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
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• [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