astro-ph.SR - 太阳和天体物理学恒星

    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.GT - 计算机科学与博弈论 cs.HC - 人机接口 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.SY - 系统与控制 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.ST - 统计理论 nlin.AO - 适应和自组织系统 q-bio.PE - 人口与发展 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.SR]Predicting Solar Flares Using a Long Short-Term Memory Network
    • [cs.AI]A Correctness Result for Synthesizing Plans With Loops in Stochastic Domains
    • [cs.AI]How Case Based Reasoning Explained Neural Networks: An XAI Survey of Post-Hoc Explanation-by-Example in ANN-CBR Twins
    • [cs.AI]Knowledge-Based Sequential Decision-Making Under Uncertainty
    • [cs.CL]Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language
    • [cs.CL]Availability-Based Production Predicts Speakers’ Real-time Choices of Mandarin Classifiers
    • [cs.CL]CHiVE: Varying Prosody in Speech Synthesis with a Linguistically Driven Dynamic Hierarchical Conditional Variational Network
    • [cs.CL]Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative
    • [cs.CL]Distant Learning for Entity Linking with Automatic Noise Detection
    • [cs.CL]Don’t Blame Distributional Semantics if it can’t do Entailment
    • [cs.CL]ERNIE: Enhanced Language Representation with Informative Entities
    • [cs.CL]IMHO Fine-Tuning Improves Claim Detection
    • [cs.CL]Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader
    • [cs.CL]Learning Cross-lingual Embeddings from Twitter via Distant Supervision
    • [cs.CL]Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs
    • [cs.CL]Plotting Markson’s ‘Mistress’
    • [cs.CL]Towards Automatic Generation of Shareable Synthetic Clinical Notes Using Neural Language Models
    • [cs.CR]A critique of the DeepSec Platform for Security Analysis of Deep Learning Models
    • [cs.CR]Finding Rats in Cats: Detecting Stealthy Attacks using Group Anomaly Detection
    • [cs.CR]Learning from Context: Exploiting and Interpreting File Path Information for Better Malware Detection
    • [cs.CV]A deep learning approach to detecting volcano deformation from satellite imagery using synthetic datasets
    • [cs.CV]AM-LFS: AutoML for Loss Function Search
    • [cs.CV]CNN-based Cost Volume Analysis as Confidence Measure for Dense Matching
    • [cs.CV]Group Re-Identification with Multi-grained Matching and Integration
    • [cs.CV]How do neural networks see depth in single images?
    • [cs.CV]LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving
    • [cs.CV]Neither Global Nor Local: A Hierarchical Robust Subspace Clustering For Image Data
    • [cs.CV]Neural Message Passing on Hybrid Spatio-Temporal Visual and Symbolic Graphs for Video Understanding
    • [cs.CV]Non-Parametric Priors For Generative Adversarial Networks
    • [cs.CV]Online Hyper-parameter Learning for Auto-Augmentation Strategy
    • [cs.CV]PoreNet: CNN-based Pore Descriptor for High-resolution Fingerprint Recognition
    • [cs.CV]Semantic Analysis of Traffic Camera Data: Topic Signal Extraction and Anomalous Event Detection
    • [cs.CV]Side Window Filtering
    • [cs.CV]Texture Fields: Learning Texture Representations in Function Space
    • [cs.CV]Transfer Learning based Detection of Diabetic Retinopathy from Small Dataset
    • [cs.CY]Between Discord and Deadlock: Consensus Under a Deadline
    • [cs.CY]Exploration methods for simulation models
    • [cs.DB]Concurrency Protocol Aiming at High Performance of Execution and Replay for Smart Contracts
    • [cs.DC]Auto-tuning of dynamic load balancing applied to 3D reverse time migration on multicore systems
    • [cs.DC]On the complexity of fault-tolerant consensus
    • [cs.DS]Parallel decompression of gzip-compressed files and random access to DNA sequences
    • [cs.DS]Separating Structure from Noise in Large Graphs Using the Regularity Lemma
    • [cs.GT]Fiduciary Bandits
    • [cs.HC]Are Automated Vehicles Safer than Manually Driven Cars?
    • [cs.HC]MiSC: Mixed Strategies Crowdsourcing
    • [cs.IR]Cleaned Similarity for Better Memory-Based Recommenders
    • [cs.IR]Deep Unified Multimodal Embeddings for Understanding both Content and Users in Social Media Networks
    • [cs.IR]Exact-K Recommendation via Maximal Clique Optimization
    • [cs.IT]Buffer-aided Resource Allocation for a Price Based Opportunistic Cognitive Radio Network
    • [cs.IT]Discussions on Signal Uncertainty Principle in Shannon Channel Capacity Equation and Research on Breaking Shannon Limit Method
    • [cs.IT]Joint Frequency-and-Phase Modulation for Backscatter-Tag Assisted Vehicular Positioning
    • [cs.IT]Optimal Status Updating with a Finite-Battery Energy Harvesting Source
    • [cs.LG]An Essay on Optimization Mystery of Deep Learning
    • [cs.LG]Biosignal Generation and Latent Variable Analysis with Recurrent Generative Adversarial Networks
    • [cs.LG]Comparison-Based Framework for Psychophysics: Lab versus Crowdsourcing
    • [cs.LG]Contrastive Fairness in Machine Learning
    • [cs.LG]Decision-Oriented Communications: Application to Energy-Efficient Resource Allocation
    • [cs.LG]DeepSwarm: Optimising Convolutional Neural Networks using Swarm Intelligence
    • [cs.LG]EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices
    • [cs.LG]Fairness in Machine Learning with Tractable Models
    • [cs.LG]Hybrid-FL: Cooperative Learning Mechanism Using Non-IID Data in Wireless Networks
    • [cs.LG]Integer Discrete Flows and Lossless Compression
    • [cs.LG]MOBA: A multi-objective bounded-abstention model for two-class cost-sensitive problems
    • [cs.LG]MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning
    • [cs.LG]Mastering the Game of Sungka from Random Play
    • [cs.LG]Online Multivariate Anomaly Detection and Localization for High-dimensional Settings
    • [cs.LG]POPQORN: Quantifying Robustness of Recurrent Neural Networks
    • [cs.LG]Privacy Preserving Adjacency Spectral Embedding on Stochastic Blockmodels
    • [cs.LG]Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
    • [cs.LG]Reference-Based Sequence Classification
    • [cs.LG]SSFN: Self Size-estimating Feed-forward Network and Low Complexity Design
    • [cs.LG]Simple Black-box Adversarial Attacks
    • [cs.LG]Sliced Score Matching: A Scalable Approach to Density and Score Estimation
    • [cs.LG]Spectral Metric for Dataset Complexity Assessment
    • [cs.LG]Stochastically Dominant Distributional Reinforcement Learning
    • [cs.LG]Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem
    • [cs.LG]TBQ($σ$): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning
    • [cs.LG]Utilizing Deep Learning Towards Multi-modal Bio-sensing and Vision-based Affective Computing
    • [cs.LG]Weakly-Supervised Temporal Localization via Occurrence Count Learning
    • [cs.NE]Approximation of the objective insensitivity regions using Hierarchic Memetic Strategy coupled with Covariance Matrix Adaptation Evolutionary Strategy
    • [cs.NI]Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals
    • [cs.RO]Challenges in Collaborative HRI for Remote Robot Teams
    • [cs.RO]Training Object Detectors With Noisy Data
    • [cs.RO]Understanding of Object Manipulation Actions Using Human Multi-Modal Sensory Data
    • [cs.SY]Randomized Algorithms for Data-Driven Stabilization of Stochastic Linear Systems
    • [eess.AS]End-to-end Adaptation with Backpropagation through WFST for On-device Speech Recognition System
    • [eess.IV]GlidarCo: gait recognition by 3D skeleton estimation and biometric feature correction of flash lidar data
    • [eess.IV]Mechanically Powered Motion Imaging Phantoms: Proof of Concept
    • [eess.SP]Deep Reinforcement Learning-Based Channel Allocation for Wireless LANs with Graph Convolutional Networks
    • [math.ST]Estimation of foreseeable and unforeseeable risks in motor insurance
    • [math.ST]Maximum Likelihood Estimation of Toric Fano Varieties
    • [math.ST]The Empirical Saddlepoint Estimator
    • [nlin.AO]When the goal is to generate a series of activities: A self-organized simulated robot arm
    • [q-bio.PE]NANUQ: A method for inferring species networks from gene trees under the coalescent model
    • [stat.AP]Colombian Women’s Life Patterns: A Multivariate Density Regression Approach
    • [stat.ME]A Bayesian hierarchical meta-analytic method for modelling surrogate relationships that vary across treatment classes
    • [stat.ME]Analytic Basis Expansions for Functional Snippets
    • [stat.ME]Functional Lagged Regression with Sparse Noisy Observations
    • [stat.ME]Model interpretation through lower-dimensional posterior summarization
    • [stat.ML]Comparison of Machine Learning Models in Food Authentication Studies
    • [stat.ML]Dream Distillation: A Data-Independent Model Compression Framework
    • [stat.ML]Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models
    • [stat.ML]Merging versus Ensembling in Multi-Study Machine Learning: Theoretical Insight from Random Effects
    • [stat.ML]Non-negative matrix factorization based on generalized dual divergence
    • [stat.ML]Online Distributed Estimation of Principal Eigenspaces
    • [stat.ML]Pair Matching: When bandits meet stochastic block model

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

    • [astro-ph.SR]Predicting Solar Flares Using a Long Short-Term Memory Network
    Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang
    http://arxiv.org/abs/1905.07095v1

    • [cs.AI]A Correctness Result for Synthesizing Plans With Loops in Stochastic Domains
    Laszlo Treszkai, Vaishak Belle
    http://arxiv.org/abs/1905.07028v1

    • [cs.AI]How Case Based Reasoning Explained Neural Networks: An XAI Survey of Post-Hoc Explanation-by-Example in ANN-CBR Twins
    Mark T Keane, Eoin M Kenny
    http://arxiv.org/abs/1905.07186v1

    • [cs.AI]Knowledge-Based Sequential Decision-Making Under Uncertainty
    Daoming Lyu
    http://arxiv.org/abs/1905.07030v1

    • [cs.CL]Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language
    Yuri Kuratov, Mikhail Arkhipov
    http://arxiv.org/abs/1905.07213v1

    • [cs.CL]Availability-Based Production Predicts Speakers’ Real-time Choices of Mandarin Classifiers
    Meilin Zhan, Roger Levy
    http://arxiv.org/abs/1905.07321v1

    • [cs.CL]CHiVE: Varying Prosody in Speech Synthesis with a Linguistically Driven Dynamic Hierarchical Conditional Variational Network
    Vincent Wan, Chun-an Chan, Tom Kenter, Jakub Vit, Rob Clark
    http://arxiv.org/abs/1905.07195v1

    • [cs.CL]Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative
    Shunsuke Kitada, Hitoshi Iyatomi, Yoshifumi Seki
    http://arxiv.org/abs/1905.07289v1

    • [cs.CL]Distant Learning for Entity Linking with Automatic Noise Detection
    Phong Le, Ivan Titov
    http://arxiv.org/abs/1905.07189v1

    • [cs.CL]Don’t Blame Distributional Semantics if it can’t do Entailment
    Matthijs Westera, Gemma Boleda
    http://arxiv.org/abs/1905.07356v1

    • [cs.CL]ERNIE: Enhanced Language Representation with Informative Entities
    Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, Qun Liu
    http://arxiv.org/abs/1905.07129v1

    • [cs.CL]IMHO Fine-Tuning Improves Claim Detection
    Tuhin Chakrabarty, Christopher Hidey, Kathleen McKeown
    http://arxiv.org/abs/1905.07000v1

    • [cs.CL]Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader
    Wenhan Xiong, Mo Yu, Shiyu Chang, Xiaoxiao Guo, William Yang Wang
    http://arxiv.org/abs/1905.07098v1

    • [cs.CL]Learning Cross-lingual Embeddings from Twitter via Distant Supervision
    Jose Camacho-Collados, Yerai Doval, Eugenio Martínez-Cámara, Luis Espinosa-Anke, Francesco Barbieri, Steven Schockaert
    http://arxiv.org/abs/1905.07358v1

    • [cs.CL]Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs
    Ming Tu, Guangtao Wang, Jing Huang, Yun Tang, Xiaodong He, Bowen Zhou
    http://arxiv.org/abs/1905.07374v1

    • [cs.CL]Plotting Markson’s ‘Mistress’
    Kelleher Conor, Mark T. Keane
    http://arxiv.org/abs/1905.07185v1

    • [cs.CL]Towards Automatic Generation of Shareable Synthetic Clinical Notes Using Neural Language Models
    Oren Melamud, Chaitanya Shivade
    http://arxiv.org/abs/1905.07002v1

    • [cs.CR]A critique of the DeepSec Platform for Security Analysis of Deep Learning Models
    Nicholas Carlini
    http://arxiv.org/abs/1905.07112v1

    • [cs.CR]Finding Rats in Cats: Detecting Stealthy Attacks using Group Anomaly Detection
    Aditya Kuppa, Slawomir Grzonkowski, Muhammad Rizwan Asghar, Nhien-An Le-Khac
    http://arxiv.org/abs/1905.07273v1

    • [cs.CR]Learning from Context: Exploiting and Interpreting File Path Information for Better Malware Detection
    Adarsh Kyadige, Ethan M. Rudd, Konstantin Berlin
    http://arxiv.org/abs/1905.06987v1

    • [cs.CV]A deep learning approach to detecting volcano deformation from satellite imagery using synthetic datasets
    Nantheera Anantrasirichai, Juliet Biggs, Fabien Albino, David Bull
    http://arxiv.org/abs/1905.07286v1

    • [cs.CV]AM-LFS: AutoML for Loss Function Search
    Chuming Li, Chen Lin, Minghao Guo, Wei Wu, Wanli Ouyang, Junjie Yan
    http://arxiv.org/abs/1905.07375v1

    • [cs.CV]CNN-based Cost Volume Analysis as Confidence Measure for Dense Matching
    Max Mehltretter, Christian Heipke
    http://arxiv.org/abs/1905.07287v1

    • [cs.CV]Group Re-Identification with Multi-grained Matching and Integration
    Weiyao Lin, Yuxi Li, Hao Xiao, John See, Junni Zou, Hongkai Xiong, Jingdong Wang, Tao Mei
    http://arxiv.org/abs/1905.07108v1

    • [cs.CV]How do neural networks see depth in single images?
    Tom van Dijk, Guido C. H. E. de Croon
    http://arxiv.org/abs/1905.07005v1

    • [cs.CV]LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving
    Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran, Nader Essam
    http://arxiv.org/abs/1905.07290v1

    • [cs.CV]Neither Global Nor Local: A Hierarchical Robust Subspace Clustering For Image Data
    Maryam Abdolali, Mohammad Rahmati
    http://arxiv.org/abs/1905.07220v1

    • [cs.CV]Neural Message Passing on Hybrid Spatio-Temporal Visual and Symbolic Graphs for Video Understanding
    Effrosyni Mavroudi, Benjamín Béjar Haro, René Vidal
    http://arxiv.org/abs/1905.07385v1

    • [cs.CV]Non-Parametric Priors For Generative Adversarial Networks
    Rajhans Singh, Pavan Turaga, Suren Jayasuriya, Ravi Garg, Martin W. Braun
    http://arxiv.org/abs/1905.07061v1

    • [cs.CV]Online Hyper-parameter Learning for Auto-Augmentation Strategy
    Chen Lin, Minghao Guo, Chuming Li, Wei Wu, Dahua Lin, Wanli Ouyang, Junjie Yan
    http://arxiv.org/abs/1905.07373v1

    • [cs.CV]PoreNet: CNN-based Pore Descriptor for High-resolution Fingerprint Recognition
    Vijay Anand, Vivek Kanhangad
    http://arxiv.org/abs/1905.06981v1

    • [cs.CV]Semantic Analysis of Traffic Camera Data: Topic Signal Extraction and Anomalous Event Detection
    Jeffrey Liu, Andrew Weinert, Saurabh Amin
    http://arxiv.org/abs/1905.07332v1

    • [cs.CV]Side Window Filtering
    Hui Yin, Yuanhao Gong, Guoping Qiu
    http://arxiv.org/abs/1905.07177v1

    • [cs.CV]Texture Fields: Learning Texture Representations in Function Space
    Michael Oechsle, Lars Mescheder, Michael Niemeyer, Thilo Strauss, Andreas Geiger
    http://arxiv.org/abs/1905.07259v1

    • [cs.CV]Transfer Learning based Detection of Diabetic Retinopathy from Small Dataset
    Misgina Tsighe Hagos, Shri Kant
    http://arxiv.org/abs/1905.07203v1

    • [cs.CY]Between Discord and Deadlock: Consensus Under a Deadline
    Marina Bannikova, Lihi Dery, Svetlana Obraztsova, Zinovi Rabinovich, Jeffrey S. Rosenschein
    http://arxiv.org/abs/1905.07173v1

    • [cs.CY]Exploration methods for simulation models
    J. Raimbault, D. Pumain
    http://arxiv.org/abs/1905.07160v1

    • [cs.DB]Concurrency Protocol Aiming at High Performance of Execution and Replay for Smart Contracts
    Shuaifeng Pang, Xiaodong Qi, Zhao Zhang, Cheqing Jin, Aoying Zhou
    http://arxiv.org/abs/1905.07169v1

    • [cs.DC]Auto-tuning of dynamic load balancing applied to 3D reverse time migration on multicore systems
    Ítalo A. S. Assis, João B. Fernandes, Tiago Barros, Samuel Xavier-de-Souza
    http://arxiv.org/abs/1905.06975v1

    • [cs.DC]On the complexity of fault-tolerant consensus
    Dariusz R. Kowalski, Jaroslaw Mirek
    http://arxiv.org/abs/1905.07063v1

    • [cs.DS]Parallel decompression of gzip-compressed files and random access to DNA sequences
    Maël Kerbiriou, Rayan Chikhi
    http://arxiv.org/abs/1905.07224v1

    • [cs.DS]Separating Structure from Noise in Large Graphs Using the Regularity Lemma
    Marco Fiorucci, Francesco Pelosin, Marcello Pelillo
    http://arxiv.org/abs/1905.06917v2

    • [cs.GT]Fiduciary Bandits
    Gal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, Moshe Tennenholtz
    http://arxiv.org/abs/1905.07043v1

    • [cs.HC]Are Automated Vehicles Safer than Manually Driven Cars?
    Lionel Peter Robert Jr
    http://arxiv.org/abs/1905.07054v1

    • [cs.HC]MiSC: Mixed Strategies Crowdsourcing
    Ching-Yun Ko, Rui Lin, Shu Li, Ngai Wong
    http://arxiv.org/abs/1905.07394v1

    • [cs.IR]Cleaned Similarity for Better Memory-Based Recommenders
    Farhan Khawar, Nevin L. Zhang
    http://arxiv.org/abs/1905.07370v1

    • [cs.IR]Deep Unified Multimodal Embeddings for Understanding both Content and Users in Social Media Networks
    Karan Sikka, Lucas Van Bramer, Ajay Divakaran
    http://arxiv.org/abs/1905.07075v1

    • [cs.IR]Exact-K Recommendation via Maximal Clique Optimization
    Yu Gong, Yu Zhu, Lu Duan, Qingwen Liu, Ziyu Guan, Fei Sun, Wenwu Ou, Kenny Q. Zhu
    http://arxiv.org/abs/1905.07089v1

    • [cs.IT]Buffer-aided Resource Allocation for a Price Based Opportunistic Cognitive Radio Network
    Nilanjan Biswas, Goutam Das, Priyadip Ray
    http://arxiv.org/abs/1905.07143v1

    • [cs.IT]Discussions on Signal Uncertainty Principle in Shannon Channel Capacity Equation and Research on Breaking Shannon Limit Method
    Dequn Liang, Xinyu Dou
    http://arxiv.org/abs/1905.07097v1

    • [cs.IT]Joint Frequency-and-Phase Modulation for Backscatter-Tag Assisted Vehicular Positioning
    Kaifeng Han, Seung-Woo Ko, Seungmin Lee, Woo-Suk Ko, Kaibin Huang
    http://arxiv.org/abs/1905.07125v1

    • [cs.IT]Optimal Status Updating with a Finite-Battery Energy Harvesting Source
    Baran Tan Bacinoglu, Yin Sun, Elif Uysal, Volkan Mutlu
    http://arxiv.org/abs/1905.06679v2

    • [cs.LG]An Essay on Optimization Mystery of Deep Learning
    Eugene Golikov
    http://arxiv.org/abs/1905.07187v1

    • [cs.LG]Biosignal Generation and Latent Variable Analysis with Recurrent Generative Adversarial Networks
    Shota Harada, Hideaki Hayashi, Seiichi Uchida
    http://arxiv.org/abs/1905.07136v1

    • [cs.LG]Comparison-Based Framework for Psychophysics: Lab versus Crowdsourcing
    Siavash Haghiri, Felix Wichmann, Ulrike von Luxburg
    http://arxiv.org/abs/1905.07234v1

    • [cs.LG]Contrastive Fairness in Machine Learning
    Tapabrata Chakraborti, Arijit Patra, Alison Noble
    http://arxiv.org/abs/1905.07360v1

    • [cs.LG]Decision-Oriented Communications: Application to Energy-Efficient Resource Allocation
    Hang Zou, Chao Zhang, Samson Lasaulce, Lucas Saludjian, Patrick Panciatici
    http://arxiv.org/abs/1905.07339v1

    • [cs.LG]DeepSwarm: Optimising Convolutional Neural Networks using Swarm Intelligence
    Edvinas Byla, Wei Pang
    http://arxiv.org/abs/1905.07350v1

    • [cs.LG]EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices
    Mario Almeida, Stefanos Laskaridis, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane
    http://arxiv.org/abs/1905.07346v1

    • [cs.LG]Fairness in Machine Learning with Tractable Models
    Michael Varley, Vaishak Belle
    http://arxiv.org/abs/1905.07026v1

    • [cs.LG]Hybrid-FL: Cooperative Learning Mechanism Using Non-IID Data in Wireless Networks
    Naoya Yoshida, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto, Ryo Yonetani
    http://arxiv.org/abs/1905.07210v1

    • [cs.LG]Integer Discrete Flows and Lossless Compression
    Emiel Hoogeboom, Jorn W. T. Peters, Rianne van den Berg, Max Welling
    http://arxiv.org/abs/1905.07376v1

    • [cs.LG]MOBA: A multi-objective bounded-abstention model for two-class cost-sensitive problems
    Hongjiao Guan
    http://arxiv.org/abs/1905.07297v1

    • [cs.LG]MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning
    Manan Tomar, Akhil Sathuluri, Balaraman Ravindran
    http://arxiv.org/abs/1905.07193v1

    • [cs.LG]Mastering the Game of Sungka from Random Play
    Darwin Bautista, Raimarc Dionido
    http://arxiv.org/abs/1905.07102v1

    • [cs.LG]Online Multivariate Anomaly Detection and Localization for High-dimensional Settings
    Mahsa Mozaffari, Yasin Yilmaz
    http://arxiv.org/abs/1905.07107v1

    • [cs.LG]POPQORN: Quantifying Robustness of Recurrent Neural Networks
    Ching-Yun Ko, Zhaoyang Lyu, Tsui-Wei Weng, Luca Daniel, Ngai Wong, Dahua Lin
    http://arxiv.org/abs/1905.07387v1

    • [cs.LG]Privacy Preserving Adjacency Spectral Embedding on Stochastic Blockmodels
    Li Chen
    http://arxiv.org/abs/1905.07065v1

    • [cs.LG]Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
    Philipp Becker, Harit Pandya, Gregor Gebhardt, Cheng Zhao, James Taylor, Gerhard Neumann
    http://arxiv.org/abs/1905.07357v1

    • [cs.LG]Reference-Based Sequence Classification
    Zengyou He, Guangyao Xu, Chaohua Sheng, Bo Xu, Quan Zou
    http://arxiv.org/abs/1905.07188v1

    • [cs.LG]SSFN: Self Size-estimating Feed-forward Network and Low Complexity Design
    Saikat Chatterjee, Alireza M. Javid, Mostafa Sadeghi, Shumpei Kikuta, Partha P. Mitra, Mikael Skoglund
    http://arxiv.org/abs/1905.07111v1

    • [cs.LG]Simple Black-box Adversarial Attacks
    Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger
    http://arxiv.org/abs/1905.07121v1

    • [cs.LG]Sliced Score Matching: A Scalable Approach to Density and Score Estimation
    Yang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon
    http://arxiv.org/abs/1905.07088v1

    • [cs.LG]Spectral Metric for Dataset Complexity Assessment
    Frederic Branchaud-Charron, Andrew Achkar, Pierre-Marc Jodoin
    http://arxiv.org/abs/1905.07299v1

    • [cs.LG]Stochastically Dominant Distributional Reinforcement Learning
    John D. Martin, Michal Lyskawinski, Xiaohu Li, Brendan Englot
    http://arxiv.org/abs/1905.07318v1

    • [cs.LG]Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem
    Christian Schroeder de Witt, Thomas Hornigold
    http://arxiv.org/abs/1905.07366v1

    • [cs.LG]TBQ($σ$): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning
    Longxiang Shi, Shijian Li, Longbing Cao, Long Yang, Gang Pan
    http://arxiv.org/abs/1905.07237v1

    • [cs.LG]Utilizing Deep Learning Towards Multi-modal Bio-sensing and Vision-based Affective Computing
    Siddharth Siddharth, Tzyy-Ping Jung, Terrence J. Sejnowski
    http://arxiv.org/abs/1905.07039v1

    • [cs.LG]Weakly-Supervised Temporal Localization via Occurrence Count Learning
    Julien Schroeter, Kirill Sidorov, David Marshall
    http://arxiv.org/abs/1905.07293v1

    • [cs.NE]Approximation of the objective insensitivity regions using Hierarchic Memetic Strategy coupled with Covariance Matrix Adaptation Evolutionary Strategy
    Jakub Sawicki, Maciej Smołka, Marcin Łoś, Robert Schaefer
    http://arxiv.org/abs/1905.07288v1

    • [cs.NI]Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals
    Igor Kadota, Eytan Modiano
    http://arxiv.org/abs/1905.07020v1

    • [cs.RO]Challenges in Collaborative HRI for Remote Robot Teams
    Helen Hastie, David A. Robb, José Lopes, Muneeb Ahmad, Pierre Le Bras, Xingkun Liu, Ronald P. A. Petrick, Katrin Lohan, Mike J. Chantler
    http://arxiv.org/abs/1905.07379v1

    • [cs.RO]Training Object Detectors With Noisy Data
    Simon Chadwick, Paul Newman
    http://arxiv.org/abs/1905.07202v1

    • [cs.RO]Understanding of Object Manipulation Actions Using Human Multi-Modal Sensory Data
    Bahareh Abbasi, Ehsan Noohi, Sina Parastegari, Milos Zefran
    http://arxiv.org/abs/1905.07012v1

    • [cs.SY]Randomized Algorithms for Data-Driven Stabilization of Stochastic Linear Systems
    Mohamad Kazem Shirani Faradonbeh, Ambuj Tewari, George Michailidis
    http://arxiv.org/abs/1905.06978v1

    • [eess.AS]End-to-end Adaptation with Backpropagation through WFST for On-device Speech Recognition System
    Emiru Tsunoo, Yosuke Kashiwagi, Satoshi Asakawa, Toshiyuki Kumakura
    http://arxiv.org/abs/1905.07149v1

    • [eess.IV]GlidarCo: gait recognition by 3D skeleton estimation and biometric feature correction of flash lidar data
    Nasrin Sadeghzadehyazdi, Tamal Batabyal, Nibir K. Dhar, B. O. Familoni, K. M. Iftekharuddin, Scott T. Acton
    http://arxiv.org/abs/1905.07058v1

    • [eess.IV]Mechanically Powered Motion Imaging Phantoms: Proof of Concept
    Alberto Gomez, Cornelia Schmitz, Markus Henningsson, James Housden, Yohan Noh, Veronika A. Zimmer, James R. Clough, Ilkay Oksuz, Nicolas Toussaint, Andrew P. King, Julia A. Schnabel
    http://arxiv.org/abs/1905.07198v1

    • [eess.SP]Deep Reinforcement Learning-Based Channel Allocation for Wireless LANs with Graph Convolutional Networks
    Kota Nakashima, Shotaro Kamiya, Kazuki Ohtsu, Koji Yamamoto, Takayuki Nishio, Masahiro Morikura
    http://arxiv.org/abs/1905.07144v1

    • [math.ST]Estimation of foreseeable and unforeseeable risks in motor insurance
    Weihong Ni, Corina Constantinescu, Alfredo Egídio dos Reis, Véronique Maume-Deschamps
    http://arxiv.org/abs/1905.07157v1

    • [math.ST]Maximum Likelihood Estimation of Toric Fano Varieties
    Carlos Améndola, Dimitra Kosta, Kaie Kubjas
    http://arxiv.org/abs/1905.07396v1

    • [math.ST]The Empirical Saddlepoint Estimator
    Benjamin Holcblat, Fallaw Sowell
    http://arxiv.org/abs/1905.06977v1

    • [nlin.AO]When the goal is to generate a series of activities: A self-organized simulated robot arm
    Tim Koglin, Bulcsú Sándor, Claudius Gros
    http://arxiv.org/abs/1905.07235v1

    • [q-bio.PE]NANUQ: A method for inferring species networks from gene trees under the coalescent model
    Elizabeth Allman, Hector Banos, John Rhodes
    http://arxiv.org/abs/1905.07050v1

    • [stat.AP]Colombian Women’s Life Patterns: A Multivariate Density Regression Approach
    Sara Wade, Raffaella Piccarreta, Andrea Cremaschi, Isadora Antoniano-Villalobos
    http://arxiv.org/abs/1905.07172v1

    • [stat.ME]A Bayesian hierarchical meta-analytic method for modelling surrogate relationships that vary across treatment classes
    Tasos Papanikos, John Thompson, Keith Abrams, Nicolas Staedler, Oriana Ciani, Rod Taylor, Sylwia Bujkiewicz
    http://arxiv.org/abs/1905.07194v1

    • [stat.ME]Analytic Basis Expansions for Functional Snippets
    Zhenhua Lin, Qixian Zhong, Jane-Ling Wang
    http://arxiv.org/abs/1905.07067v1

    • [stat.ME]Functional Lagged Regression with Sparse Noisy Observations
    Tomáš Rubín, Victor M. Panaretos
    http://arxiv.org/abs/1905.07218v1

    • [stat.ME]Model interpretation through lower-dimensional posterior summarization
    Spencer Woody, Carlos M. Carvalho, Jared S. Murray
    http://arxiv.org/abs/1905.07103v1

    • [stat.ML]Comparison of Machine Learning Models in Food Authentication Studies
    Manokamna Singh, Katarina Domijan
    http://arxiv.org/abs/1905.07302v1

    • [stat.ML]Dream Distillation: A Data-Independent Model Compression Framework
    Kartikeya Bhardwaj, Naveen Suda, Radu Marculescu
    http://arxiv.org/abs/1905.07072v1

    • [stat.ML]Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models
    Mor Shpigel Nacson, Suriya Gunasekar, Jason D. Lee, Nathan Srebro, Daniel Soudry
    http://arxiv.org/abs/1905.07325v1

    • [stat.ML]Merging versus Ensembling in Multi-Study Machine Learning: Theoretical Insight from Random Effects
    Zoe Guan, Giovanni Parmigiani, Prasad Patil
    http://arxiv.org/abs/1905.07382v1

    • [stat.ML]Non-negative matrix factorization based on generalized dual divergence
    Karthik Devarajan
    http://arxiv.org/abs/1905.07034v1

    • [stat.ML]Online Distributed Estimation of Principal Eigenspaces
    Davoud Ataee Tarzanagh, Mohamad Kazem Shirani Faradonbeh, George Michailidis
    http://arxiv.org/abs/1905.07389v1

    • [stat.ML]Pair Matching: When bandits meet stochastic block model
    Christophe Giraud, Yann Issartel, Luc Lehéricy, Matthieu Lerasle
    http://arxiv.org/abs/1905.07342v1