/1910.08162v1

    • [stat.AP]Generalized Mixed Modeling in Massive Electronic Health Record Databases: what is a healthy serum potassium?
    Cristian Bologa, Vernon Shane Pankratz, Mark L Unruh, Maria Eleni Roumelioti, Vallabh Shah, Saeed Kamran Shaffi, Soraya Arzhan, John Cook, Christos Argyropoulos
    http://arxiv.org/abs/1910.08179v1

    • [stat.AP]Inverse modeling of hydrologic parameters in CLM4 via generalized polynomial chaos in the Bayesian framework
    Georgios Karagiannis, Zhangshuan Hou, Maoyi Huang, Guang Lin
    http://arxiv.org/abs/1910.08409v1

    • [stat.ME]Anatomically informed Bayesian spatial priors for fMRI analysis
    David Abramian, Per Sidén, Hans Knutsson, Mattias Villani, Anders Eklund
    http://arxiv.org/abs/1910.08415v1

    • [stat.ME]Information Loss and Power Distortion from Standardizing in Multiple Hypothesis Testing
    Luella Fu, Bowen Gang, Gareth M. James, Wenguang Sun
    http://arxiv.org/abs/1910.08107v1

    • [stat.ML]Classification of spherical objects based on the form function of acoustic echoes
    Mariia Dmitrieva, Keith E. Brown, Gary J. Heald, David M. Lane
    http://arxiv.org/abs/1910.08501v1

    • [stat.ML]Detecting multiple change-points in the time-varying Ising model
    Batiste Le Bars, Pierre Humbert, Argyris Kalogeratos, Nicolas Vayatis
    http://arxiv.org/abs/1910.08512v1

    • [stat.ML]Federated Generative Privacy
    Aleksei Triastcyn, Boi Faltings
    http://arxiv.org/abs/1910.08385v1

    • [stat.ML]Identification of Model Uncertainty via Optimal Design of Experiments applied to a Mechanical Press
    Tristan Gally, Peter Groche, Florian Hoppe, Anja Kuttich, Alexander Matei, Marc E. Pfetsch, Martin Rakowitsch, Stefan Ulbrich
    http://arxiv.org/abs/1910.08408v1

    • [stat.ML]Multi-level conformal clustering: A distribution-free technique for clustering and anomaly detection
    Ilia Nouretdinov, James Gammerman, Matteo Fontana, Daljit Rehal
    http://arxiv.org/abs/1910.08105v1

    • [stat.ML]Personalized Treatment for Coronary Artery Disease Patients: A Machine Learning Approach
    Dimitris Bertsimas, Agni Orfanoudaki, Rory B. Weiner
    http://arxiv.org/abs/1910.08483v1

    • [stat.ML]Robust modal regression with direct log-density derivative estimation
    Hiroaki Sasaki, Tomoya Sakai, Takafumi Kanamori
    http://arxiv.org/abs/1910.08280v1