astro-ph.EP - 地球与行星天体

    cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 eess.SP - 信号处理 eess.SY - 系统和控制 math.PR - 概率 math.ST - 统计理论 physics.soc-ph - 物理学与社会 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.EP]Automated crater shape retrieval using weakly-supervised deep learning
    • [cs.AI]Categorizing Wireheading in Partially Embedded Agents
    • [cs.AI]Customer Segmentation of Wireless Trajectory Data
    • [cs.AI]Hybrid Planning for Dynamic Multimodal Stochastic Shortest Paths
    • [cs.CL]A Deep Generative Model for Code-Switched Text
    • [cs.CL]Be Consistent! Improving Procedural Text Comprehension using Label Consistency
    • [cs.CL]CUNI System for the WMT19 Robustness Task
    • [cs.CL]Demonstration of a Neural Machine Translation System with Online Learning for Translators
    • [cs.CL]Exploiting Entity BIO Tag Embeddings and Multi-task Learning for Relation Extraction with Imbalanced Data
    • [cs.CL]Incremental Adaptation of NMT for Professional Post-editors: A User Study
    • [cs.CL]Informative Image Captioning with External Sources of Information
    • [cs.CL]Learning Bilingual Word Embeddings Using Lexical Definitions
    • [cs.CL]Low-Resource Corpus Filtering using Multilingual Sentence Embeddings
    • [cs.CL]Mitigating Gender Bias in Natural Language Processing: Literature Review
    • [cs.CR]Finding Needles in a Moving Haystack: Prioritizing Alerts with Adversarial Reinforcement Learning
    • [cs.CR]Quantitative Mitigation of Timing Side Channels
    • [cs.CV]Acute Lymphoblastic Leukemia Classification from Microscopic Images using Convolutional Neural Networks
    • [cs.CV]Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
    • [cs.CV]Evolution Attack On Neural Networks
    • [cs.CV]FBK-HUPBA Submission to the EPIC-Kitchens 2019 Action Recognition Challenge
    • [cs.CV]From Zero-Shot Learning to Cold-Start Recommendation
    • [cs.CV]Fully Decoupled Neural Network Learning Using Delayed Gradients
    • [cs.CV]Pixel-Accurate Depth Evaluation in Realistic Driving Scenarios
    • [cs.CV]Predicting Future Opioid Incidences Today
    • [cs.CV]Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions
    • [cs.CY]Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices
    • [cs.CY]Zero Latency for Emergencies: A Machine Learning based Approach to Quantify Impact of Construction Projects on Emergency Response in Urban Settings
    • [cs.DB]A Comparative Survey of Recent Natural Language Interfaces for Databases
    • [cs.DB]Explainable Fact Checking with Probabilistic Answer Set Programming
    • [cs.DC]MinMax Algorithms for Stabilizing Consensus
    • [cs.DC]Performance Comparison Between OpenCV Built in CPU and GPU Functions on Image Processing Operations
    • [cs.DC]QoE-Aware Resource Allocation for Crowdsourced Live Streaming: A Machine Learning Approach
    • [cs.DC]Scalable and Probabilistic Leaderless BFT Consensus through Metastability
    • [cs.DC]Scheduling for Flexible Manufacturing System with Objective Function to be Minimization of Total Processing Time and Unbalance of Machine Load
    • [cs.DC]Semantics-aware Virtual Machine Image Management in IaaS Clouds
    • [cs.DC]Toward a Standard Interface for User-Defined Scheduling in OpenMP
    • [cs.DC]VM Image Repository and Distribution Models for Federated Clouds: State of the Art, Possible Directions and Open Issues
    • [cs.DS]Fairness and Utilization in Allocating Resources with Uncertain Demand
    • [cs.HC]Stuck? No worries!: Task-aware Command Recommendation and Proactive Help for Analysts
    • [cs.IR]Hierarchical Gating Networks for Sequential Recommendation
    • [cs.IT]A New Achievable Rate-Distortion Region for Distributed Source Coding
    • [cs.IT]LPD Communication: A Sequential Change-Point Detection Perspective
    • [cs.IT]Multi-Server Private Information Retrieval with Coded Side Information
    • [cs.IT]Some results about permutation properties of a kind of binomials over finite fields
    • [cs.LG]A Deep Reinforcement Learning Approach for Global Routing
    • [cs.LG]A Fourier Perspective on Model Robustness in Computer Vision
    • [cs.LG]Adaptive Learning Rate Clipping Stabilizes Learning
    • [cs.LG]Backpropagation-Friendly Eigendecomposition
    • [cs.LG]Connectivity-Optimized Representation Learning via Persistent Homology
    • [cs.LG]Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-Correction
    • [cs.LG]Deep Leakage from Gradients
    • [cs.LG]Deep Learning in the Automotive Industry: Recent Advances and Application Examples
    • [cs.LG]Disentangled Skill Embeddings for Reinforcement Learning
    • [cs.LG]Entropic Risk Measure in Policy Search
    • [cs.LG]FlipTest: Fairness Auditing via Optimal Transport
    • [cs.LG]Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis
    • [cs.LG]Intrinsic Weight Learning Approach for Multi-view Clustering
    • [cs.LG]Joint Detection of Malicious Domains and Infected Clients
    • [cs.LG]Learning as the Unsupervised Alignment of Conceptual Systems
    • [cs.LG]Learning from weakly dependent data under Dobrushin’s condition
    • [cs.LG]Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems
    • [cs.LG]Meta-learning of textual representations
    • [cs.LG]Neural Topographic Factor Analysis for fMRI Data
    • [cs.LG]Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning
    • [cs.LG]Privacy Preserving QoE Modeling using Collaborative Learning
    • [cs.LG]Quantum-Inspired Support Vector Machine
    • [cs.LG]Randomized Exploration in Generalized Linear Bandits
    • [cs.LG]Shaping Belief States with Generative Environment Models for RL
    • [cs.LG]Sparse Spectrum Gaussian Process for Bayesian Optimisation
    • [cs.LG]Theory of the Frequency Principle for General Deep Neural Networks
    • [cs.LG]Thompson Sampling for Adversarial Bit Prediction
    • [cs.LG]Universal Approximation of Input-Output Maps by Temporal Convolutional Nets
    • [cs.LG]When Multiple Agents Learn to Schedule: A Distributed Radio Resource Management Framework
    • [cs.MA]Topology Inference over Networks with Nonlinear Coupling
    • [cs.NE]Derivation of the Variational Bayes Equations
    • [cs.NE]Sharp Bounds on the Runtime of the (1+1) EA via Drift Analysis and Analytic Combinatorial Tools
    • [cs.RO]A Robust Biped Locomotion Based on Linear-Quadratic-Gaussian Controller and Divergent Component of Motion
    • [cs.RO]Autonomous Navigation of MAVs in Unknown Cluttered Environments
    • [cs.RO]Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks
    • [cs.RO]Improved Planetary Rover Inertial Navigation and Wheel Odometry Performance through Periodic Use of Zero-Type Constraints
    • [cs.RO]Learning Reward Functions by Integrating Human Demonstrations and Preferences
    • [cs.RO]Local Online Motor Babbling: Learning Motor Abundance of A Musculoskeletal Robot Arm
    • [cs.RO]SGANVO: Unsupervised Deep Visual Odometry and Depth Estimation with Stacked Generative Adversarial Networks
    • [cs.RO]Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks
    • [cs.SD]Query-based Deep Improvisation
    • [cs.SD]Singing Voice Synthesis Using Deep Autoregressive Neural Networks for Acoustic Modeling
    • [cs.SI]Appliance of network theory in economic geography
    • [cs.SI]Coupled Graph Neural Networks for Predicting the Popularity of Online Content
    • [cs.SI]Engagement index for users and conversations in encrypted messages from WhatsApp groups
    • [cs.SI]The Impact of Projection and Backboning on Network Topologies
    • [eess.SP]Information Bottleneck Decoding of Rate-Compatible 5G-LDPC Codes
    • [eess.SY]Revised Progressive-Hedging-Algorithm Based Two-layer Solution Scheme for Bayesian Reinforcement Learning
    • [math.PR]Power and limitations of conformal martingales
    • [math.ST]A Multiscale Scan Statistic for Adaptive Submatrix Localization
    • [math.ST]Estimation of the Kronecker Covariance Model by Partial Means and Quadratic Form
    • [math.ST]Intermediate efficiency of some weighted goodness-of-fit statistics
    • [math.ST]Posterior Contraction Rates for Gaussian Cox Processes with Non-identically Distributed Data
    • [physics.soc-ph]Community Detection in the Hyperbolic Space
    • [physics.soc-ph]Gender gaps in urban mobility
    • [physics.soc-ph]Inside the Echo Chamber: Disentangling network dynamics from polarization
    • [physics.soc-ph]Simplex2Vec embeddings for community detection in simplicial complexes
    • [stat.AP]A Flexible Pipeline for Prediction of Tropical Cyclone Paths
    • [stat.CO]Pushing the Limits of Importance Sampling through Iterative Moment Matching
    • [stat.ME]Maximum Approximate Bernstein Likelihood Estimation in Proportional Hazard Model for Interval-Censored Data
    • [stat.ME]Mediation analysis for zero-inflated mediators with applications to microbiome data
    • [stat.ME]New methods for multiple testing in permutation inference for the general linear model
    • [stat.ME]On Statistical Properties of A Veracity Scoring Method for Spatial Data
    • [stat.ME]Versatile linkage: a family of space-conserving strategies for agglomerative hierarchical clustering
    • [stat.ML]Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information
    • [stat.ML]First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise
    • [stat.ML]Limitations of Lazy Training of Two-layers Neural Networks
    • [stat.ML]Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation
    • [stat.ML]Modeling and Forecasting Art Movements with CGANs
    • [stat.ML]On Tree-based Methods for Similarity Learning
    • [stat.ML]Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning
    • [stat.ML]Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes

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

    • [astro-ph.EP]Automated crater shape retrieval using weakly-supervised deep learning
    Mohamad Ali-Dib, Kristen Menou, Chenchong Zhu, Noah Hammond, Alan P. Jackson
    http://arxiv.org/abs/1906.08826v1

    • [cs.AI]Categorizing Wireheading in Partially Embedded Agents
    Arushi Majha, Sayan Sarkar, Davide Zagami
    http://arxiv.org/abs/1906.09136v1

    • [cs.AI]Customer Segmentation of Wireless Trajectory Data
    Matthew R Karlsen, Sotiris K. Moschoyiannis
    http://arxiv.org/abs/1906.08874v1

    • [cs.AI]Hybrid Planning for Dynamic Multimodal Stochastic Shortest Paths
    Shushman Choudhury, Mykel J. Kochenderfer
    http://arxiv.org/abs/1906.09094v1

    • [cs.CL]A Deep Generative Model for Code-Switched Text
    Bidisha Samanta, Sharmila Reddy, Hussain Jagirdar, Niloy Ganguly, Soumen Chakrabarti
    http://arxiv.org/abs/1906.08972v1

    • [cs.CL]Be Consistent! Improving Procedural Text Comprehension using Label Consistency
    Xinya Du, Bhavana Dalvi Mishra, Niket Tandon, Antoine Bosselut, Wen-tau Yih, Peter Clark, Claire Cardie
    http://arxiv.org/abs/1906.08942v1

    • [cs.CL]CUNI System for the WMT19 Robustness Task
    Jindřich Helcl, Jindřich Libovický, Martin Popel
    http://arxiv.org/abs/1906.09246v1

    • [cs.CL]Demonstration of a Neural Machine Translation System with Online Learning for Translators
    Miguel Domingo, Mercedes García-Martínez, Amando Estela, Laurent Bié, Alexandre Helle, Álvaro Peris, Francisco Casacuberta, Manuerl Herranz
    http://arxiv.org/abs/1906.09000v1

    • [cs.CL]Exploiting Entity BIO Tag Embeddings and Multi-task Learning for Relation Extraction with Imbalanced Data
    Wei Ye, Bo Li, Rui Xie, Zhonghao Sheng, Long Chen, Shikun Zhang
    http://arxiv.org/abs/1906.08931v1

    • [cs.CL]Incremental Adaptation of NMT for Professional Post-editors: A User Study
    Miguel Domingo, Mercedes García-Martínez, Álvaro Peris, Alexandre Helle, Amando Estela, Laurent Bié, Francisco Casacuberta, Manuel Herranz
    http://arxiv.org/abs/1906.08996v1

    • [cs.CL]Informative Image Captioning with External Sources of Information
    Sanqiang Zhao, Piyush Sharma, Tomer Levinboim, Radu Soricut
    http://arxiv.org/abs/1906.08876v1

    • [cs.CL]Learning Bilingual Word Embeddings Using Lexical Definitions
    Weijia Shi, Muhao Chen, Yingtao Tian, Kai-Wei Chang
    http://arxiv.org/abs/1906.08939v1

    • [cs.CL]Low-Resource Corpus Filtering using Multilingual Sentence Embeddings
    Vishrav Chaudhary, Yuqing Tang, Francisco Guzmán, Holger Schwenk, Philipp Koehn
    http://arxiv.org/abs/1906.08885v1

    • [cs.CL]Mitigating Gender Bias in Natural Language Processing: Literature Review
    Tony Sun, Andrew Gaut, Shirlyn Tang, Yuxin Huang, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, William Yang Wang
    http://arxiv.org/abs/1906.08976v1

    • [cs.CR]Finding Needles in a Moving Haystack: Prioritizing Alerts with Adversarial Reinforcement Learning
    Liang Tong, Aron Laszka, Chao Yan, Ning Zhang, Yevgeniy Vorobeychik
    http://arxiv.org/abs/1906.08805v1

    • [cs.CR]Quantitative Mitigation of Timing Side Channels
    Saeid Tizpaz-Niari, Pavol Cerny, Ashutosh Trivedi
    http://arxiv.org/abs/1906.08957v1

    • [cs.CV]Acute Lymphoblastic Leukemia Classification from Microscopic Images using Convolutional Neural Networks
    Jonas Prellberg, Oliver Kramer
    http://arxiv.org/abs/1906.09020v1

    • [cs.CV]Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
    Yiqi Zhong, Cho-Ying Wu, Suya You, Ulrich Neumann
    http://arxiv.org/abs/1906.08967v1

    • [cs.CV]Evolution Attack On Neural Networks
    YiGui Luo, RuiJia Yang, Wei Sha, WeiYi Ding, YouTeng Sun, YiSi Wang
    http://arxiv.org/abs/1906.09072v1

    • [cs.CV]FBK-HUPBA Submission to the EPIC-Kitchens 2019 Action Recognition Challenge
    Swathikiran Sudhakaran, Sergio Escalera, Oswald Lanz
    http://arxiv.org/abs/1906.08960v1

    • [cs.CV]From Zero-Shot Learning to Cold-Start Recommendation
    Jingjing Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, Zi Huang
    http://arxiv.org/abs/1906.08511v2

    • [cs.CV]Fully Decoupled Neural Network Learning Using Delayed Gradients
    Huiping Zhuang, Yi Wang, Qinglai Liu, Zhiping Lin
    http://arxiv.org/abs/1906.09108v1

    • [cs.CV]Pixel-Accurate Depth Evaluation in Realistic Driving Scenarios
    Tobias Gruber, Mario Bijelic, Felix Heide, Werner Ritter, Klaus Dietmayer
    http://arxiv.org/abs/1906.08953v1

    • [cs.CV]Predicting Future Opioid Incidences Today
    Sandipan Choudhuri, Kaustav Basu, Kevin Thomas, Arunabha Sen
    http://arxiv.org/abs/1906.08891v1

    • [cs.CV]Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions
    Joey Hong, Benjamin Sapp, James Philbin
    http://arxiv.org/abs/1906.08945v1

    • [cs.CY]Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices
    Manish Raghavan, Solon Barocas, Jon Kleinberg, Karen Levy
    http://arxiv.org/abs/1906.09208v1

    • [cs.CY]Zero Latency for Emergencies: A Machine Learning based Approach to Quantify Impact of Construction Projects on Emergency Response in Urban Settings
    Zhengbo Zou, Semiha Ergan
    http://arxiv.org/abs/1906.08910v1

    • [cs.DB]A Comparative Survey of Recent Natural Language Interfaces for Databases
    Katrin Affolter, Kurt Stockinger, Abraham Bernstein
    http://arxiv.org/abs/1906.08990v1

    • [cs.DB]Explainable Fact Checking with Probabilistic Answer Set Programming
    Naser Ahmadi, Joohyung Lee, Paolo Papotti, Mohammed Saeed
    http://arxiv.org/abs/1906.09198v1

    • [cs.DC]MinMax Algorithms for Stabilizing Consensus
    Bernadette Charron-Bost, Shlomo Moran
    http://arxiv.org/abs/1906.09073v1

    • [cs.DC]Performance Comparison Between OpenCV Built in CPU and GPU Functions on Image Processing Operations
    Batuhan Hangün, Önder Eyecioğlu
    http://arxiv.org/abs/1906.08819v1

    • [cs.DC]QoE-Aware Resource Allocation for Crowdsourced Live Streaming: A Machine Learning Approach
    Fatima Haouari, Emna Baccour, Aiman Erbad, Amr Mohamed, Mohsen Guizani
    http://arxiv.org/abs/1906.09086v1

    • [cs.DC]Scalable and Probabilistic Leaderless BFT Consensus through Metastability
    Team Rocket, Maofan Yin, Kevin Sekniqi, Robbert van Renesse, Emin Gün Sirer
    http://arxiv.org/abs/1906.08936v1

    • [cs.DC]Scheduling for Flexible Manufacturing System with Objective Function to be Minimization of Total Processing Time and Unbalance of Machine Load
    U Yongnam, Ri Taehyong
    http://arxiv.org/abs/1906.08926v1

    • [cs.DC]Semantics-aware Virtual Machine Image Management in IaaS Clouds
    Nishant Saurabh, Julian Remmers, Dragi Kimovski, Radu Prodan, Jorge G. Barbosa
    http://arxiv.org/abs/1906.09122v1

    • [cs.DC]Toward a Standard Interface for User-Defined Scheduling in OpenMP
    Vivek Kale, Christian Iwainsky, Michael Klemm, Jonas Kondorfer, Florina Ciorba
    http://arxiv.org/abs/1906.08911v1

    • [cs.DC]VM Image Repository and Distribution Models for Federated Clouds: State of the Art, Possible Directions and Open Issues
    Nishant Saurabh, Dragi Kimovski, Simon Ostermann, Radu Prodan
    http://arxiv.org/abs/1906.09182v1

    • [cs.DS]Fairness and Utilization in Allocating Resources with Uncertain Demand
    Kate Donahue, Jon Kleinberg
    http://arxiv.org/abs/1906.09050v1

    • [cs.HC]Stuck? No worries!: Task-aware Command Recommendation and Proactive Help for Analysts
    Aadhavan M. Nambhi, Bhanu Prakash Reddy, Aarsh Prakash Agarwal, Gaurav Verma, Harvineet Singh, Iftikhar Ahamath Burhanuddin
    http://arxiv.org/abs/1906.08973v1

    • [cs.IR]Hierarchical Gating Networks for Sequential Recommendation
    Chen Ma, Peng Kang, Xue Liu
    http://arxiv.org/abs/1906.09217v1

    • [cs.IT]A New Achievable Rate-Distortion Region for Distributed Source Coding
    Farhad Shirani, S. Sandeep Pradhan
    http://arxiv.org/abs/1906.08810v1

    • [cs.IT]LPD Communication: A Sequential Change-Point Detection Perspective
    Ke-Wen Huang, Hui-Ming Wang, Don Towsley, H. Vincent Poor
    http://arxiv.org/abs/1906.08938v1

    • [cs.IT]Multi-Server Private Information Retrieval with Coded Side Information
    Fatemeh Kazemi, Esmaeil Karimi, Anoosheh Heidarzadeh, Alex Sprintson
    http://arxiv.org/abs/1906.09259v1

    • [cs.IT]Some results about permutation properties of a kind of binomials over finite fields
    Xiaogang Liu
    http://arxiv.org/abs/1906.09168v1

    • [cs.LG]A Deep Reinforcement Learning Approach for Global Routing
    Haiguang Liao, Wentai Zhang, Xuliang Dong, Barnabas Poczos, Kenji Shimada, Levent Burak Kara
    http://arxiv.org/abs/1906.08809v1

    • [cs.LG]A Fourier Perspective on Model Robustness in Computer Vision
    Dong Yin, Raphael Gontijo Lopes, Jonathon Shlens, Ekin D. Cubuk, Justin Gilmer
    http://arxiv.org/abs/1906.08988v1

    • [cs.LG]Adaptive Learning Rate Clipping Stabilizes Learning
    Jeffrey M. Ede, Richard Beanland
    http://arxiv.org/abs/1906.09060v1

    • [cs.LG]Backpropagation-Friendly Eigendecomposition
    Wei Wang, Zheng Dang, Yinlin Hu, Pascal Fua, Mathieu Salzmann
    http://arxiv.org/abs/1906.09023v1

    • [cs.LG]Connectivity-Optimized Representation Learning via Persistent Homology
    Christoph Hofer, Roland Kwitt, Mandar Dixit, Marc Niethammer
    http://arxiv.org/abs/1906.09003v1

    • [cs.LG]Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-Correction
    Fengda Zhu, Xiaojun Chang, Runhao Zeng, Mingkui Tan
    http://arxiv.org/abs/1906.09205v1

    • [cs.LG]Deep Leakage from Gradients
    Ligeng Zhu, Zhijian Liu, Song Han
    http://arxiv.org/abs/1906.08935v1

    • [cs.LG]Deep Learning in the Automotive Industry: Recent Advances and Application Examples
    Kanwar Bharat Singh, Mustafa Ali Arat
    http://arxiv.org/abs/1906.08834v1

    • [cs.LG]Disentangled Skill Embeddings for Reinforcement Learning
    Janith C. Petangoda, Sergio Pascual-Diaz, Vincent Adam, Peter Vrancx, Jordi Grau-Moya
    http://arxiv.org/abs/1906.09223v1

    • [cs.LG]Entropic Risk Measure in Policy Search
    David Nass, Boris Belousov, Jan Peters
    http://arxiv.org/abs/1906.09090v1

    • [cs.LG]FlipTest: Fairness Auditing via Optimal Transport
    Emily Black, Samuel Yeom, Matt Fredrikson
    http://arxiv.org/abs/1906.09218v1

    • [cs.LG]Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis
    Ryan Rogers, Aaron Roth, Adam Smith, Nathan Srebro, Om Thakkar, Blake Woodworth
    http://arxiv.org/abs/1906.09231v1

    • [cs.LG]Intrinsic Weight Learning Approach for Multi-view Clustering
    Feiping Nie, Jing Li, Xuelong Li
    http://arxiv.org/abs/1906.08905v1

    • [cs.LG]Joint Detection of Malicious Domains and Infected Clients
    Paul Prasse, Rene Knaebel, Lukas Machlica, Tomas Pevny, Tobias Scheffer
    http://arxiv.org/abs/1906.09084v1

    • [cs.LG]Learning as the Unsupervised Alignment of Conceptual Systems
    Brett D. Roads, Bradley C. Love
    http://arxiv.org/abs/1906.09012v1

    • [cs.LG]Learning from weakly dependent data under Dobrushin’s condition
    Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
    http://arxiv.org/abs/1906.09247v1

    • [cs.LG]Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems
    Žiga Lukšič, Jovan Tanevski, Sašo Džeroski, Ljupčo Todorovski
    http://arxiv.org/abs/1906.09088v1

    • [cs.LG]Meta-learning of textual representations
    Jorge Madrid, Hugo Jair Escalante, Eduardo Morales
    http://arxiv.org/abs/1906.08934v1

    • [cs.LG]Neural Topographic Factor Analysis for fMRI Data
    Eli Sennesh, Zulqarnain Khan, Jennifer Dy, Ajay B. Satpute, J. Benjamin Hutchinson, Jan-Willem van de Meent
    http://arxiv.org/abs/1906.08901v1

    • [cs.LG]Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning
    Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta, Hongzi Mao, Mohammad Alizadeh
    http://arxiv.org/abs/1906.08879v1

    • [cs.LG]Privacy Preserving QoE Modeling using Collaborative Learning
    Selim Ickin, Konstantinos Vandikas, Markus Fiedler
    http://arxiv.org/abs/1906.09248v1

    • [cs.LG]Quantum-Inspired Support Vector Machine
    Chen Ding, Tian-Yi Bao, He-Liang Huang
    http://arxiv.org/abs/1906.08902v1

    • [cs.LG]Randomized Exploration in Generalized Linear Bandits
    Branislav Kveton, Manzil Zaheer, Csaba Szepesvari, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier
    http://arxiv.org/abs/1906.08947v1

    • [cs.LG]Shaping Belief States with Generative Environment Models for RL
    Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, Aaron van den Oord
    http://arxiv.org/abs/1906.09237v1

    • [cs.LG]Sparse Spectrum Gaussian Process for Bayesian Optimisation
    Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh
    http://arxiv.org/abs/1906.08898v1

    • [cs.LG]Theory of the Frequency Principle for General Deep Neural Networks
    Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang
    http://arxiv.org/abs/1906.09235v1

    • [cs.LG]Thompson Sampling for Adversarial Bit Prediction
    Yuval Lewi, Haim Kaplan, Yishay Mansour
    http://arxiv.org/abs/1906.09059v1

    • [cs.LG]Universal Approximation of Input-Output Maps by Temporal Convolutional Nets
    Joshua Hanson, Maxim Raginsky
    http://arxiv.org/abs/1906.09211v1

    • [cs.LG]When Multiple Agents Learn to Schedule: A Distributed Radio Resource Management Framework
    Navid Naderializadeh, Jaroslaw Sydir, Meryem Simsek, Hosein Nikopour, Shilpa Talwar
    http://arxiv.org/abs/1906.08792v1

    • [cs.MA]Topology Inference over Networks with Nonlinear Coupling
    Augusto Santos, Vincenzo Matta, Ali H. Sayed
    http://arxiv.org/abs/1906.09029v1

    • [cs.NE]Derivation of the Variational Bayes Equations
    Alianna J. Maren
    http://arxiv.org/abs/1906.08804v1

    • [cs.NE]Sharp Bounds on the Runtime of the (1+1) EA via Drift Analysis and Analytic Combinatorial Tools
    Hsien-Kuei Hwang, Carsten Witt
    http://arxiv.org/abs/1906.09047v1

    • [cs.RO]A Robust Biped Locomotion Based on Linear-Quadratic-Gaussian Controller and Divergent Component of Motion
    Mohammadreza Kasaei, Nuno Lau, Artur Pereira
    http://arxiv.org/abs/1906.09239v1

    • [cs.RO]Autonomous Navigation of MAVs in Unknown Cluttered Environments
    Leobardo Campos-Macías, Rodrigo Aldana-López, Rafael de la Guardia, José I. Parra-Vilchis, David Gómez-Gutiérrez
    http://arxiv.org/abs/1906.08839v1

    • [cs.RO]Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks
    Xinchen Yan, Mohi Khansari, Jasmine Hsu, Yuanzheng Gong, Yunfei Bai, Sören Pirk, Honglak Lee
    http://arxiv.org/abs/1906.08989v1

    • [cs.RO]Improved Planetary Rover Inertial Navigation and Wheel Odometry Performance through Periodic Use of Zero-Type Constraints
    Cagri Kilic, Jason N. Gross, Nicholas Ohi, Ryan Watson, Jared Strader, Thomas Swiger, Scott Harper, Yu Gu
    http://arxiv.org/abs/1906.08849v1

    • [cs.RO]Learning Reward Functions by Integrating Human Demonstrations and Preferences
    Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh
    http://arxiv.org/abs/1906.08928v1

    • [cs.RO]Local Online Motor Babbling: Learning Motor Abundance of A Musculoskeletal Robot Arm
    Zinan Liu, Arne Hitzmann, Shuhei Ikemoto, Svenja Stark, Jan Peters, Koh Hosoda
    http://arxiv.org/abs/1906.09013v1

    • [cs.RO]SGANVO: Unsupervised Deep Visual Odometry and Depth Estimation with Stacked Generative Adversarial Networks
    Tuo Feng, Dongbing Gu
    http://arxiv.org/abs/1906.08889v1

    • [cs.RO]Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks
    Roberto Martín-Martín, Michelle A. Lee, Rachel Gardner, Silvio Savarese, Jeannette Bohg, Animesh Garg
    http://arxiv.org/abs/1906.08880v1

    • [cs.SD]Query-based Deep Improvisation
    Shlomo Dubnov
    http://arxiv.org/abs/1906.09155v1

    • [cs.SD]Singing Voice Synthesis Using Deep Autoregressive Neural Networks for Acoustic Modeling
    Yuan-Hao Yi, Yang Ai, Zhen-Hua Ling, Li-Rong Dai
    http://arxiv.org/abs/1906.08977v1

    • [cs.SI]Appliance of network theory in economic geography
    Alexandra Barina, Gabriel Barina, Mihai Udrescu
    http://arxiv.org/abs/1906.08946v1

    • [cs.SI]Coupled Graph Neural Networks for Predicting the Popularity of Online Content
    Qi Cao, Huawei Shen, Jinhua Gao, Bingzheng Wei, Xueqi Cheng
    http://arxiv.org/abs/1906.09032v1

    • [cs.SI]Engagement index for users and conversations in encrypted messages from WhatsApp groups
    Moshe Cotacallapa, Didier A. Vega-Oliveros
    http://arxiv.org/abs/1906.08875v1

    • [cs.SI]The Impact of Projection and Backboning on Network Topologies
    Michele Coscia, Luca Rossi
    http://arxiv.org/abs/1906.09081v1

    • [eess.SP]Information Bottleneck Decoding of Rate-Compatible 5G-LDPC Codes
    Maximilian Stark, Linfang Wang, Richard D. Wesel, Gerhard Bauch
    http://arxiv.org/abs/1906.08985v1

    • [eess.SY]Revised Progressive-Hedging-Algorithm Based Two-layer Solution Scheme for Bayesian Reinforcement Learning
    Xin Huang, Duan Li, Daniel Zhuoyu Long
    http://arxiv.org/abs/1906.09035v1

    • [math.PR]Power and limitations of conformal martingales
    Vladimir Vovk
    http://arxiv.org/abs/1906.09256v1

    • [math.ST]A Multiscale Scan Statistic for Adaptive Submatrix Localization
    Yuchao Liu, Ery Arias-Castro
    http://arxiv.org/abs/1906.08884v1

    • [math.ST]Estimation of the Kronecker Covariance Model by Partial Means and Quadratic Form
    Oliver B. Linton, Haihan Tang
    http://arxiv.org/abs/1906.08908v1

    • [math.ST]Intermediate efficiency of some weighted goodness-of-fit statistics
    Bogdan Ćmiel, Tadeusz Inglot, Teresa Ledwina
    http://arxiv.org/abs/1906.09143v1

    • [math.ST]Posterior Contraction Rates for Gaussian Cox Processes with Non-identically Distributed Data
    James A. Grant, David S. Leslie
    http://arxiv.org/abs/1906.08799v1

    • [physics.soc-ph]Community Detection in the Hyperbolic Space
    Matteo Bruno, Sandro Ferreira Sousa, Furkan Gursoy, Matteo Serafino, Francesca V. Vianello, Ana Vranić, Marián Boguñá
    http://arxiv.org/abs/1906.09082v1

    • [physics.soc-ph]Gender gaps in urban mobility
    Laetitia Gauvin, Michele Tizzoni, Simone Piaggesi, Andrew Young, Natalia Adler, Stefaan Verhulst, Leo Ferres, Ciro Cattuto
    http://arxiv.org/abs/1906.09092v1

    • [physics.soc-ph]Inside the Echo Chamber: Disentangling network dynamics from polarization
    Duilio Balsamo, Valeria Gelardi, Chengyuan Han, Daniele Rama, Abhishek Samantray, Claudia Zucca, Michele Starnini
    http://arxiv.org/abs/1906.09076v1

    • [physics.soc-ph]Simplex2Vec embeddings for community detection in simplicial complexes
    Jacob Charles Wright Billings, Mirko Hu, Giulia Lerda, Alexey N. Medvedev, Francesco Mottes, Adrian Onicas, Andrea Santoro, Giovanni Petri
    http://arxiv.org/abs/1906.09068v1

    • [stat.AP]A Flexible Pipeline for Prediction of Tropical Cyclone Paths
    Niccolò Dalmasso, Robin Dunn, Benjamin LeRoy, Chad Schafer
    http://arxiv.org/abs/1906.08832v1

    • [stat.CO]Pushing the Limits of Importance Sampling through Iterative Moment Matching
    Topi Paananen, Juho Piironen, Paul-Christian Bürkner, Aki Vehtari
    http://arxiv.org/abs/1906.08850v1

    • [stat.ME]Maximum Approximate Bernstein Likelihood Estimation in Proportional Hazard Model for Interval-Censored Data
    Zhong Guan
    http://arxiv.org/abs/1906.08882v1

    • [stat.ME]Mediation analysis for zero-inflated mediators with applications to microbiome data
    Zhigang Li, Janaka S. S. Liyanage, A. James O’Malley, Susmita Datta, Raad Z. Gharaibeh, Christian Jobin, Modupe O. Coker, Anne G. Hoen, Brock C. Christensen, Juliette C. Madan, Margaret R. Karagas
    http://arxiv.org/abs/1906.09175v1

    • [stat.ME]New methods for multiple testing in permutation inference for the general linear model
    Tomas Mrkvicka, Mari Myllymaki, Naveen Naidu Narisetty
    http://arxiv.org/abs/1906.09004v1

    • [stat.ME]On Statistical Properties of A Veracity Scoring Method for Spatial Data
    Arnab Chakraborty, Soumendra N. Lahiri
    http://arxiv.org/abs/1906.08843v1

    • [stat.ME]Versatile linkage: a family of space-conserving strategies for agglomerative hierarchical clustering
    Alberto Fernández, Sergio Gómez
    http://arxiv.org/abs/1906.09222v1

    • [stat.ML]Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information
    Maya Okawa, Tomoharu Iwata, Takeshi Kurashima, Yusuke Tanaka, Hiroyuki Toda, Naonori Ueda
    http://arxiv.org/abs/1906.08952v1

    • [stat.ML]First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise
    Thanh Huy Nguyen, Umut Şimşekli, Mert Gürbüzbalaban, Gaël Richard
    http://arxiv.org/abs/1906.09069v1

    • [stat.ML]Limitations of Lazy Training of Two-layers Neural Networks
    Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
    http://arxiv.org/abs/1906.08899v1

    • [stat.ML]Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation
    Avishek Ghosh, Ashwin Pananjady, Adityanand Guntuboyina, Kannan Ramchandran
    http://arxiv.org/abs/1906.09255v1

    • [stat.ML]Modeling and Forecasting Art Movements with CGANs
    Edoardo Lisi, Mohammad Malekzadeh, Hamed Haddadi, F. Din-Houn Lau, Seth Flaxman
    http://arxiv.org/abs/1906.09230v1

    • [stat.ML]On Tree-based Methods for Similarity Learning
    Stéphan Clémençon, Robin Vogel
    http://arxiv.org/abs/1906.09243v1

    • [stat.ML]Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning
    Robin Vogel, Aurélien Bellet, Stephan Clémençon, Ons Jelassi, Guillaume Papa
    http://arxiv.org/abs/1906.09234v1

    • [stat.ML]Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes
    Wil O. C. Ward, Tom Ryder, Dennis Prangle, Mauricio A. Álvarez
    http://arxiv.org/abs/1906.09199v1