cs.AI - 人工智能

    cs.AR - 硬件体系结构 cs.CG - 计算几何学 cs.CL - 计算与语言 cs.CV - 机器视觉与模式识别 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DM - 离散数学 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.LO - 计算逻辑 cs.OH - 其他CS cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.CO - 组合数学 math.PR - 概率 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.data-an - 数据分析、 统计和概率 physics.geo-ph - 地球物理学 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

    • [cs.AI]Effective problem solving using SAT solvers
    • [cs.AI]Embedding Biomedical Ontologies by Jointly Encoding Network Structure and Textual Node Descriptors
    • [cs.AR]Thread Batching for High-performance Energy-efficient GPU Memory Design
    • [cs.CG]Topological Data Analysis with $ε$-net Induced Lazy Witness Complex
    • [cs.CL]A Simple and Effective Approach to Automatic Post-Editing with Transfer Learning
    • [cs.CL]Conceptor Debiasing of Word Representations Evaluated on WEAT
    • [cs.CL]Cost-sensitive Regularization for Label Confusion-aware Event Detection
    • [cs.CL]Cumulative Adaptation for BLSTM Acoustic Models
    • [cs.CL]DocRED: A Large-Scale Document-Level Relation Extraction Dataset
    • [cs.CL]Improving Visual Question Answering by Referring to Generated Paragraph Captions
    • [cs.CL]Learning to Ask Unanswerable Questions for Machine Reading Comprehension
    • [cs.CL]Meaning to Form: Measuring Systematicity as Information
    • [cs.CL]Microsoft AI Challenge India 2018: Learning to Rank Passages for Web Question Answering with Deep Attention Networks
    • [cs.CL]NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
    • [cs.CL]Neural Response Generation with Meta-Words
    • [cs.CV]A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation
    • [cs.CV]A Survey on Deep Learning Architectures for Image-based Depth Reconstruction
    • [cs.CV]Connecting Touch and Vision via Cross-Modal Prediction
    • [cs.CV]Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks
    • [cs.CV]Cross-View Policy Learning for Street Navigation
    • [cs.CV]Direct Image to Point Cloud Descriptors Matching for 6-DOF Camera Localization in Dense 3D Point Cloud
    • [cs.CV]Divide and Conquer the Embedding Space for Metric Learning
    • [cs.CV]Fusion vectors: Embedding Graph Fusions for Efficient Unsupervised Rank Aggregation
    • [cs.CV]Image Captioning: Transforming Objects into Words
    • [cs.CV]Low-light Image Enhancement Algorithm Based on Retinex and Generative Adversarial Network
    • [cs.CV]Modality Conversion of Handwritten Patterns by Cross Variational Autoencoders
    • [cs.CV]MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation
    • [cs.CV]Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
    • [cs.CV]R2D2: Reliable and Repeatable Detectors and Descriptors for Joint Sparse Keypoint Detection and Local Feature Extraction
    • [cs.CV]Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping
    • [cs.CV]Towards End-to-End Text Spotting in Natural Scenes
    • [cs.CV]Universal Barcode Detector via Semantic Segmentation
    • [cs.CV]Utilizing the Instability in Weakly Supervised Object Detection
    • [cs.DB]Scalable Community Detection over Geo-Social Network
    • [cs.DC]A Performance Study of the 2D Ising Model on GPUs
    • [cs.DC]Diffusing Your Mobile Apps: Extending In-Network Function Virtualization to Mobile Function Offloading
    • [cs.DC]Distributed Optimization for Over-Parameterized Learning
    • [cs.DC]Gathering with extremely restricted visibility
    • [cs.DM]Link Dimension and Exact Construction of a Graph
    • [cs.DS]Dynamic Path-Decomposed Tries
    • [cs.IR]Scalable Knowledge Graph Construction from Twitter
    • [cs.IR]Topic Modeling via Full Dependence Mixtures
    • [cs.IT]A Finite-Length Construction of Irregular Spatially-Coupled Codes
    • [cs.IT]A Lattice Based Joint Encryption, Encoding and Modulation Scheme
    • [cs.IT]Collaborative Broadcast in O(log log n) Rounds
    • [cs.IT]Deep Learning-Based Decoding of Constrained Sequence Codes
    • [cs.IT]Optimal $q$-Ary Error Correcting/All Unidirectional Error Detecting Codes
    • [cs.LG]A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization
    • [cs.LG]A Signal Propagation Perspective for Pruning Neural Networks at Initialization
    • [cs.LG]A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games
    • [cs.LG]A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation
    • [cs.LG]Adversarial Training Can Hurt Generalization
    • [cs.LG]Anomaly Detection with HMM Gauge Likelihood Analysis
    • [cs.LG]Augmenting Neural Networks with First-order Logic
    • [cs.LG]Binary Classification using Pairs of Minimum Spanning Trees or N-ary Trees
    • [cs.LG]Curriculum Learning for Cumulative Return Maximization
    • [cs.LG]Deep Learning Development Environment in Virtual Reality
    • [cs.LG]Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
    • [cs.LG]Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks
    • [cs.LG]Efficient N-Dimensional Convolutions via Higher-Order Factorization
    • [cs.LG]Empirical study of extreme overfitting points of neural networks
    • [cs.LG]Epistemic Risk-Sensitive Reinforcement Learning
    • [cs.LG]Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets
    • [cs.LG]Gradient Descent Maximizes the Margin of Homogeneous Neural Networks
    • [cs.LG]InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers
    • [cs.LG]Layered SGD: A Decentralized and Synchronous SGD Algorithm for Scalable Deep Neural Network Training
    • [cs.LG]Learning to Forget for Meta-Learning
    • [cs.LG]Model Agnostic Dual Quality Assessment for Adversarial Machine Learning and an Analysis of Current Neural Networks and Defenses
    • [cs.LG]Multigrid Neural Memory
    • [cs.LG]Online Active Learning of Reject Option Classifiers
    • [cs.LG]Provably Efficient $Q$-learning with Function Approximation via Distribution Shift Error Checking Oracle
    • [cs.LG]Recurrent Neural Processes
    • [cs.LG]Scalable Neural Architecture Search for 3D Medical Image Segmentation
    • [cs.LG]Stochastic Proximal AUC Maximization
    • [cs.LG]Sub-policy Adaptation for Hierarchical Reinforcement Learning
    • [cs.LG]Support vector machines on the D-Wave quantum annealer
    • [cs.LG]Towards Compact and Robust Deep Neural Networks
    • [cs.LG]Towards Stable and Efficient Training of Verifiably Robust Neural Networks
    • [cs.LG]Variational Federated Multi-Task Learning
    • [cs.LO]Dynamic Term-Modal Logics for Epistemic Planning
    • [cs.LO]Extensions of Generic DOL for Generic Ontology Design Patterns
    • [cs.OH]FPScreen: A Rapid Similarity Search Tool for Massive Molecular Library Based on Molecular Fingerprint Comparison
    • [cs.SI]A model of anonymous influence with anti-conformist agents
    • [cs.SI]An analysis of community structure in Brazilian political topic-based Twitter networks
    • [cs.SI]Disentangling Mixtures of Epidemics on Graphs
    • [eess.AS]Speaker-Targeted Audio-Visual Models for Speech Recognition in Cocktail-Party Environments
    • [eess.AS]Video-Driven Speech Reconstruction using Generative Adversarial Networks
    • [eess.IV]Deep neural network for fringe pattern filtering and normalisation
    • [eess.IV]GAN-based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer’s Disease Diagnosis
    • [eess.IV]Global and Local Interpretability for Cardiac MRI Classification
    • [eess.IV]Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification
    • [eess.SP]Cache-Aided Non-Orthogonal Multiple Access for 5G-Enabled Vehicular Networks
    • [eess.SP]Convolutional Neural Network based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis
    • [eess.SP]Massive MIMO Radar for Target Detection
    • [eess.SP]Multi-Carrier Agile Phased Array Radar
    • [eess.SP]Self-Tuning Sectorization: Deep Reinforcement Learning Meets Broadcast Beam Optimization
    • [math.CO]Complexity of Dependencies in Bounded Domains, Armstrong Codes, and Generalizations
    • [math.PR]Peskun-Tierney ordering for Markov chain and process Monte Carlo: beyond the reversible scenario
    • [math.ST]A technical note on divergence of the Wald statistic
    • [physics.comp-ph]Computing Committor Functions for the Study of Rare Events Using Deep Learning
    • [physics.data-an]hepaccelerate: Fast Analysis of Columnar Collider Data
    • [physics.geo-ph]Machine Learning Approach to Earthquake Rupture Dynamics
    • [stat.AP]Comparison of Methods for the Assessment of Nonlinearity in Short-Term Heart Rate Variability under different Physiopathological States
    • [stat.AP]Early Detection of Long Term Evaluation Criteria in Online Controlled Experiments
    • [stat.AP]Exploiting Convexification for Bayesian Optimal Sensor Placement by Maximization of Mutual Information
    • [stat.AP]Machine Learning on EPEX Order Books: Insights and Forecasts
    • [stat.CO]Robustly estimating the marginal likelihood for cognitive models via importance sampling
    • [stat.ME]A Latent Gaussian Process Model for Analyzing Intensive Longitudinal Data
    • [stat.ME]Identify treatment effect patterns for personalised decisions
    • [stat.ME]Statistical Inference for Generative Models with Maximum Mean Discrepancy
    • [stat.ML]$(1 + \varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets
    • [stat.ML]A stochastic alternating minimizing method for sparse phase retrieval
    • [stat.ML]Distributionally Robust Counterfactual Risk Minimization
    • [stat.ML]Empirical Bayes Method for Boltzmann Machines
    • [stat.ML]Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting
    • [stat.ML]Spectrally-truncated kernel ridge regression and its free lunch

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    • [cs.AI]Effective problem solving using SAT solvers
    Curtis Bright, Jürgen Gerhard, Ilias Kotsireas, Vijay Ganesh
    http://arxiv.org/abs/1906.06251v1

    • [cs.AI]Embedding Biomedical Ontologies by Jointly Encoding Network Structure and Textual Node Descriptors
    Sotiris Kotitsas, Dimitris Pappas, Ion Androutsopoulos, Ryan McDonald, Marianna Apidianaki
    http://arxiv.org/abs/1906.05939v1

    • [cs.AR]Thread Batching for High-performance Energy-efficient GPU Memory Design
    Bing Li, Mengjie Mao, Xiaoxiao Liu, Tao Liu, Zihao Liu, Wujie Wen, Yiran Chen, Hai, Li
    http://arxiv.org/abs/1906.05922v1

    • [cs.CG]Topological Data Analysis with $ε$-net Induced Lazy Witness Complex
    Naheed Anjum Arafat, Debabrota Basu, Stéphane Bressan
    http://arxiv.org/abs/1906.06122v1

    • [cs.CL]A Simple and Effective Approach to Automatic Post-Editing with Transfer Learning
    Gonçalo M. Correia, André F. T. Martins
    http://arxiv.org/abs/1906.06253v1

    • [cs.CL]Conceptor Debiasing of Word Representations Evaluated on WEAT
    Saket Karve, Lyle Ungar, João Sedoc
    http://arxiv.org/abs/1906.05993v1

    • [cs.CL]Cost-sensitive Regularization for Label Confusion-aware Event Detection
    Hongyu Lin, Yaojie Lu, Xianpei Han, Le Sun
    http://arxiv.org/abs/1906.06003v1

    • [cs.CL]Cumulative Adaptation for BLSTM Acoustic Models
    Markus Kitza, Pavel Golik, Ralf Schlüter, Hermann Ney
    http://arxiv.org/abs/1906.06207v1

    • [cs.CL]DocRED: A Large-Scale Document-Level Relation Extraction Dataset
    Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou, Maosong Sun
    http://arxiv.org/abs/1906.06127v1

    • [cs.CL]Improving Visual Question Answering by Referring to Generated Paragraph Captions
    Hyounghun Kim, Mohit Bansal
    http://arxiv.org/abs/1906.06216v1

    • [cs.CL]Learning to Ask Unanswerable Questions for Machine Reading Comprehension
    Haichao Zhu, Li Dong, Furu Wei, Wenhui Wang, Bing Qin, Ting Liu
    http://arxiv.org/abs/1906.06045v1

    • [cs.CL]Meaning to Form: Measuring Systematicity as Information
    Tiago Pimentel, Arya D. McCarthy, Damián E. Blasi, Brian Roark, Ryan Cotterell
    http://arxiv.org/abs/1906.05906v1

    • [cs.CL]Microsoft AI Challenge India 2018: Learning to Rank Passages for Web Question Answering with Deep Attention Networks
    Chaitanya Sai Alaparthi
    http://arxiv.org/abs/1906.06056v1

    • [cs.CL]NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
    Leon Weber, Pasquale Minervini, Jannes Münchmeyer, Ulf Leser, Tim Rocktäschel
    http://arxiv.org/abs/1906.06187v1

    • [cs.CL]Neural Response Generation with Meta-Words
    Can Xu, Wei Wu, Chongyang Tao, Huang Hu, Matt Schuerman, Ying Wang
    http://arxiv.org/abs/1906.06050v1

    • [cs.CV]A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation
    Robin Brügger, Christian F. Baumgartner, Ender Konukoglu
    http://arxiv.org/abs/1906.06148v1

    • [cs.CV]A Survey on Deep Learning Architectures for Image-based Depth Reconstruction
    Hamid Laga
    http://arxiv.org/abs/1906.06113v1

    • [cs.CV]Connecting Touch and Vision via Cross-Modal Prediction
    Yunzhu Li, Jun-Yan Zhu, Russ Tedrake, Antonio Torralba
    http://arxiv.org/abs/1906.06322v1

    • [cs.CV]Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks
    Thomas Brunner, Frederik Diehl, Alois Knoll
    http://arxiv.org/abs/1906.06086v1

    • [cs.CV]Cross-View Policy Learning for Street Navigation
    Ang Li, Huiyi Hu, Piotr Mirowski, Mehrdad Farajtabar
    http://arxiv.org/abs/1906.05930v1

    • [cs.CV]Direct Image to Point Cloud Descriptors Matching for 6-DOF Camera Localization in Dense 3D Point Cloud
    Uzair Nadeem, Mohammad A. A. K. Jalwana, Mohammed Bennamoun, Roberto Togneri, Ferdous Sohel
    http://arxiv.org/abs/1906.06064v1

    • [cs.CV]Divide and Conquer the Embedding Space for Metric Learning
    Artsiom Sanakoyeu, Vadim Tschernezki, Uta Büchler, Björn Ommer
    http://arxiv.org/abs/1906.05990v1

    • [cs.CV]Fusion vectors: Embedding Graph Fusions for Efficient Unsupervised Rank Aggregation
    Icaro Cavalcante Dourado, Ricardo da Silva Torres
    http://arxiv.org/abs/1906.06011v1

    • [cs.CV]Image Captioning: Transforming Objects into Words
    Simao Herdade, Armin Kappeler, Kofi Boakye, Joao Soares
    http://arxiv.org/abs/1906.05963v1

    • [cs.CV]Low-light Image Enhancement Algorithm Based on Retinex and Generative Adversarial Network
    Yangming Shi, Xiaopo Wu, Ming Zhu
    http://arxiv.org/abs/1906.06027v1

    • [cs.CV]Modality Conversion of Handwritten Patterns by Cross Variational Autoencoders
    Taichi Sumi, Brian Kenji Iwana, Hideaki Hayashi, Seiichi Uchida
    http://arxiv.org/abs/1906.06142v1

    • [cs.CV]MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation
    Lorenzo Bertoni, Sven Kreiss, Alexandre Alahi
    http://arxiv.org/abs/1906.06059v1

    • [cs.CV]Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
    Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger
    http://arxiv.org/abs/1906.06310v1

    • [cs.CV]R2D2: Reliable and Repeatable Detectors and Descriptors for Joint Sparse Keypoint Detection and Local Feature Extraction
    Jerome Revaud, Philippe Weinzaepfel, César De Souza, Noe Pion, Gabriela Csurka, Yohann Cabon, Martin Humenberger
    http://arxiv.org/abs/1906.06195v1

    • [cs.CV]Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping
    Suhas Lohit, Qiao Wang, Pavan Turaga
    http://arxiv.org/abs/1906.05947v1

    • [cs.CV]Towards End-to-End Text Spotting in Natural Scenes
    Hui Li, Peng Wang, Chunhua Shen
    http://arxiv.org/abs/1906.06013v1

    • [cs.CV]Universal Barcode Detector via Semantic Segmentation
    Andrey Zharkov, Ivan Zagaynov
    http://arxiv.org/abs/1906.06281v1

    • [cs.CV]Utilizing the Instability in Weakly Supervised Object Detection
    Yan Gao, Boxiao Liu, Nan Guo, Xiaochun Ye, Fang Wan, Haihang You, Dongrui Fan
    http://arxiv.org/abs/1906.06023v1

    • [cs.DB]Scalable Community Detection over Geo-Social Network
    Xiuwen Zheng, Qiyu Liu, Amarnath Gupta
    http://arxiv.org/abs/1906.05505v2

    • [cs.DC]A Performance Study of the 2D Ising Model on GPUs
    Joshua Romero, Mauro Bisson, Massimiliano Fatica, Massimo Bernaschi
    http://arxiv.org/abs/1906.06297v1

    • [cs.DC]Diffusing Your Mobile Apps: Extending In-Network Function Virtualization to Mobile Function Offloading
    Mario Almeida, Liang Wang, Jeremy Blackburn, Konstantina Papagiannaki, Jon Crowcroft
    http://arxiv.org/abs/1906.06240v1

    • [cs.DC]Distributed Optimization for Over-Parameterized Learning
    Chi Zhang, Qianxiao Li
    http://arxiv.org/abs/1906.06205v1

    • [cs.DC]Gathering with extremely restricted visibility
    Rachid Guerraoui, Alexandre Maurer
    http://arxiv.org/abs/1906.06239v1

    • [cs.DM]Link Dimension and Exact Construction of a Graph
    Gunjan S. Mahindre, Anura P. Jayasumana
    http://arxiv.org/abs/1906.05916v1

    • [cs.DS]Dynamic Path-Decomposed Tries
    Shunsuke Kanda, Dominik Köppl, Yasuo Tabei, Kazuhiro Morita, Masao Fuketa
    http://arxiv.org/abs/1906.06015v1

    • [cs.IR]Scalable Knowledge Graph Construction from Twitter
    Omar Alonso, Vasileios Kandylas, Serge-Eric Tremblay
    http://arxiv.org/abs/1906.05986v1

    • [cs.IR]Topic Modeling via Full Dependence Mixtures
    Dan Fisher, Mark Kozdoba, Shie Mannor
    http://arxiv.org/abs/1906.06181v1

    • [cs.IT]A Finite-Length Construction of Irregular Spatially-Coupled Codes
    Homa Esfahanizadeh, Ruiyi Wu, Lara Dolecek
    http://arxiv.org/abs/1906.05955v1

    • [cs.IT]A Lattice Based Joint Encryption, Encoding and Modulation Scheme
    Khadijeh Bagheri, Taraneh Eghlidos, Mohammad-Reza Sadeghi, Daniel Panario
    http://arxiv.org/abs/1906.06280v1

    • [cs.IT]Collaborative Broadcast in O(log log n) Rounds
    Christian Schindelhauer, Aditya Oak, Thomas Janson
    http://arxiv.org/abs/1906.05153v2

    • [cs.IT]Deep Learning-Based Decoding of Constrained Sequence Codes
    Congzhe Cao, Duanshun Li, Ivan Fair
    http://arxiv.org/abs/1906.06172v1

    • [cs.IT]Optimal $q$-Ary Error Correcting/All Unidirectional Error Detecting Codes
    Yeow Meng Chee, Xiande Zhang
    http://arxiv.org/abs/1906.06066v1

    • [cs.LG]A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization
    Alexander Mey, Tom Viering, Marco Loog
    http://arxiv.org/abs/1906.06100v1

    • [cs.LG]A Signal Propagation Perspective for Pruning Neural Networks at Initialization
    Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr
    http://arxiv.org/abs/1906.06307v1

    • [cs.LG]A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games
    Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
    http://arxiv.org/abs/1906.05945v1

    • [cs.LG]A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation
    Steven Squires, Adam Prügel Bennett, Mahesan Niranjan
    http://arxiv.org/abs/1906.05912v1

    • [cs.LG]Adversarial Training Can Hurt Generalization
    Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang
    http://arxiv.org/abs/1906.06032v1

    • [cs.LG]Anomaly Detection with HMM Gauge Likelihood Analysis
    Boris Lorbeer, Tanja Deutsch, Peter Ruppel, Axel Küpper
    http://arxiv.org/abs/1906.06134v1

    • [cs.LG]Augmenting Neural Networks with First-order Logic
    Tao Li, Vivek Srikumar
    http://arxiv.org/abs/1906.06298v1

    • [cs.LG]Binary Classification using Pairs of Minimum Spanning Trees or N-ary Trees
    Riccardo La Grassa, Ignazio Gallo, Alessandro Calefati, Dimitri Ognibene
    http://arxiv.org/abs/1906.06090v1

    • [cs.LG]Curriculum Learning for Cumulative Return Maximization
    Francesco Foglino, Christiano Coletto Christakou, Ricardo Luna Gutierrez, Matteo Leonetti
    http://arxiv.org/abs/1906.06178v1

    • [cs.LG]Deep Learning Development Environment in Virtual Reality
    Kevin C. VanHorn, Meyer Zinn, Murat Can Cobanoglu
    http://arxiv.org/abs/1906.05925v1

    • [cs.LG]Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
    Guy Lorberbom, Chris J. Maddison, Nicolas Heess, Tamir Hazan, Daniel Tarlow
    http://arxiv.org/abs/1906.06062v1

    • [cs.LG]Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks
    Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh
    http://arxiv.org/abs/1906.06033v1

    • [cs.LG]Efficient N-Dimensional Convolutions via Higher-Order Factorization
    Jean Kossaifi, Adrian Bulat, Yannis Panagakis, Maja Pantic
    http://arxiv.org/abs/1906.06196v1

    • [cs.LG]Empirical study of extreme overfitting points of neural networks
    Daniil Merkulov, Ivan Oseledets
    http://arxiv.org/abs/1906.06295v1

    • [cs.LG]Epistemic Risk-Sensitive Reinforcement Learning
    Hannes Eriksson, Christos Dimitrakakis
    http://arxiv.org/abs/1906.06273v1

    • [cs.LG]Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets
    Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Sanjeev Arora, Rong Ge
    http://arxiv.org/abs/1906.06247v1

    • [cs.LG]Gradient Descent Maximizes the Margin of Homogeneous Neural Networks
    Kaifeng Lyu, Jian Li
    http://arxiv.org/abs/1906.05890v1

    • [cs.LG]InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers
    Zinan Lin, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh
    http://arxiv.org/abs/1906.06034v1

    • [cs.LG]Layered SGD: A Decentralized and Synchronous SGD Algorithm for Scalable Deep Neural Network Training
    Kwangmin Yu, Thomas Flynn, Shinjae Yoo, Nicholas D’Imperio
    http://arxiv.org/abs/1906.05936v1

    • [cs.LG]Learning to Forget for Meta-Learning
    Sungyong Baik, Seokil Hong, Kyoung Mu Lee
    http://arxiv.org/abs/1906.05895v1

    • [cs.LG]Model Agnostic Dual Quality Assessment for Adversarial Machine Learning and an Analysis of Current Neural Networks and Defenses
    Danilo Vasconcellos Vargas, Shashank Kotyan
    http://arxiv.org/abs/1906.06026v1

    • [cs.LG]Multigrid Neural Memory
    Tri Huynh, Michael Maire, Matthew R. Walter
    http://arxiv.org/abs/1906.05948v1

    • [cs.LG]Online Active Learning of Reject Option Classifiers
    Kulin Shah, Naresh Manwani
    http://arxiv.org/abs/1906.06166v1

    • [cs.LG]Provably Efficient $Q$-learning with Function Approximation via Distribution Shift Error Checking Oracle
    Simon S. Du, Yuping Luo, Ruosong Wang, Hanrui Zhang
    http://arxiv.org/abs/1906.06321v1

    • [cs.LG]Recurrent Neural Processes
    Timon Willi, Jonathan Masci, Jürgen Schmidhuber, Christian Osendorfer
    http://arxiv.org/abs/1906.05915v1

    • [cs.LG]Scalable Neural Architecture Search for 3D Medical Image Segmentation
    Sungwoong Kim, Ildoo Kim, Sungbin Lim, Woonhyuk Baek, Chiheon Kim, Hyungjoo Cho, Boogeon Yoon, Taesup Kim
    http://arxiv.org/abs/1906.05956v1

    • [cs.LG]Stochastic Proximal AUC Maximization
    Yunwen Lei, Yiming Ying
    http://arxiv.org/abs/1906.06053v1

    • [cs.LG]Sub-policy Adaptation for Hierarchical Reinforcement Learning
    Alexander C. Li, Carlos Florensa, Ignasi Clavera, Pieter Abbeel
    http://arxiv.org/abs/1906.05862v1

    • [cs.LG]Support vector machines on the D-Wave quantum annealer
    Dennis Willsch, Madita Willsch, Hans De Raedt, Kristel Michielsen
    http://arxiv.org/abs/1906.06283v1

    • [cs.LG]Towards Compact and Robust Deep Neural Networks
    Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
    http://arxiv.org/abs/1906.06110v1

    • [cs.LG]Towards Stable and Efficient Training of Verifiably Robust Neural Networks
    Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Duane Boning, Cho-Jui Hsieh
    http://arxiv.org/abs/1906.06316v1

    • [cs.LG]Variational Federated Multi-Task Learning
    Luca Corinzia, Joachim M. Buhmann
    http://arxiv.org/abs/1906.06268v1

    • [cs.LO]Dynamic Term-Modal Logics for Epistemic Planning
    Andreas Achen, Andrés Occhipinti Liberman, Rasmus K. Rendsvig
    http://arxiv.org/abs/1906.06047v1

    • [cs.LO]Extensions of Generic DOL for Generic Ontology Design Patterns
    Mihai Codescu, Bernd Krieg-Brückner, Till Mossakowski
    http://arxiv.org/abs/1906.06275v1

    • [cs.OH]FPScreen: A Rapid Similarity Search Tool for Massive Molecular Library Based on Molecular Fingerprint Comparison
    Lijun Wang, Jianbing Gong, Yingxia Zhang, Tianmou Liu, Junhui Gao
    http://arxiv.org/abs/1906.06170v1

    • [cs.SI]A model of anonymous influence with anti-conformist agents
    Michel Grabisch, Alexis Poindron, Agnieszka Rusinowska
    http://arxiv.org/abs/1906.06094v1

    • [cs.SI]An analysis of community structure in Brazilian political topic-based Twitter networks
    Camila P. S. Tautenhain, Rodrigo Francisquini, Mariá C. V. Nascimento
    http://arxiv.org/abs/1906.06315v1

    • [cs.SI]Disentangling Mixtures of Epidemics on Graphs
    Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
    http://arxiv.org/abs/1906.06057v1

    • [eess.AS]Speaker-Targeted Audio-Visual Models for Speech Recognition in Cocktail-Party Environments
    Guan-Lin Chao, William Chan, Ian Lane
    http://arxiv.org/abs/1906.05962v1

    • [eess.AS]Video-Driven Speech Reconstruction using Generative Adversarial Networks
    Konstantinos Vougioukas, Pingchuan Ma, Stavros Petridis, Maja Pantic
    http://arxiv.org/abs/1906.06301v1

    • [eess.IV]Deep neural network for fringe pattern filtering and normalisation
    Alan Reyes-Figueroa, Mariano Rivera
    http://arxiv.org/abs/1906.06224v1

    • [eess.IV]GAN-based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer’s Disease Diagnosis
    Changhee Han, Leonardo Rundo, Kohei Murao, Zoltán Ádám Milacski, Kazuki Umemoto, Hideki Nakayama, Shin’ichi Satoh
    http://arxiv.org/abs/1906.06114v1

    • [eess.IV]Global and Local Interpretability for Cardiac MRI Classification
    James R. Clough, Ilkay Oksuz, Esther Puyol-Anton, Bram Ruijsink, Andrew P. King, Julia A. Schnabel
    http://arxiv.org/abs/1906.06188v1

    • [eess.IV]Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification
    Christoph Haarburger, Michael Baumgartner, Daniel Truhn, Mirjam Broeckmann, Hannah Schneider, Simone Schwabing, Christiane Kuhl, Dorit Merhof
    http://arxiv.org/abs/1906.06058v1

    • [eess.SP]Cache-Aided Non-Orthogonal Multiple Access for 5G-Enabled Vehicular Networks
    Sanjeev Gurugopinath, Paschalis C. Sofotasios, Yousof Al-Hammadi, Sami Muhaidat
    http://arxiv.org/abs/1906.06025v1

    • [eess.SP]Convolutional Neural Network based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis
    Jiajia Guo, Chao-Kai Wen, Shi Jin, Geoffrey Ye Li
    http://arxiv.org/abs/1906.06007v1

    • [eess.SP]Massive MIMO Radar for Target Detection
    Stefano Fortunati, Luca Sanguinetti, Fulvio Gini, Maria S. Greco
    http://arxiv.org/abs/1906.06191v1

    • [eess.SP]Multi-Carrier Agile Phased Array Radar
    Tianyao Huang, Nir Shlezinger, Xingyu Xu, Dingyou Ma, Yimin Liu, Yonina C. Eldar
    http://arxiv.org/abs/1906.06289v1

    • [eess.SP]Self-Tuning Sectorization: Deep Reinforcement Learning Meets Broadcast Beam Optimization
    Rubayet Shafin, Hao Chen, Young Han Nam, Sooyoung Hur, Jeongho Park, Jianzhong, Zhang, Jeffrey Reed, Lingjia Liu
    http://arxiv.org/abs/1906.06021v1

    • [math.CO]Complexity of Dependencies in Bounded Domains, Armstrong Codes, and Generalizations
    Yeow Meng Chee, Hui Zhang, Xiande Zhang
    http://arxiv.org/abs/1906.06070v1

    • [math.PR]Peskun-Tierney ordering for Markov chain and process Monte Carlo: beyond the reversible scenario
    Christophe Andrieu, Samuel Livingstone
    http://arxiv.org/abs/1906.06197v1

    • [math.ST]A technical note on divergence of the Wald statistic
    Jean-Marie Dufour, Eric Renault, Victoria Zinde-Walsh
    http://arxiv.org/abs/1906.05951v1

    • [physics.comp-ph]Computing Committor Functions for the Study of Rare Events Using Deep Learning
    Qianxiao Li, Bo Lin, Weiqing Ren
    http://arxiv.org/abs/1906.06285v1

    • [physics.data-an]hepaccelerate: Fast Analysis of Columnar Collider Data
    Joosep Pata, Maria Spiropulu
    http://arxiv.org/abs/1906.06242v1

    • [physics.geo-ph]Machine Learning Approach to Earthquake Rupture Dynamics
    Sabber Ahamed, Eric G. Daub
    http://arxiv.org/abs/1906.06250v1

    • [stat.AP]Comparison of Methods for the Assessment of Nonlinearity in Short-Term Heart Rate Variability under different Physiopathological States
    Luca Faes, Manuel Gòmez-Extremera, Riccardo Pernice, Pedro Carpena, Giandomenico Nollo, Alberto Porta, Pedro Bernaola-Galvàn
    http://arxiv.org/abs/1906.05918v1

    • [stat.AP]Early Detection of Long Term Evaluation Criteria in Online Controlled Experiments
    Yoni Schamroth, Liron Gat Kahlon, Boris Rabinovich, David Steinberg
    http://arxiv.org/abs/1906.05959v1

    • [stat.AP]Exploiting Convexification for Bayesian Optimal Sensor Placement by Maximization of Mutual Information
    Pinaky Bhattacharyya, James L. Beck
    http://arxiv.org/abs/1906.05953v1

    • [stat.AP]Machine Learning on EPEX Order Books: Insights and Forecasts
    Simon Schnürch, Andreas Wagner
    http://arxiv.org/abs/1906.06248v1

    • [stat.CO]Robustly estimating the marginal likelihood for cognitive models via importance sampling
    Minh-Ngoc Tran, Marcel Scharth, David Gunawan, Robert Kohn, Scott D. Brown, Guy E. Hawkins
    http://arxiv.org/abs/1906.06020v1

    • [stat.ME]A Latent Gaussian Process Model for Analyzing Intensive Longitudinal Data
    Yunxiao Chen, Siliang Zhang
    http://arxiv.org/abs/1906.06095v1

    • [stat.ME]Identify treatment effect patterns for personalised decisions
    Jiuyong Li, Saisai Ma, Lin Liu, Thuc Duy Le, Jixue Liu, Yizhao Han
    http://arxiv.org/abs/1906.06080v1

    • [stat.ME]Statistical Inference for Generative Models with Maximum Mean Discrepancy
    Francois-Xavier Briol, Alessandro Barp, Andrew B. Duncan, Mark Girolami
    http://arxiv.org/abs/1906.05944v1

    • [stat.ML]$(1 + \varepsilon)$-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets
    Maxim Borisyak, Artem Ryzhikov, Andrey Ustyuzhanin, Denis Derkach, Fedor Ratnikov, Olga Mineeva
    http://arxiv.org/abs/1906.06096v1

    • [stat.ML]A stochastic alternating minimizing method for sparse phase retrieval
    Jianfeng Cai, Yuling Jiao, Xiliang Lu, Juntao You
    http://arxiv.org/abs/1906.05967v1

    • [stat.ML]Distributionally Robust Counterfactual Risk Minimization
    Louis Faury, Ugo Tanielian, Flavian Vasile, Elena Smirnova, Elvis Dohmatob
    http://arxiv.org/abs/1906.06211v1

    • [stat.ML]Empirical Bayes Method for Boltzmann Machines
    Muneki Yasuda, Tomoyuki Obuchi
    http://arxiv.org/abs/1906.06002v1

    • [stat.ML]Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting
    Léo Gautheron, Pascal Germain, Amaury Habrard, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
    http://arxiv.org/abs/1906.06203v1

    • [stat.ML]Spectrally-truncated kernel ridge regression and its free lunch
    Arash A. Amini
    http://arxiv.org/abs/1906.06276v1