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