astro-ph.CO - 宇宙学和天体物理学

    cs.AI - 人工智能 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.DS - 数据结构与算法 cs.ET - 新兴技术 cs.GR - 计算机图形学 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.MM - 多媒体 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.GN - 一般经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.NA - 数值分析 math.PR - 概率 math.ST - 统计理论 q-fin.RM - 风险管理 quant-ph - 量子物理 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.CO]CMB-GAN: Fast Simulations of Cosmic Microwave background anisotropy maps using Deep Learning
    • [cs.AI]Evaluation of a Recommender System for Assisting Novice Game Designers
    • [cs.AI]Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics
    • [cs.AI]Is Deep Reinforcement Learning Really Superhuman on Atari?
    • [cs.AI]Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
    • [cs.AI]Semi-Supervised Learning using Differentiable Reasoning
    • [cs.CL]AmazonQA: A Review-Based Question Answering Task
    • [cs.CL]Attention is not not Explanation
    • [cs.CL]EASSE: Easier Automatic Sentence Simplification Evaluation
    • [cs.CL]Fine-grained Information Status Classification Using Discourse Context-Aware Self-Attention
    • [cs.CL]Getting To Know You: User Attribute Extraction from Dialogues
    • [cs.CL]IMS-Speech: A Speech to Text Tool
    • [cs.CL]Improving Generalization in Coreference Resolution via Adversarial Training
    • [cs.CL]Incorporating Relation Knowledge into Commonsense Reading Comprehension with Multi-task Learning
    • [cs.CL]LSTM vs. GRU vs. Bidirectional RNN for script generation
    • [cs.CL]Learn How to Cook a New Recipe in a New House: Using Map Familiarization, Curriculum Learning, and Common Sense to Learn Families of Text-Based Adventure Games
    • [cs.CL]Neural Machine Translation with Noisy Lexical Constraints
    • [cs.CL]Offensive Language and Hate Speech Detection for Danish
    • [cs.CL]Playing log(N)-Questions over Sentences
    • [cs.CL]StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
    • [cs.CL]Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning
    • [cs.CV]Boosted GAN with Semantically Interpretable Information for Image Inpainting
    • [cs.CV]Construction of efficient detectors for character information recognition
    • [cs.CV]Detecting semantic anomalies
    • [cs.CV]Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation
    • [cs.CV]Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation
    • [cs.CV]Interpolated Convolutional Networks for 3D Point Cloud Understanding
    • [cs.CV]Is This The Right Place? Geometric-Semantic Pose Verification for Indoor Visual Localization
    • [cs.CV]Learning Target-oriented Dual Attention for Robust RGB-T Tracking
    • [cs.CV]Learning elementary structures for 3D shape generation and matching
    • [cs.CV]MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
    • [cs.CV]Matrix Nets: A New Deep Architecture for Object Detection
    • [cs.CV]Multi-timescale Trajectory Prediction for Abnormal Human Activity Detection
    • [cs.CV]Point-Based Multi-View Stereo Network
    • [cs.CV]Predicting 3D Human Dynamics from Video
    • [cs.CV]Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data
    • [cs.CV]Super-resolution of Omnidirectional Images Using Adversarial Learning
    • [cs.CV]Three Branches: Detecting Actions With Richer Features
    • [cs.CV]Why Does a Visual Question Have Different Answers?
    • [cs.DB]Adaptive Learning of Aggregate Analytics under Dynamic Workloads
    • [cs.DB]Linking Graph Entities with Multiplicity and Provenance
    • [cs.DC]A Scalable, Portable, and Memory-Efficient Lock-Free FIFO Queue
    • [cs.DC]Industrial Control via Application Containers: Migrating from Bare-Metal to IAAS
    • [cs.DC]Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations
    • [cs.DS]Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions
    • [cs.ET]Implementing Binarized Neural Networks with Magnetoresistive RAM without Error Correction
    • [cs.GR]SDM-NET: Deep Generative Network for Structured Deformable Mesh
    • [cs.HC]Modeling Personality vs. Modeling Personalidad: In-the-wild Mobile Data Analysis in Five Countries Suggests Cultural Impact on Personality Models
    • [cs.IR]Complicated Table Structure Recognition
    • [cs.IT]Classes of Full-Duplex Channels with Capacity Achieved Without Adaptation
    • [cs.IT]Context-Aware Information Lapse for Timely Status Updates in Remote Control Systems
    • [cs.IT]Efficient Resource Allocation for Mobile-Edge Computing Networks with NOMA: Completion Time and Energy Minimization
    • [cs.IT]On Product Codes with Probabilistic Amplitude Shaping for High-Throughput Fiber-Optic Systems
    • [cs.IT]On Steane-Enlargement of Quantum Codes from Cartesian Product Point Sets
    • [cs.IT]Optimizations with Intelligent Reflecting Surfaces (IRSs) in 6G Wireless Networks: Power Control, Quality of Service, Max-Min Fair Beamforming for Unicast, Broadcast, and Multicast with Multi-antenna Mobile Users and Multiple IRSs
    • [cs.IT]V2X-Based Vehicular Positioning: Opportunities, Challenges, and Future Directions
    • [cs.LG]Adversarial Neural Pruning
    • [cs.LG]Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders
    • [cs.LG]Behaviour Suite for Reinforcement Learning
    • [cs.LG]Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking
    • [cs.LG]Einconv: Exploring Unexplored Tensor Decompositions for Convolutional Neural Networks
    • [cs.LG]Exploiting Parallelism Opportunities with Deep Learning Frameworks
    • [cs.LG]Feature Partitioning for Efficient Multi-Task Architectures
    • [cs.LG]Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model
    • [cs.LG]L2P: An Algorithm for Estimating Heavy-tailed Outcomes
    • [cs.LG]Multi-View Fuzzy Clustering with The Alternative Learning between Shared Hidden Space and Partition
    • [cs.LG]Multi-view Clustering with the Cooperation of Visible and Hidden Views
    • [cs.LG]Neural Text Generation with Unlikelihood Training
    • [cs.LG]Null Space Analysis for Class-Specific Discriminant Learning
    • [cs.LG]On Defending Against Label Flipping Attacks on Malware Detection Systems
    • [cs.LG]On the Convergence of AdaBound and its Connection to SGD
    • [cs.LG]Online Continual Learning with Maximally Interfered Retrieval
    • [cs.LG]Regional Tree Regularization for Interpretability in Black Box Models
    • [cs.LG]Superstition in the Network: Deep Reinforcement Learning Plays Deceptive Games
    • [cs.LG]metric-learn: Metric Learning Algorithms in Python
    • [cs.MA]A sub-modular receding horizon solution for mobile multi-agent persistent monitoring
    • [cs.MM]Exploiting Multi-domain Visual Information for Fake News Detection
    • [cs.NI]ConfigTron: Tackling network diversity with heterogeneous configurations
    • [cs.NI]Reinforcement Learning based Interconnection Routing for Adaptive Traffic Optimization
    • [cs.RO]Cataglyphis ant navigation strategies solve the global localization problem in robots with binary sensors
    • [cs.RO]Deep Dexterous Grasping of Novel Objects from a Single View
    • [cs.RO]General Hand Guidance Framework using Microsoft HoloLens
    • [cs.RO]Learning to Detect Collisions for Continuum Manipulators without a Prior Model
    • [cs.RO]Loop Closure Detection in Closed Environments
    • [cs.SI]Deep Hashing for Signed Social Network Embedding
    • [cs.SI]Modularity belief propagation on multilayer networks to detect significant community structure
    • [cs.SI]Network constraints on the mixing patterns of binary node metadata
    • [econ.GN]Wasserstein Index Generation Model: Automatic Generation of Time-series Index with Application to Economic Policy Uncertainty
    • [eess.AS]End-to-End Multi-Speaker Speech Recognition using Speaker Embeddings and Transfer Learning
    • [eess.IV]Collaborative Multi-agent Learning for MR Knee Articular Cartilage Segmentation
    • [eess.IV]Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides
    • [eess.IV]Generalizing Deep Whole Brain Segmentation for Pediatric and Post-Contrast MRI with Augmented Transfer Learning
    • [eess.IV]Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection
    • [eess.IV]Structural Similarity based Anatomical and Functional Brain Imaging Fusion
    • [eess.SP]Learn to Compress CSI and Allocate Resources in Vehicular Networks
    • [math.NA]Tensor-based EDMD for the Koopman analysis of high-dimensional systems
    • [math.PR]Growth of Common Friends in a Preferential Attachment Model
    • [math.ST]A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates
    • [math.ST]Elements of asymptotic theory with outer probability measures
    • [math.ST]Identifying shifts between two regression curves
    • [math.ST]Principal symmetric space analysis
    • [math.ST]Sharp Guarantees for Solving Random Equations with One-Bit Information
    • [math.ST]The bias of isotonic regression
    • [q-fin.RM]Forecast Encompassing Tests for the Expected Shortfall
    • [quant-ph]Quantum adiabatic machine learning with zooming
    • [stat.AP]Blinded sample size re-estimation in equivalence testing
    • [stat.AP]Inverse Parametric Uncertain Identification using Polynomial Chaos and high-order Moment Matching benchmarked on a Wet Friction Clutch
    • [stat.CO]Bayesian automated posterior repartitioning for nested sampling
    • [stat.ME]A Groupwise Approach for Inferring Heterogeneous Treatment Effects in Causal Inference
    • [stat.ME]Optimal Estimation of Generalized Average Treatment Effects using Kernel Optimal Matching
    • [stat.ML]Comparison theorems on large-margin learning
    • [stat.ML]DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data

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    • [astro-ph.CO]CMB-GAN: Fast Simulations of Cosmic Microwave background anisotropy maps using Deep Learning
    Amit Mishra, Pranath Reddy, Rahul Nigam
    http://arxiv.org/abs/1908.04682v1

    • [cs.AI]Evaluation of a Recommender System for Assisting Novice Game Designers
    Tiago Machado, Daniel Gopstein, Oded Nov, Angela Wang, Andy Nealen, Julian Togelius
    http://arxiv.org/abs/1908.04629v1

    • [cs.AI]Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics
    Saurabh Daptardar, Paul Schrater, Xaq Pitkow
    http://arxiv.org/abs/1908.04696v1

    • [cs.AI]Is Deep Reinforcement Learning Really Superhuman on Atari?
    Marin Toromanoff, Emilie Wirbel, Fabien Moutarde
    http://arxiv.org/abs/1908.04683v1

    • [cs.AI]Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
    Tom Everitt, Marcus Hutter
    http://arxiv.org/abs/1908.04734v1

    • [cs.AI]Semi-Supervised Learning using Differentiable Reasoning
    Emile van Krieken, Erman Acar, Frank van Harmelen
    http://arxiv.org/abs/1908.04700v1

    • [cs.CL]AmazonQA: A Review-Based Question Answering Task
    Mansi Gupta, Nitish Kulkarni, Raghuveer Chanda, Anirudha Rayasam, Zachary C Lipton
    http://arxiv.org/abs/1908.04364v1

    • [cs.CL]Attention is not not Explanation
    Sarah Wiegreffe, Yuval Pinter
    http://arxiv.org/abs/1908.04626v1

    • [cs.CL]EASSE: Easier Automatic Sentence Simplification Evaluation
    Fernando Alva-Manchego, Louis Martin, Carolina Scarton, Lucia Specia
    http://arxiv.org/abs/1908.04567v1

    • [cs.CL]Fine-grained Information Status Classification Using Discourse Context-Aware Self-Attention
    Yufang Hou
    http://arxiv.org/abs/1908.04755v1

    • [cs.CL]Getting To Know You: User Attribute Extraction from Dialogues
    Chien-Sheng Wu, Andrea Madotto, Zhaojiang Lin, Peng Xu, Pascale Fung
    http://arxiv.org/abs/1908.04621v1

    • [cs.CL]IMS-Speech: A Speech to Text Tool
    Pavel Denisov, Ngoc Thang Vu
    http://arxiv.org/abs/1908.04743v1

    • [cs.CL]Improving Generalization in Coreference Resolution via Adversarial Training
    Sanjay Subramanian, Dan Roth
    http://arxiv.org/abs/1908.04728v1

    • [cs.CL]Incorporating Relation Knowledge into Commonsense Reading Comprehension with Multi-task Learning
    Jiangnan Xia, Chen Wu, Ming Yan
    http://arxiv.org/abs/1908.04530v1

    • [cs.CL]LSTM vs. GRU vs. Bidirectional RNN for script generation
    Sanidhya Mangal, Poorva Joshi, Rahul Modak
    http://arxiv.org/abs/1908.04332v1

    • [cs.CL]Learn How to Cook a New Recipe in a New House: Using Map Familiarization, Curriculum Learning, and Common Sense to Learn Families of Text-Based Adventure Games
    Xusen Yin, Jonathan May
    http://arxiv.org/abs/1908.04777v1

    • [cs.CL]Neural Machine Translation with Noisy Lexical Constraints
    Huayang Li, Guoping Huang, Lemao Liu
    http://arxiv.org/abs/1908.04664v1

    • [cs.CL]Offensive Language and Hate Speech Detection for Danish
    Gudbjartur Ingi Sigurbergsson, Leon Derczynski
    http://arxiv.org/abs/1908.04531v1

    • [cs.CL]Playing log(N)-Questions over Sentences
    Peter Potash, Kaheer Suleman
    http://arxiv.org/abs/1908.04660v1

    • [cs.CL]StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
    Wei Wang, Bin Bi, Ming Yan, Chen Wu, Zuyi Bao, Liwei Peng, Luo Si
    http://arxiv.org/abs/1908.04577v1

    • [cs.CL]Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning
    Surabhi Datta, Yuqi Si, Laritza Rodriguez, Sonya E Shooshan, Dina Demner-Fushman, Kirk Roberts
    http://arxiv.org/abs/1908.04485v1

    • [cs.CV]Boosted GAN with Semantically Interpretable Information for Image Inpainting
    Ang Li, Jianzhong Qi, Rui Zhang, Ramamohanarao Kotagiri
    http://arxiv.org/abs/1908.04503v1

    • [cs.CV]Construction of efficient detectors for character information recognition
    A. A. Telnykh, I. V. Nuidel, Yu. R. Samorodova
    http://arxiv.org/abs/1908.04634v1

    • [cs.CV]Detecting semantic anomalies
    Faruk Ahmed, Aaron Courville
    http://arxiv.org/abs/1908.04388v1

    • [cs.CV]Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation
    Hyeon Woo Lee, Mert R. Sabuncu, Adrian V. Dalca
    http://arxiv.org/abs/1908.04466v1

    • [cs.CV]Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation
    Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, Sungroh Yoon
    http://arxiv.org/abs/1908.04501v1

    • [cs.CV]Interpolated Convolutional Networks for 3D Point Cloud Understanding
    Jiageng Mao, Xiaogang Wang, Hongsheng Li
    http://arxiv.org/abs/1908.04512v1

    • [cs.CV]Is This The Right Place? Geometric-Semantic Pose Verification for Indoor Visual Localization
    Hajime Taira, Ignacio Rocco, Jiri Sedlar, Masatoshi Okutomi, Josef Sivic, Tomas Pajdla, Torsten Sattler, Akihiko Torii
    http://arxiv.org/abs/1908.04598v1

    • [cs.CV]Learning Target-oriented Dual Attention for Robust RGB-T Tracking
    Rui Yang, Yabin Zhu, Xiao Wang, Chenglong Li, Jin Tang
    http://arxiv.org/abs/1908.04441v1

    • [cs.CV]Learning elementary structures for 3D shape generation and matching
    Theo Deprelle, Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell, Mathieu Aubry
    http://arxiv.org/abs/1908.04725v1

    • [cs.CV]MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
    Ke Yan, Youbao Tang, Yifan Peng, Veit Sandfort, Mohammadhadi Bagheri, Zhiyong Lu, Ronald M. Summers
    http://arxiv.org/abs/1908.04373v1

    • [cs.CV]Matrix Nets: A New Deep Architecture for Object Detection
    Abdulah Rashwan, Agastya Kalra, Pascal Poupart
    http://arxiv.org/abs/1908.04646v1

    • [cs.CV]Multi-timescale Trajectory Prediction for Abnormal Human Activity Detection
    Royston Rodrigues, Neha Bhargava, Rajbabu Velmurugan, Subhasis Chaudhuri
    http://arxiv.org/abs/1908.04321v1

    • [cs.CV]Point-Based Multi-View Stereo Network
    Rui Chen, Songfang Han, Jing Xu, Hao Su
    http://arxiv.org/abs/1908.04422v1

    • [cs.CV]Predicting 3D Human Dynamics from Video
    Jason Y. Zhang, Panna Felsen, Angjoo Kanazawa, Jitendra Malik
    http://arxiv.org/abs/1908.04781v1

    • [cs.CV]Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data
    Mikaela Angelina Uy, Quang-Hieu Pham, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung
    http://arxiv.org/abs/1908.04616v1

    • [cs.CV]Super-resolution of Omnidirectional Images Using Adversarial Learning
    Cagri Ozcinar, Aakanksha Rana, Aljosa Smolic
    http://arxiv.org/abs/1908.04297v1

    • [cs.CV]Three Branches: Detecting Actions With Richer Features
    Jin Xia, Jiajun Tang, Cewu Lu
    http://arxiv.org/abs/1908.04519v1

    • [cs.CV]Why Does a Visual Question Have Different Answers?
    Nilavra Bhattacharya, Qing Li, Danna Gurari
    http://arxiv.org/abs/1908.04342v1

    • [cs.DB]Adaptive Learning of Aggregate Analytics under Dynamic Workloads
    Fotis Savva, Christos Anagnostopoulos, Peter Triantafillou
    http://arxiv.org/abs/1908.04772v1

    • [cs.DB]Linking Graph Entities with Multiplicity and Provenance
    Jixue Liu, Selasi Kwashie, Jiuyong Li, Lin Liu, Michael Bewong
    http://arxiv.org/abs/1908.04464v1

    • [cs.DC]A Scalable, Portable, and Memory-Efficient Lock-Free FIFO Queue
    Ruslan Nikolaev
    http://arxiv.org/abs/1908.04511v1

    • [cs.DC]Industrial Control via Application Containers: Migrating from Bare-Metal to IAAS
    Florian Hofer, Martin A. Sehr, Antonio Iannopollo, Ines Ugalde, Alberto Sangiovanni-Vincentelli, Barbara Russo
    http://arxiv.org/abs/1908.04465v1

    • [cs.DC]Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations
    Shigang Li, Tal Ben-Nun, Salvatore Di Girolamo, Dan Alistarh, Torsten Hoefler
    http://arxiv.org/abs/1908.04207v2

    • [cs.DS]Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions
    Jeffrey M. Dudek, Leonardo Dueñas-Osorio, Moshe Y. Vardi
    http://arxiv.org/abs/1908.04381v1

    • [cs.ET]Implementing Binarized Neural Networks with Magnetoresistive RAM without Error Correction
    Tifenn Hirtzlin, Bogdan Penkovsky, Jacques-Olivier Klein, Nicolas Locatelli, Adrien F. Vincent, Marc Bocquet, Jean-Michel Portal, Damien Querlioz
    http://arxiv.org/abs/1908.04085v1

    • [cs.GR]SDM-NET: Deep Generative Network for Structured Deformable Mesh
    Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai, Hao Zhang
    http://arxiv.org/abs/1908.04520v1

    • [cs.HC]Modeling Personality vs. Modeling Personalidad: In-the-wild Mobile Data Analysis in Five Countries Suggests Cultural Impact on Personality Models
    Mohammed Khwaja, Sumer S. Vaid, Sara Zannone, Gabriella M. Harari, A. Aldo Faisal, Aleksandar Matic
    http://arxiv.org/abs/1908.04617v1

    • [cs.IR]Complicated Table Structure Recognition
    Zewen Chi, Heyan Huang, Heng-Da Xu, Houjin Yu, Wanxuan Yin, Xian-Ling Mao
    http://arxiv.org/abs/1908.04729v1

    • [cs.IT]Classes of Full-Duplex Channels with Capacity Achieved Without Adaptation
    Daewon Seo, Anas Chaaban, Lav R. Varshney, Mohamed-Slim Alouini
    http://arxiv.org/abs/1908.04327v1

    • [cs.IT]Context-Aware Information Lapse for Timely Status Updates in Remote Control Systems
    Xi Zheng, Sheng Zhou, Zhisheng Niu
    http://arxiv.org/abs/1908.04446v1

    • [cs.IT]Efficient Resource Allocation for Mobile-Edge Computing Networks with NOMA: Completion Time and Energy Minimization
    Zhaohui Yang, Cunhua Pan, Jiancao Hou, Mohammad Shikh-Bahaei
    http://arxiv.org/abs/1908.04689v1

    • [cs.IT]On Product Codes with Probabilistic Amplitude Shaping for High-Throughput Fiber-Optic Systems
    Alireza Sheikh, Alexandre Graell i Amat, Alex Alvarado
    http://arxiv.org/abs/1908.04205v2

    • [cs.IT]On Steane-Enlargement of Quantum Codes from Cartesian Product Point Sets
    René Bødker Christensen, Olav Geil
    http://arxiv.org/abs/1908.04560v1

    • [cs.IT]Optimizations with Intelligent Reflecting Surfaces (IRSs) in 6G Wireless Networks: Power Control, Quality of Service, Max-Min Fair Beamforming for Unicast, Broadcast, and Multicast with Multi-antenna Mobile Users and Multiple IRSs
    Jun Zhao
    http://arxiv.org/abs/1908.03965v2

    • [cs.IT]V2X-Based Vehicular Positioning: Opportunities, Challenges, and Future Directions
    Seung-Woo Ko, Hyukjin Chae, Kaifeng Han, Seungmin Lee, Kaibin Huang
    http://arxiv.org/abs/1908.04606v1

    • [cs.LG]Adversarial Neural Pruning
    Divyam Madaan, Sung Ju Hwang
    http://arxiv.org/abs/1908.04355v1

    • [cs.LG]Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders
    Esther Puyol-Antón, Bram Ruijsink, James R. Clough, Ilkay Oksuz, Daniel Rueckert, Reza Razavi, Andrew P. King
    http://arxiv.org/abs/1908.04538v1

    • [cs.LG]Behaviour Suite for Reinforcement Learning
    Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepezvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver, Hado Van Hasselt
    http://arxiv.org/abs/1908.03568v2

    • [cs.LG]Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking
    Yue Wang, Yao Wan, Chenwei Zhang, Lixin Cui, Lu Bai, Philip S. Yu
    http://arxiv.org/abs/1908.04573v1

    • [cs.LG]Einconv: Exploring Unexplored Tensor Decompositions for Convolutional Neural Networks
    Kohei Hayashi, Taiki Yamaguchi, Yohei Sugawara, Shin-ichi Maeda
    http://arxiv.org/abs/1908.04471v1

    • [cs.LG]Exploiting Parallelism Opportunities with Deep Learning Frameworks
    Yu Emma Wang, Carole-Jean Wu, Xiaodong Wang, Kim Hazelwood, David Brooks
    http://arxiv.org/abs/1908.04705v1

    • [cs.LG]Feature Partitioning for Efficient Multi-Task Architectures
    Alejandro Newell, Lu Jiang, Chong Wang, Li-Jia Li, Jia Deng
    http://arxiv.org/abs/1908.04339v1

    • [cs.LG]Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model
    Wenbo Gong, Sebastian Tschiatschek, Richard Turner, Sebastian Nowozin, José Miguel Hernández-Lobato
    http://arxiv.org/abs/1908.04537v1

    • [cs.LG]L2P: An Algorithm for Estimating Heavy-tailed Outcomes
    Xindi Wang, Onur Varol, Tina Eliassi-Rad
    http://arxiv.org/abs/1908.04628v1

    • [cs.LG]Multi-View Fuzzy Clustering with The Alternative Learning between Shared Hidden Space and Partition
    Zhaohong Deng, Chen Cui, Peng Xu, Ling Liang, Haoran Chen, Te Zhang, Shitong Wang
    http://arxiv.org/abs/1908.04771v1

    • [cs.LG]Multi-view Clustering with the Cooperation of Visible and Hidden Views
    Zhaohong Deng, Ruixiu Liu, Te Zhang, Peng Xu, Kup-Sze Choi, Bin Qin, Shitong Wang
    http://arxiv.org/abs/1908.04766v1

    • [cs.LG]Neural Text Generation with Unlikelihood Training
    Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston
    http://arxiv.org/abs/1908.04319v1

    • [cs.LG]Null Space Analysis for Class-Specific Discriminant Learning
    Jenni Raitoharju, Alexandros Iosifidis
    http://arxiv.org/abs/1908.04562v1

    • [cs.LG]On Defending Against Label Flipping Attacks on Malware Detection Systems
    Rahim Taheri, Reza Javidan, Mohammad Shojafar, Zahra Pooranian, Ali Miri, Mauro Conti
    http://arxiv.org/abs/1908.04473v1

    • [cs.LG]On the Convergence of AdaBound and its Connection to SGD
    Pedro Savarese
    http://arxiv.org/abs/1908.04457v1

    • [cs.LG]Online Continual Learning with Maximally Interfered Retrieval
    Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Laurent Charlin, Tinne Tuytelaars
    http://arxiv.org/abs/1908.04742v1

    • [cs.LG]Regional Tree Regularization for Interpretability in Black Box Models
    Mike Wu, Sonali Parbhoo, Michael Hughes, Ryan Kindle, Leo Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez
    http://arxiv.org/abs/1908.04494v1

    • [cs.LG]Superstition in the Network: Deep Reinforcement Learning Plays Deceptive Games
    Philip Bontrager, Ahmed Khalifa, Damien Anderson, Matthew Stephenson, Christoph Salge, Julian Togelius
    http://arxiv.org/abs/1908.04436v1

    • [cs.LG]metric-learn: Metric Learning Algorithms in Python
    William de Vazelhes, CJ Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet
    http://arxiv.org/abs/1908.04710v1

    • [cs.MA]A sub-modular receding horizon solution for mobile multi-agent persistent monitoring
    Navid Rezazadeh, Solmaz S. Kia
    http://arxiv.org/abs/1908.04425v1

    • [cs.MM]Exploiting Multi-domain Visual Information for Fake News Detection
    Peng Qi, Juan Cao, Tianyun Yang, Junbo Guo, Jintao Li
    http://arxiv.org/abs/1908.04472v1

    • [cs.NI]ConfigTron: Tackling network diversity with heterogeneous configurations
    Usama Naseer, Theophilus Benson
    http://arxiv.org/abs/1908.04518v1

    • [cs.NI]Reinforcement Learning based Interconnection Routing for Adaptive Traffic Optimization
    Sheng-Chun Kao, Chao-Han Huck Yang, Pin-Yu Chen, Xiaoli Ma, Tushar Krishna
    http://arxiv.org/abs/1908.04484v1

    • [cs.RO]Cataglyphis ant navigation strategies solve the global localization problem in robots with binary sensors
    Nils Rottmann, Ralf Bruder, Achim Schweikard, Elmar Rueckert
    http://arxiv.org/abs/1908.04564v1

    • [cs.RO]Deep Dexterous Grasping of Novel Objects from a Single View
    Umit Rusen Aktas, Chao Zhao, Marek Kopicki, Ales Leonardis, Jeremy L. Wyatt
    http://arxiv.org/abs/1908.04293v1

    • [cs.RO]General Hand Guidance Framework using Microsoft HoloLens
    David Puljiz, Erik Stöhr, Katharina S. Riesterer, Björn Hein, Torsten Kröger
    http://arxiv.org/abs/1908.04692v1

    • [cs.RO]Learning to Detect Collisions for Continuum Manipulators without a Prior Model
    Shahriar Sefati, Shahin Sefati, Iulian Iordachita, Russell H. Taylor, Mehran Armand
    http://arxiv.org/abs/1908.04354v1

    • [cs.RO]Loop Closure Detection in Closed Environments
    Nils Rottmann, Ralf Bruder, Achim Schweikard, Elmar Rueckert
    http://arxiv.org/abs/1908.04558v1

    • [cs.SI]Deep Hashing for Signed Social Network Embedding
    Jia-Nan Guo, Xian-Ling Mao, Xiao-Jian Jiang, Ying-Xiang Sun, He-Yan Huang, Wei Wei
    http://arxiv.org/abs/1908.04007v2

    • [cs.SI]Modularity belief propagation on multilayer networks to detect significant community structure
    William H. Weir, Benjamin Walker, Lenka Zdeborová, Peter J. Mucha
    http://arxiv.org/abs/1908.04653v1

    • [cs.SI]Network constraints on the mixing patterns of binary node metadata
    Matteo Cinelli, Leto Peel, Antonio Iovanella, Jean-Charles Delvenne
    http://arxiv.org/abs/1908.04588v1

    • [econ.GN]Wasserstein Index Generation Model: Automatic Generation of Time-series Index with Application to Economic Policy Uncertainty
    Fangzhou Xie
    http://arxiv.org/abs/1908.04369v1

    • [eess.AS]End-to-End Multi-Speaker Speech Recognition using Speaker Embeddings and Transfer Learning
    Pavel Denisov, Ngoc Thang Vu
    http://arxiv.org/abs/1908.04737v1

    • [eess.IV]Collaborative Multi-agent Learning for MR Knee Articular Cartilage Segmentation
    Chaowei Tan, Zhennan Yan, Shaoting Zhang, Kang Li, Dimitris N. Metaxas
    http://arxiv.org/abs/1908.04469v1

    • [eess.IV]Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides
    Christian Marzahl, Marc Aubreville, Christof A. Bertram, Jason Stayt, Anne-Katherine Jasensky, Florian Bartenschlager, Marco Fragoso-Garcia, Ann K. Barton, Svenja Elsemann, Samir Jabari, Jens Krauth, Prathmesh Madhu, Jörn Voigt, Jenny Hill, Robert Klopfleisch, Andreas Maier
    http://arxiv.org/abs/1908.04767v1

    • [eess.IV]Generalizing Deep Whole Brain Segmentation for Pediatric and Post-Contrast MRI with Augmented Transfer Learning
    Camilo Bermudez, Justin Blaber, Samuel W. Remedios, Jess E. Reynolds, Catherine Lebel, Maureen McHugo, Stephan Heckers, Yuankai Huo, Bennett A. Landman
    http://arxiv.org/abs/1908.04702v1

    • [eess.IV]Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection
    Maxim Pisov, Mikhail Goncharov, Nadezhda Kurochkina, Sergey Morozov, Victor Gombolevsky, Valeria Chernina, Anton Vladzymyrskyy, Ksenia Zamyatina, Anna Cheskova, Igor Pronin, Michael Shifrin, Mikhail Belyaev
    http://arxiv.org/abs/1908.04568v1

    • [eess.IV]Structural Similarity based Anatomical and Functional Brain Imaging Fusion
    Nishant Kumar, Nico Hoffmann, Martin Oelschlägel, Edmund Koch, Matthias Kirsch, Stefan Gumhold
    http://arxiv.org/abs/1908.03958v2

    • [eess.SP]Learn to Compress CSI and Allocate Resources in Vehicular Networks
    Liang Wang, Hao Ye, Le Liang, Geoffrey Ye Li
    http://arxiv.org/abs/1908.04685v1

    • [math.NA]Tensor-based EDMD for the Koopman analysis of high-dimensional systems
    Feliks Nüske, Patrick Gelß, Stefan Klus, Cecilia Clementi
    http://arxiv.org/abs/1908.04741v1

    • [math.PR]Growth of Common Friends in a Preferential Attachment Model
    Bikramjit Das, Souvik Ghosh
    http://arxiv.org/abs/1908.04510v1

    • [math.ST]A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates
    Zhixian Lei, Kyle Luh, Prayaag Venkat, Fred Zhang
    http://arxiv.org/abs/1908.04468v1

    • [math.ST]Elements of asymptotic theory with outer probability measures
    Jeremie Houssineau, Neil K. Chada, Emmanuel Delande
    http://arxiv.org/abs/1908.04331v1

    • [math.ST]Identifying shifts between two regression curves
    Holger Dette, Subhra Sankar Dhar, Weichi Wu
    http://arxiv.org/abs/1908.04328v1

    • [math.ST]Principal symmetric space analysis
    Stephen R Marsland, Robert I McLachlan, Charles Curry
    http://arxiv.org/abs/1908.04553v1

    • [math.ST]Sharp Guarantees for Solving Random Equations with One-Bit Information
    Hossein Taheri, Ramtin Pedarsani, Christos Thrampoulidis
    http://arxiv.org/abs/1908.04433v1

    • [math.ST]The bias of isotonic regression
    Ran Dai, Hyebin Song, Rina Foygel Barber, Garvesh Raskutti
    http://arxiv.org/abs/1908.04462v1

    • [q-fin.RM]Forecast Encompassing Tests for the Expected Shortfall
    Timo Dimitriadis, Julie Schnaitmann
    http://arxiv.org/abs/1908.04569v1

    • [quant-ph]Quantum adiabatic machine learning with zooming
    Alexander Zlokapa, Alex Mott, Joshua Job, Jean-Roch Vlimant, Daniel Lidar, Maria Spiropulu
    http://arxiv.org/abs/1908.04480v1

    • [stat.AP]Blinded sample size re-estimation in equivalence testing
    Ekkehard Glimm, Lillian Yau, Heike Woehling
    http://arxiv.org/abs/1908.04695v1

    • [stat.AP]Inverse Parametric Uncertain Identification using Polynomial Chaos and high-order Moment Matching benchmarked on a Wet Friction Clutch
    Wannes De Groote, Tom Lefebvre, Georges Tod, Nele De Geeter, Bruno Depraetere, Suzanne Van Poppel, Guillaume Crevecoeur
    http://arxiv.org/abs/1908.04597v1

    • [stat.CO]Bayesian automated posterior repartitioning for nested sampling
    Xi Chen, Farhan Feroz, Michael Hobson
    http://arxiv.org/abs/1908.04655v1

    • [stat.ME]A Groupwise Approach for Inferring Heterogeneous Treatment Effects in Causal Inference
    Chan Park, Hyunseung Kang
    http://arxiv.org/abs/1908.04427v1

    • [stat.ME]Optimal Estimation of Generalized Average Treatment Effects using Kernel Optimal Matching
    Nathan Kallus, Michele Santacatterina
    http://arxiv.org/abs/1908.04748v1

    • [stat.ML]Comparison theorems on large-margin learning
    Jun Fan, Dao-Hong Xiang
    http://arxiv.org/abs/1908.04470v1

    • [stat.ML]DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data
    Hao Xu, Haibin Chang, Dongxiao Zhang
    http://arxiv.org/abs/1908.04463v1