cond-mat.stat-mech - 统计数学

    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.ET - 新兴技术 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.PL - 编程语言 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-ph - 数学物理 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.data-an - 数据分析、 统计和概率 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 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

    • [cond-mat.stat-mech]Harnessing Fluctuations in Thermodynamic Computing via Time-Reversal Symmetries
    • [cs.AI]Anticipatory Thinking: A Metacognitive Capability
    • [cs.AI]The Winnability of Klondike and Many Other Single-Player Card Games
    • [cs.CL]Findings of the First Shared Task on Machine Translation Robustness
    • [cs.CL]Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translation
    • [cs.CL]Multi-Criteria Chinese Word Segmentation with Transformer
    • [cs.CL]Relating Simple Sentence Representations in Deep Neural Networks and the Brain
    • [cs.CL]Supervised Contextual Embeddings for Transfer Learning in Natural Language Processing Tasks
    • [cs.CL]Training Models to Extract Treatment Plans from Clinical Notes Using Contents of Sections with Headings
    • [cs.CL]Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts
    • [cs.CR]Adaptive Honeypot Engagement through Reinforcement Learning of Semi-Markov Decision Processes
    • [cs.CR]Privacy-Preserving Distributed Learning with Secret Gradient Descent
    • [cs.CR]SeF: A Secure Fountain Architecture for Slashing Storage Costs in Blockchains
    • [cs.CV]A Utility-Preserving GAN for Face Obscuration
    • [cs.CV]A linear method for camera pair self-calibration and multi-view reconstruction with geometrically verified correspondences
    • [cs.CV]BTEL: A Binary Tree Encoding Approach for Visual Localization
    • [cs.CV]Background Subtraction using Adaptive Singular Value Decomposition
    • [cs.CV]Convolution Based Spectral Partitioning Architecture for Hyperspectral Image Classification
    • [cs.CV]Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN
    • [cs.CV]Localizing Unseen Activities in Video via Image Query
    • [cs.CV]On the notion of number in humans and machines
    • [cs.CV]Open-Ended Long-Form Video Question Answering via Hierarchical Convolutional Self-Attention Networks
    • [cs.CV]Place recognition in gardens by learning visual representations: data set and benchmark analysis
    • [cs.CV]PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
    • [cs.CV]ProtoNet: Learning from Web Data with Memory
    • [cs.CY]Analyzing GDPR Compliance Through the Lens of Privacy Policy
    • [cs.CY]Implementing Ethics in AI: An industrial multiple case study
    • [cs.CY]Safeguarding the Evidential Value of Forensic Cryptocurrency Investigations
    • [cs.DB]Pruned Landmark Labeling Meets Vertex Centric Computation: A Surprisingly Happy Marriage!
    • [cs.ET]4K-Memristor Analog-Grade Passive Crossbar Circuit
    • [cs.HC]Studying the Impact of Mood on Identifying Smartphone Users
    • [cs.IR]Uncovering the Semantics of Wikipedia Categories
    • [cs.IT]Access Balancing in Storage Systems by Labeling Partial Steiner Systems
    • [cs.IT]Binary optimal linear codes from posets of the disjoint union of two chains
    • [cs.IT]Can Marton Coding Alone Ensure Individual Secrecy?
    • [cs.IT]Throughput Scaling of Covert Communication over Wireless Adhoc Networks
    • [cs.IT]Towards Assigning Priorities in Queues Using Age of Information
    • [cs.LG]ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network
    • [cs.LG]Certifiable Robustness and Robust Training for Graph Convolutional Networks
    • [cs.LG]Continual Rare-Class Recognition with Emerging Novel Subclasses
    • [cs.LG]DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM
    • [cs.LG]Early Bird Catches the Worm: Predicting Returns Even Before Purchase in Fashion E-commerce
    • [cs.LG]FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
    • [cs.LG]Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent
    • [cs.LG]GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
    • [cs.LG]Growing Action Spaces
    • [cs.LG]L*-Based Learning of Markov Decision Processes (Extended Version)
    • [cs.LG]Learning to Cope with Adversarial Attacks
    • [cs.LG]MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data
    • [cs.LG]Modelling Airway Geometry as Stock Market Data using Bayesian Changepoint Detection
    • [cs.LG]One Embedding To Do Them All
    • [cs.LG]Quantile Regression Deep Reinforcement Learning
    • [cs.LG]RECURSIA-RRT: Recursive translatable point-set pattern discovery with removal of redundant translators
    • [cs.LG]Rényi Fair Inference
    • [cs.LG]Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning
    • [cs.LG]Searching for Interaction Functions in Collaborative Filtering
    • [cs.LG]Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments
    • [cs.LG]Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
    • [cs.LG]Variational Mandible Shape Completion for Virtual Surgical Planning
    • [cs.NE]High Speed Cognitive Domain Ontologies for Asset Allocation Using Loihi Spiking Neurons
    • [cs.NE]Synaptic Delays for Temporal Feature Detection in Dynamic Neuromorphic Processors
    • [cs.NI]Multivariate Big Data Analysis for Intrusion Detection: 5 steps from the haystack to the needle
    • [cs.PL]A Neural-based Program Decompiler
    • [cs.PL]Category-Theoretic Foundations of “STCLang: State Thread Composition as a Foundation for Monadic Dataflow Parallelism”
    • [cs.RO]Learning Arbitration for Shared Autonomy by Hindsight Data Aggregation
    • [cs.RO]Motion Prediction with Recurrent Neural Network Dynamical Models and Trajectory Optimization
    • [cs.RO]Robotic Supervised Autonomy: A Review
    • [cs.RO]Sample Efficient Learning of Path Following and Obstacle Avoidance Behavior for Quadrotors
    • [cs.SI]Adversarial Representation Learning on Large-Scale Bipartite Graphs
    • [cs.SI]Automatic Discovery of Families of Network Generative Processes
    • [cs.SI]Critical Edge Identification: A K-Truss Based Model
    • [cs.SI]K-Core Maximization through Edge Additions
    • [cs.SI]Modularity in Multilayer Networks using Redundancy-based Resolution and Projection-based Inter-Layer Coupling
    • [cs.SI]To Act or React: Investigating Proactive Strategies For Online Community Moderation
    • [eess.IV]Accurate Retinal Vessel Segmentation via Octave Convolution Neural Network
    • [eess.IV]Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy
    • [eess.IV]Automated characterization of noise distributions in diffusion MRI data
    • [eess.IV]Densely Residual Laplacian Super-Resolution
    • [eess.SP]The Impact of Feature Causality on Normal Behaviour Models for SCADA-based Wind Turbine Fault Detection
    • [math-ph]Recursion scheme for the largest $β$-Wishart-Laguerre eigenvalue and Landauer conductance in quantum transport
    • [math.NA]Error bounds for deep ReLU networks using the Kolmogorov—Arnold superposition theorem
    • [math.NA]FameSVD: Fast and Memory-efficient Singular Value Decomposition
    • [math.OC]Asymptotic Network Independence in Distributed Optimization for Machine Learning
    • [math.OC]Geodesic analysis in Kendall’s shape space with epidemiological applications
    • [math.OC]Near-Optimal Methods for Minimizing Star-Convex Functions and Beyond
    • [math.ST]Differentially private sub-Gaussian location estimators
    • [math.ST]Multiple Testing and Variable Selection along Least Angle Regression’s path
    • [math.ST]Robust test for dispersion parameter change in discretely observed diffusion processes
    • [physics.data-an]Chi-squared Test for Binned, Gaussian Samples
    • [physics.soc-ph]Modeling echo chambers and polarization dynamics in social networks
    • [q-bio.NC]Symphony of high-dimensional brain
    • [stat.AP]Conformity bias in the cultural transmission of music sampling traditions
    • [stat.AP]Estimating adult death rates from sibling histories: A network approach
    • [stat.CO]A Python Library For Empirical Calibration
    • [stat.CO]Consensus Monte Carlo for Random Subsets using Shared Anchors
    • [stat.ME]A Bayesian Phylogenetic Hidden Markov Model for B Cell Receptor Sequence Analysis
    • [stat.ME]Direct Estimation of Difference Between Structural Equation Models in High Dimensions
    • [stat.ME]Formulating causal questions and principled statistical answers
    • [stat.ME]High-dimensional principal component analysis with heterogeneous missingness
    • [stat.ME]On the conditional distribution of the mean of the two closest among a set of three observations
    • [stat.ML]Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions
    • [stat.ML]Causal Regularization
    • [stat.ML]Comparing Semi-Parametric Model Learning Algorithms for Dynamic Model Estimation in Robotics
    • [stat.ML]Large scale Lasso with windowed active set for convolutional spike sorting
    • [stat.ML]Neural ODEs as the Deep Limit of ResNets with constant weights
    • [stat.ML]Statistical Learning from Biased Training Samples

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    • [cond-mat.stat-mech]Harnessing Fluctuations in Thermodynamic Computing via Time-Reversal Symmetries
    Gregory Wimsatt, Olli-Pentti Saira, Alexander B. Boyd, Matthew H. Matheny, Siyuan Han, Michael L. Roukes, James P. Crutchfield
    http://arxiv.org/abs/1906.11973v1

    • [cs.AI]Anticipatory Thinking: A Metacognitive Capability
    Adam Amos-Binks, Dustin Dannenhauer
    http://arxiv.org/abs/1906.12249v1

    • [cs.AI]The Winnability of Klondike and Many Other Single-Player Card Games
    Charlie Blake, Ian P. Gent
    http://arxiv.org/abs/1906.12314v1

    • [cs.CL]Findings of the First Shared Task on Machine Translation Robustness
    Xian Li, Paul Michel, Antonios Anastasopoulos, Yonatan Belinkov, Nadir Durrani, Orhan Firat, Philipp Koehn, Graham Neubig, Juan Pino, Hassan Sajjad
    http://arxiv.org/abs/1906.11943v1

    • [cs.CL]Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translation
    Eva Vanmassenhove, Dimitar Shterionov, Andy Way
    http://arxiv.org/abs/1906.12068v1

    • [cs.CL]Multi-Criteria Chinese Word Segmentation with Transformer
    Xipeng Qiu, Hengzhi Pei, Hang Yan, Xuanjing Huang
    http://arxiv.org/abs/1906.12035v1

    • [cs.CL]Relating Simple Sentence Representations in Deep Neural Networks and the Brain
    Sharmistha Jat, Hao Tang, Partha Talukdar, Tom Mitchell
    http://arxiv.org/abs/1906.11861v1

    • [cs.CL]Supervised Contextual Embeddings for Transfer Learning in Natural Language Processing Tasks
    Mihir Kale, Aditya Siddhant, Sreyashi Nag, Radhika Parik, Matthias Grabmair, Anthony Tomasic
    http://arxiv.org/abs/1906.12039v1

    • [cs.CL]Training Models to Extract Treatment Plans from Clinical Notes Using Contents of Sections with Headings
    Ananya Poddar, Bharath Dandala, Murthy Devarakonda
    http://arxiv.org/abs/1906.11930v1

    • [cs.CL]Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts
    Denis Emelin, Ivan Titov, Rico Sennrich
    http://arxiv.org/abs/1906.12284v1

    • [cs.CR]Adaptive Honeypot Engagement through Reinforcement Learning of Semi-Markov Decision Processes
    Linan Huang, Quanyan Zhu
    http://arxiv.org/abs/1906.12182v1

    • [cs.CR]Privacy-Preserving Distributed Learning with Secret Gradient Descent
    Valentin Hartmann, Robert West
    http://arxiv.org/abs/1906.11993v1

    • [cs.CR]SeF: A Secure Fountain Architecture for Slashing Storage Costs in Blockchains
    Swanand Kadhe, Jichan Chung, Kannan Ramchandran
    http://arxiv.org/abs/1906.12140v1

    • [cs.CV]A Utility-Preserving GAN for Face Obscuration
    Hanxiang Hao, David Güera, Amy R. Reibman, Edward J. Delp
    http://arxiv.org/abs/1906.11979v1

    • [cs.CV]A linear method for camera pair self-calibration and multi-view reconstruction with geometrically verified correspondences
    Nikos Melanitis, Petros Maragos
    http://arxiv.org/abs/1906.12075v1

    • [cs.CV]BTEL: A Binary Tree Encoding Approach for Visual Localization
    Huu Le, Tuan Hoang, Michael Milford
    http://arxiv.org/abs/1906.11992v1

    • [cs.CV]Background Subtraction using Adaptive Singular Value Decomposition
    Günther Reitberger, Tomas Sauer
    http://arxiv.org/abs/1906.12064v1

    • [cs.CV]Convolution Based Spectral Partitioning Architecture for Hyperspectral Image Classification
    Ringo S. W. Chu, Ho-Cheung Ng, Xiwei Wang, Wayne Luk
    http://arxiv.org/abs/1906.11981v1

    • [cs.CV]Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN
    Hang Min, Devin Wilson, Yinhuang Huang, Samuel Kelly, Stuart Crozier, Andrew P Bradley, Shekhar S. Chandra
    http://arxiv.org/abs/1906.12118v1

    • [cs.CV]Localizing Unseen Activities in Video via Image Query
    Zhu Zhang, Zhou Zhao, Zhijie Lin, Jingkuan Song, Deng Cai
    http://arxiv.org/abs/1906.12165v1

    • [cs.CV]On the notion of number in humans and machines
    Norbert Bátfai, Dávid Papp, Gergő Bogacsovics, Máté Szabó, Viktor Szilárd Simkó, Márió Bersenszki, Gergely Szabó, Lajos Kovács, Ferencz Kovács, Erik Szilveszter Varga
    http://arxiv.org/abs/1906.12213v1

    • [cs.CV]Open-Ended Long-Form Video Question Answering via Hierarchical Convolutional Self-Attention Networks
    Zhu Zhang, Zhou Zhao, Zhijie Lin, Jingkuan Song, Xiaofei He
    http://arxiv.org/abs/1906.12158v1

    • [cs.CV]Place recognition in gardens by learning visual representations: data set and benchmark analysis
    Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov
    http://arxiv.org/abs/1906.12151v1

    • [cs.CV]PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
    Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, Bharath Hariharan
    http://arxiv.org/abs/1906.12320v1

    • [cs.CV]ProtoNet: Learning from Web Data with Memory
    Yi Tu, Li Niu, Dawei Cheng, Liqing Zhang
    http://arxiv.org/abs/1906.12028v1

    • [cs.CY]Analyzing GDPR Compliance Through the Lens of Privacy Policy
    Jayashree Mohan, Melissa Wasserman, Vijay Chidambaram
    http://arxiv.org/abs/1906.12038v1

    • [cs.CY]Implementing Ethics in AI: An industrial multiple case study
    Ville Vakkuri, Kai-Kristian Kemell, Pekka Abrahamsson
    http://arxiv.org/abs/1906.12307v1

    • [cs.CY]Safeguarding the Evidential Value of Forensic Cryptocurrency Investigations
    Michael Fröwis, Thilo Gottschalk, Bernhard Haslhofer, Christian Rückert, Paulina Pesch
    http://arxiv.org/abs/1906.12221v1

    • [cs.DB]Pruned Landmark Labeling Meets Vertex Centric Computation: A Surprisingly Happy Marriage!
    Ruoming Jin, Zhen Peng, Wendell Wu, Feodor Dragan, Gagan Agrawal, Bin Ren
    http://arxiv.org/abs/1906.12018v1

    • [cs.ET]4K-Memristor Analog-Grade Passive Crossbar Circuit
    Hyungjin Kim, Hussein Nili, Mahmood Mahmoodi, Dmitri Strukov
    http://arxiv.org/abs/1906.12045v1

    • [cs.HC]Studying the Impact of Mood on Identifying Smartphone Users
    Khadija Zanna, Sayde King, Tempestt Neal, Shaun Canavan
    http://arxiv.org/abs/1906.11960v1

    • [cs.IR]Uncovering the Semantics of Wikipedia Categories
    Nicolas Heist, Heiko Paulheim
    http://arxiv.org/abs/1906.12089v1

    • [cs.IT]Access Balancing in Storage Systems by Labeling Partial Steiner Systems
    Yeow Meng Chee, Charles J. Colbourn, Hoang Dau, Ryan Gabrys, Alan C. H. Ling, Dylan Lusi, Olgica Milenkovic
    http://arxiv.org/abs/1906.12073v1

    • [cs.IT]Binary optimal linear codes from posets of the disjoint union of two chains
    Yansheng Wu, Jong Yoon Hyun, Qin Yue
    http://arxiv.org/abs/1906.12017v1

    • [cs.IT]Can Marton Coding Alone Ensure Individual Secrecy?
    Jin Yeong Tan, Lawrence Ong, Behzad Asadi
    http://arxiv.org/abs/1906.12326v1

    • [cs.IT]Throughput Scaling of Covert Communication over Wireless Adhoc Networks
    Kang-Hee Cho, Si-Hyeon Lee, Vincent Y. F. Tan
    http://arxiv.org/abs/1906.12092v1

    • [cs.IT]Towards Assigning Priorities in Queues Using Age of Information
    Jin Xu, Natarajan Gautam
    http://arxiv.org/abs/1906.12278v1

    • [cs.LG]ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network
    Zhangheng Li, Jia-Xing Zhong, Jingjia Huang, Tao Zhang, Thomas Li, Ge Li
    http://arxiv.org/abs/1906.12087v1

    • [cs.LG]Certifiable Robustness and Robust Training for Graph Convolutional Networks
    Daniel Zügner, Stephan Günnemann
    http://arxiv.org/abs/1906.12269v1

    • [cs.LG]Continual Rare-Class Recognition with Emerging Novel Subclasses
    Hung Nguyen, Xuejian Wang, Leman Akoglu
    http://arxiv.org/abs/1906.12218v1

    • [cs.LG]DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM
    Bao Wang, Quanquan Gu, March Boedihardjo, Farzin Barekat, Stanley J. Osher
    http://arxiv.org/abs/1906.12056v1

    • [cs.LG]Early Bird Catches the Worm: Predicting Returns Even Before Purchase in Fashion E-commerce
    Sajan Kedia, Manchit Madan, Sumit Borar
    http://arxiv.org/abs/1906.12128v1

    • [cs.LG]FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
    Henry B. Moss, Andrew Moore, David S. Leslie, Paul Rayson
    http://arxiv.org/abs/1906.12230v1

    • [cs.LG]Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent
    Shuheng Shen, Linli Xu, Jingchang Liu, Xianfeng Liang, Yifei Cheng
    http://arxiv.org/abs/1906.12043v1

    • [cs.LG]GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
    Marc Brockschmidt
    http://arxiv.org/abs/1906.12192v1

    • [cs.LG]Growing Action Spaces
    Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson, Nicolas Usunier, Gabriel Synnaeve
    http://arxiv.org/abs/1906.12266v1

    • [cs.LG]**L-Based Learning of Markov Decision Processes (Extended Version)
    Martin Tappler, Bernhard K. Aichernig, Giovanni Bacci, Maria Eichlseder, Kim G. Larsen
    http://arxiv.org/abs/1906.12239v1

    • [cs.LG]Learning to Cope with Adversarial Attacks
    Xian Yeow Lee, Aaron Havens, Girish Chowdhary, Soumik Sarkar
    http://arxiv.org/abs/1906.12061v1

    • [cs.LG]MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data
    Lei Xu, Shubhra Kanti Karmaker Santu, Kalyan Veeramachaneni
    http://arxiv.org/abs/1906.12348v1

    • [cs.LG]Modelling Airway Geometry as Stock Market Data using Bayesian Changepoint Detection
    Kin Quan, Ryutaro Tanno, Michael Duong, Arjun Nair, Rebecca Shipley, Mark Jones, Christopher Brereton, John Hurst, David Hawkes, Joseph Jacob
    http://arxiv.org/abs/1906.12225v1

    • [cs.LG]One Embedding To Do Them All
    Loveperteek Singh, Shreya Singh, Sagar Arora, Sumit Borar
    http://arxiv.org/abs/1906.12120v1

    • [cs.LG]Quantile Regression Deep Reinforcement Learning
    Oliver Richter, Roger Wattenhofer
    http://arxiv.org/abs/1906.11941v1

    • [cs.LG]RECURSIA-RRT: Recursive translatable point-set pattern discovery with removal of redundant translators
    David Meredith
    http://arxiv.org/abs/1906.12286v1

    • [cs.LG]Rényi Fair Inference
    Sina Baharlouei, Maher Nouiehed, Meisam Razaviyayn
    http://arxiv.org/abs/1906.12005v1

    • [cs.LG]Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning
    Marcello Fiducioso, Sebastian Curi, Benedikt Schumacher, Markus Gwerder, Andreas Krause
    http://arxiv.org/abs/1906.12086v1

    • [cs.LG]Searching for Interaction Functions in Collaborative Filtering
    Quanming Yao, Xiangning Chen, James Kwok, Yong Li
    http://arxiv.org/abs/1906.12091v1

    • [cs.LG]Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments
    Evan Racah, Christopher Pal
    http://arxiv.org/abs/1906.11951v1

    • [cs.LG]Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
    Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, Dawn Song
    http://arxiv.org/abs/1906.12340v1

    • [cs.LG]Variational Mandible Shape Completion for Virtual Surgical Planning
    Amir H. Abdi, Mehran Pesteie, Eitan Prisman, Purang Abolmaesumi, Sidney Fels
    http://arxiv.org/abs/1906.11957v1

    • [cs.NE]High Speed Cognitive Domain Ontologies for Asset Allocation Using Loihi Spiking Neurons
    Chris Yakopcic, Nayim Rahman, Tanvir Atahary, Tarek M. Taha, Alex Beigh, Scott Douglass
    http://arxiv.org/abs/1906.12338v1

    • [cs.NE]Synaptic Delays for Temporal Feature Detection in Dynamic Neuromorphic Processors
    Fredrik Sandin, Mattias Nilsson
    http://arxiv.org/abs/1906.12282v1

    • [cs.NI]Multivariate Big Data Analysis for Intrusion Detection: 5 steps from the haystack to the needle
    José Camacho, José Manuel García-Giménez, Noemí Marta Fuentes-García, Gabriel Maciá-Fernández
    http://arxiv.org/abs/1906.11976v1

    • [cs.PL]A Neural-based Program Decompiler
    Cheng Fu, Huili Chen, Haolan Liu, Xinyun Chen, Yuandong Tian, Farinaz Koushanfar, Jishen Zhao
    http://arxiv.org/abs/1906.12029v1

    • [cs.PL]Category-Theoretic Foundations of “STCLang: State Thread Composition as a Foundation for Monadic Dataflow Parallelism”
    Sebastian Ertel, Justus Adam, Norman A. Rink, Andrés Goens, Jeronimo Castrillon
    http://arxiv.org/abs/1906.12098v1

    • [cs.RO]Learning Arbitration for Shared Autonomy by Hindsight Data Aggregation
    Yoojin Oh, Marc Toussaint, Jim Mainprice
    http://arxiv.org/abs/1906.12280v1

    • [cs.RO]Motion Prediction with Recurrent Neural Network Dynamical Models and Trajectory Optimization
    Philipp Kratzer, Marc Toussaint, Jim Mainprice
    http://arxiv.org/abs/1906.12279v1

    • [cs.RO]Robotic Supervised Autonomy: A Review
    Yangming Li
    http://arxiv.org/abs/1906.11858v1

    • [cs.RO]Sample Efficient Learning of Path Following and Obstacle Avoidance Behavior for Quadrotors
    Stefan Stevsic, Tobias Naegeli, Javier Alonso-Mora, Otmar Hilliges
    http://arxiv.org/abs/1906.12082v1

    • [cs.SI]Adversarial Representation Learning on Large-Scale Bipartite Graphs
    Chaoyang He, Tian Xie, Yu Rong, Wenbing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi
    http://arxiv.org/abs/1906.11994v1

    • [cs.SI]Automatic Discovery of Families of Network Generative Processes
    Telmo Menezes, Camille Roth
    http://arxiv.org/abs/1906.12332v1

    • [cs.SI]Critical Edge Identification: A K-Truss Based Model
    Wenjie Zhu, Mengqi Zhang, Chen Chen, Xiaoyang Wang, Fan Zhang, Xuemin Lin
    http://arxiv.org/abs/1906.12335v1

    • [cs.SI]K-Core Maximization through Edge Additions
    Zhongxin Zhou, Fan Zhang, Xuemin Lin, Wenjie Zhang, Chen Chen
    http://arxiv.org/abs/1906.12334v1

    • [cs.SI]Modularity in Multilayer Networks using Redundancy-based Resolution and Projection-based Inter-Layer Coupling
    Alessia Amelio, Giuseppe Mangioni, Andrea Tagarelli
    http://arxiv.org/abs/1906.12204v1

    • [cs.SI]To Act or React: Investigating Proactive Strategies For Online Community Moderation
    Hussam Habib, Maaz Bin Musa, Fareed Zaffar, Rishab Nithyanand
    http://arxiv.org/abs/1906.11932v1

    • [eess.IV]Accurate Retinal Vessel Segmentation via Octave Convolution Neural Network
    Zhun Fan, Jiajie Mo, Benzhang Qiu
    http://arxiv.org/abs/1906.12193v1

    • [eess.IV]Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy
    Mohamed S. Elmahdy, Jelmer M. Wolterink, Hessam Sokooti, Ivana Išgum, Marius Staring
    http://arxiv.org/abs/1906.12223v1

    • [eess.IV]Automated characterization of noise distributions in diffusion MRI data
    Samuel St-Jean, Alberto De Luca, Chantal M. W. Tax, Max A. Viergever, Alexander Leemans
    http://arxiv.org/abs/1906.12121v1

    • [eess.IV]Densely Residual Laplacian Super-Resolution
    Saeed Anwar, Nick Barnes
    http://arxiv.org/abs/1906.12021v1

    • [eess.SP]The Impact of Feature Causality on Normal Behaviour Models for SCADA-based Wind Turbine Fault Detection
    Telmo Felgueira, Silvio Rodrigues, Christian S. Perone, Rui Castro
    http://arxiv.org/abs/1906.12329v1

    • [math-ph]Recursion scheme for the largest $β$-Wishart-Laguerre eigenvalue and Landauer conductance in quantum transport
    Peter J. Forrester, Santosh Kumar
    http://arxiv.org/abs/1906.12074v1

    • [math.NA]Error bounds for deep ReLU networks using the Kolmogorov—Arnold superposition theorem
    Hadrien Montanelli, Haizhao Yang
    http://arxiv.org/abs/1906.11945v1

    • [math.NA]FameSVD: Fast and Memory-efficient Singular Value Decomposition
    Xiaocan Li, Shuo Wang, Yinghao Cai
    http://arxiv.org/abs/1906.12085v1

    • [math.OC]Asymptotic Network Independence in Distributed Optimization for Machine Learning
    Alex Olshevsky, Ioannis Ch. Paschalidis, Shi Pu
    http://arxiv.org/abs/1906.12345v1

    • [math.OC]Geodesic analysis in Kendall’s shape space with epidemiological applications
    Esfandiar Nava-Yazdani, Hans-Christian Hege, T. J. Sullivan, Christoph von Tycowicz
    http://arxiv.org/abs/1906.11950v1

    • [math.OC]Near-Optimal Methods for Minimizing Star-Convex Functions and Beyond
    Oliver Hinder, Aaron Sidford, Nimit Sharad Sohoni
    http://arxiv.org/abs/1906.11985v1

    • [math.ST]Differentially private sub-Gaussian location estimators
    Marco Avella-Medina, Victor-Emmanuel Brunel
    http://arxiv.org/abs/1906.11923v1

    • [math.ST]Multiple Testing and Variable Selection along Least Angle Regression’s path
    J. -M. Azaïs, Y. De Castro
    http://arxiv.org/abs/1906.12072v1

    • [math.ST]Robust test for dispersion parameter change in discretely observed diffusion processes
    Junmo Song
    http://arxiv.org/abs/1906.12208v1

    • [physics.data-an]Chi-squared Test for Binned, Gaussian Samples
    Nicholas R. Hutzler
    http://arxiv.org/abs/1906.11748v1

    • [physics.soc-ph]Modeling echo chambers and polarization dynamics in social networks
    Fabian Baumann, Philipp Lorenz-Spreen, Igor M. Sokolov, Michele Starnini
    http://arxiv.org/abs/1906.12325v1

    • [q-bio.NC]Symphony of high-dimensional brain
    Alexander N. Gorban, Valeri A. Makarov, Ivan Y. Tyukin
    http://arxiv.org/abs/1906.12222v1

    • [stat.AP]Conformity bias in the cultural transmission of music sampling traditions
    Mason Youngblood
    http://arxiv.org/abs/1906.11928v1

    • [stat.AP]Estimating adult death rates from sibling histories: A network approach
    Dennis M. Feehan, Gabriel M. Borges
    http://arxiv.org/abs/1906.12000v1

    • [stat.CO]A Python Library For Empirical Calibration
    Xiaojing Wang, Jingang Miao, Yunting Sun
    http://arxiv.org/abs/1906.11920v1

    • [stat.CO]Consensus Monte Carlo for Random Subsets using Shared Anchors
    Yang Ni, Yuan Ji, Peter Mueller
    http://arxiv.org/abs/1906.12309v1

    • [stat.ME]A Bayesian Phylogenetic Hidden Markov Model for B Cell Receptor Sequence Analysis
    Amrit Dhar, Duncan K. Ralph, Vladimir N. Minin, Frederick A. Matsen IV
    http://arxiv.org/abs/1906.11982v1

    • [stat.ME]Direct Estimation of Difference Between Structural Equation Models in High Dimensions
    Asish Ghoshal, Jean Honorio
    http://arxiv.org/abs/1906.12024v1

    • [stat.ME]Formulating causal questions and principled statistical answers
    Els Goetghebeur, Saskia le Cessie, Bianca De Stavola, Erica Moodie, Ingeborg Waernbaum
    http://arxiv.org/abs/1906.12100v1

    • [stat.ME]High-dimensional principal component analysis with heterogeneous missingness
    Ziwei Zhu, Tengyao Wang, Richard J. Samworth
    http://arxiv.org/abs/1906.12125v1

    • [stat.ME]On the conditional distribution of the mean of the two closest among a set of three observations
    I. J. H. Visagie, F. Lombard
    http://arxiv.org/abs/1906.12106v1

    • [stat.ML]Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions
    Simon Luo, Mahito Sugiyama
    http://arxiv.org/abs/1906.12063v1

    • [stat.ML]Causal Regularization
    Dominik Janzing
    http://arxiv.org/abs/1906.12179v1

    • [stat.ML]Comparing Semi-Parametric Model Learning Algorithms for Dynamic Model Estimation in Robotics
    Sebastian Riedel, Freek Stulp
    http://arxiv.org/abs/1906.11909v1

    • [stat.ML]Large scale Lasso with windowed active set for convolutional spike sorting
    Laurent Dragoni, Rémi Flamary, Karim Lounici, Patricia Reynaud-Bouret
    http://arxiv.org/abs/1906.12077v1

    • [stat.ML]Neural ODEs as the Deep Limit of ResNets with constant weights
    Benny Avelin, Kaj Nyström
    http://arxiv.org/abs/1906.12183v1

    • [stat.ML]Statistical Learning from Biased Training Samples
    Pierre Laforgue, Stephan Clémençon
    http://arxiv.org/abs/1906.12304v1