cs.AI - 人工智能

    cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 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.LO - 计算逻辑 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.CO - 组合数学 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.med-ph - 医学物理学 physics.soc-ph - 物理学与社会 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]Clinical acceptance of software based on artificial intelligence technologies (radiology)
    • [cs.AI]Deduction Theorem: The Problematic Nature of Common Practice in Game Theory
    • [cs.AI]Domain-Independent Cost-Optimal Planning in ASP
    • [cs.AI]EcoLens: Visual Analysis of Urban Region Dynamics Using Traffic Data
    • [cs.AI]Neural Simplex Architecture
    • [cs.CL]Dolphin: A Verbal Fluency Evaluation System for Elementary Education
    • [cs.CL]GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension
    • [cs.CL]JUCBNMT at WMT2018 News Translation Task: Character Based Neural Machine Translation of Finnish to English
    • [cs.CL]MSnet: A BERT-based Network for Gendered Pronoun Resolution
    • [cs.CL]MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible
    • [cs.CL]Sentiment Analysis at SEPLN (TASS)-2019: Sentiment Analysis at Tweet level using Deep Learning
    • [cs.CL]Simple and Effective Text Matching with Richer Alignment Features
    • [cs.CR]KiloGrams: Very Large N-Grams for Malware Classification
    • [cs.CR]Optimal Deployments of Defense Mechanisms for the Internet of Things
    • [cs.CV]3D Virtual Garment Modeling from RGB Images
    • [cs.CV]A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
    • [cs.CV]A Unified Point-Based Framework for 3D Segmentation
    • [cs.CV]An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation
    • [cs.CV]Cascaded Context Pyramid for Full-Resolution 3D Semantic Scene Completion
    • [cs.CV]Central Similarity Hashing via Hadamard matrix
    • [cs.CV]Competing Ratio Loss for Discriminative Multi-class Image Classification
    • [cs.CV]Content and Colour Distillation for Learning Image Translations with the Spatial Profile Loss
    • [cs.CV]Convolutional Auto-encoding of Sentence Topics for Image Paragraph Generation
    • [cs.CV]Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation
    • [cs.CV]DIODE: A Dense Indoor and Outdoor DEpth Dataset
    • [cs.CV]DROGON: A Causal Reasoning Framework for Future Trajectory Forecast
    • [cs.CV]Efficient Machine Learning for Large-Scale Urban Land-Use Forecasting in Sub-Saharan Africa
    • [cs.CV]Extract and Merge: Merging extracted humans from different images utilizing Mask R-CNN
    • [cs.CV]Falls Prediction Based on Body Keypoints and Seq2Seq Architecture
    • [cs.CV]Few-Shot Meta-Denoising
    • [cs.CV]Generative Image Inpainting with Submanifold Alignment
    • [cs.CV]Image Captioning with Unseen Objects
    • [cs.CV]Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes
    • [cs.CV]Learning to Adapt Invariance in Memory for Person Re-identification
    • [cs.CV]Moulding Humans: Non-parametric 3D Human Shape Estimation from Single Images
    • [cs.CV]Multi-path Learning for Object Pose Estimation Across Domains
    • [cs.CV]OCT Fingerprints: Resilience to Presentation Attacks
    • [cs.CV]Physical Cue based Depth-Sensing by Color Coding with Deaberration Network
    • [cs.CV]Pseudo-Labeling Curriculum for Unsupervised Domain Adaptation
    • [cs.CV]Pyramid Real Image Denoising Network
    • [cs.CV]Scalable Place Recognition Under Appearance Change for Autonomous Driving
    • [cs.CV]ScarfNet: Multi-scale Features with Deeply Fused and Redistributed Semantics for Enhanced Object Detection
    • [cs.CV]ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences
    • [cs.CV]Simultaneous Iris and Periocular Region Detection Using Coarse Annotations
    • [cs.CV]Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling
    • [cs.CV]Two-Stream Video Classification with Cross-Modality Attention
    • [cs.CV]Visual Place Recognition for Aerial Robotics: Exploring Accuracy-Computation Trade-off for Local Image Descriptors
    • [cs.CY]Auditing News Curation Systems: A Case Study Examining Algorithmic and Editorial Logic in Apple News
    • [cs.CY]GrfKids: Development of a Greek language teaching platform via a Learning Management System for primary school pupils with Russian as a mother tongue
    • [cs.DC]A performance comparison of Dask and Apache Spark for data-intensive neuroimaging pipelines
    • [cs.DC]An Asymptotically Optimal Channel Hopping Sequence with Maximum Rendezvous Diversity
    • [cs.DC]Distributed Streaming Analytics on Large-scale Oceanographic Data using Apache Spark
    • [cs.DC]GLU3.0: Fast GPU-based Parallel Sparse LU Factorization for Circuit Simulation
    • [cs.DC]Popt4jlib: A Parallel/Distributed Optimization Library for Java
    • [cs.DS]Distributed Data Summarization in Well-Connected Networks
    • [cs.DS]New Techniques for Graph Edit Distance Computation
    • [cs.DS]Sublinear Subwindow Search
    • [cs.GR]Software-Enhanced Teaching and Visualization Capabilities of an Ultra-High-Resolution Video Wall
    • [cs.HC]Ablate, Variate, and Contemplate: Visual Analytics for Discovering Neural Architectures
    • [cs.HC]Cultural association based on machine learning for team formation
    • [cs.HC]FairSight: Visual Analytics for Fairness in Decision Making
    • [cs.IR]Answering Complex Questions by Joining Multi-Document Evidence with Quasi Knowledge Graphs
    • [cs.IR]MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation
    • [cs.IR]Personalized, Health-Aware Recipe Recommendation: An Ensemble Topic Modeling Based Approach
    • [cs.IR]Session-Based Hotel Recommendations: Challenges and Future Directions
    • [cs.IR]Sudden Death: A New Way to Compare Recommendation Diversification
    • [cs.IT]General Information Theory: Time and Information
    • [cs.IT]Pilot-Based Channel Estimation Design in Covert Wireless Communication
    • [cs.LG]Accelerating CNN Training by Sparsifying Activation Gradients
    • [cs.LG]Adversarial Robustness Curves
    • [cs.LG]Chainer: A Deep Learning Framework for Accelerating the Research Cycle
    • [cs.LG]Continual Learning via Online Leverage Score Sampling
    • [cs.LG]Deep Gaussian networks for function approximation on data defined manifolds
    • [cs.LG]Featuring the topology with the unsupervised machine learning
    • [cs.LG]Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview
    • [cs.LG]How Good is SGD with Random Shuffling?
    • [cs.LG]Learning Joint Acoustic-Phonetic Word Embeddings
    • [cs.LG]Learning-Aided Physical Layer Attacks Against Multicarrier Communications in IoT
    • [cs.LG]Machine Learning at the Network Edge: A Survey
    • [cs.LG]Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes
    • [cs.LG]Reinforcement Learning for Personalized Dialogue Management
    • [cs.LG]Tree-Transformer: A Transformer-Based Method for Correction of Tree-Structured Data
    • [cs.LO]Solving a Flowshop Scheduling Problem with Answer Set Programming: Exploiting the Problem to Reduce the Number of Combinations
    • [cs.MM]Quality Assessment of In-the-Wild Videos
    • [cs.NE]Estimation of Tire-Road Friction for Autonomous Vehicles: a Neural Network Approach
    • [cs.RO]A Framework for Depth Estimation and Relative Localization of Ground Robots using Computer Vision
    • [cs.RO]Automatic pre-grasps generation for unknown 3D objects
    • [cs.RO]DEDUCE: Diverse scEne Detection methods in Unseen Challenging Environments
    • [cs.RO]Deep Kinematic Models for Physically Realistic Prediction of Vehicle Trajectories
    • [cs.RO]Deep Sensor Fusion for Real-Time Odometry Estimation
    • [cs.RO]Learning When to Drive in Intersections by Combining Reinforcement Learning and Model Predictive Control
    • [cs.SI]Cross-domain Network Representations
    • [cs.SI]Hateful People or Hateful Bots? Detection and Characterization of Bots Spreading Religious Hatred in Arabic Social Media
    • [cs.SI]Maximum likelihood estimation of power-law degree distributions using friendship paradox based sampling
    • [cs.SI]Measuring the Clustering Strength of a Network via the Normalized Clustering Coefficient
    • [cs.SI]Sampling on networks: estimating eigenvector centrality on incomplete graphs
    • [cs.SI]Supervised Learning of the Global Risk Network Activation from Media Event Reports
    • [eess.IV]GANs ‘N Lungs: improving pneumonia prediction
    • [eess.IV]InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations
    • [eess.IV]Multiparametric Deep Learning Tissue Signatures for Muscular Dystrophy: Preliminary Results
    • [eess.IV]Single-Shot High Dynamic Range Imaging with Spatially Varying Exposures Considering Hue Distortion
    • [eess.SP]Achievable Degrees of Freedom for Closed-form Solution to Interference Alignment and Cancellation in Gaussian Interference Multiple Access Channel
    • [eess.SP]Directional Measurements in Urban Street Canyons from Macro Rooftop Sites at 28 GHz for 90% Outdoor Coverage
    • [eess.SP]FCFGS-CV-Based Channel Estimation for Wideband MmWave Massive MIMO Systems with Low-Resolution ADCs
    • [eess.SP]First Experimental Demonstration of Probabilistic Enumerative Sphere Shaping in Optical Fiber Communications
    • [eess.SP]Gradient Pursuit-Based Channel Estimation for MmWave Massive MIMO Systems with One-Bit ADCs
    • [eess.SP]Learning to Denoise and Decode: A Novel Residual Neural Network Decoder for Polar Codes
    • [eess.SP]LoadCNN: A Efficient Green Deep Learning Model for Day-ahead Individual Resident Load Forecasting
    • [eess.SP]Max-Min Fairness Design for MIMO Interference Channels: a Minorization-Maximization Approach
    • [math.CO]Existence of some optimal maximal entanglement entanglement-assisted quantum codes
    • [math.CO]On the existence of paradoxical motions of generically rigid graphs on the sphere
    • [math.NA]On the stable sampling rate for binary measurements and wavelet reconstruction
    • [math.OC]Adaptive Kernel Learning in Heterogeneous Networks
    • [math.OC]Gradient Flow Algorithms for Density Propagation in Stochastic Systems
    • [math.OC]Neural networks-based backward scheme for fully nonlinear PDEs
    • [math.OC]pySOT and POAP: An event-driven asynchronous framework for surrogate optimization
    • [math.ST]Bias Correction and Robust Inference in Semiparametric Models
    • [math.ST]General proof of a limit related to AR(k) model of Statistics
    • [physics.med-ph]Meta-QSM: An Image-Resolution-Arbitrary Network for QSM Reconstruction
    • [physics.soc-ph]Influencer identification in dynamical complex systems
    • [stat.AP]Bivariate temporal orders for causal inference
    • [stat.AP]Groundwater pumping to increase food production causes persistent groundwater drought in India
    • [stat.AP]Mapping the uncertainty of 19th century West African slave origins using a Markov decision process model
    • [stat.AP]Network Dependence and Confounding by Network Structure Lead to Invalid Inference
    • [stat.AP]Projection pursuit based generalized betas accounting for higher order co-moment effects in financial market analysis
    • [stat.CO]Updating Variational Bayes: Fast sequential posterior inference
    • [stat.ME]Finite-sample properties of robust location and scale estimators
    • [stat.ME]Forecasting functional time series using weighted likelihood methodology
    • [stat.ME]Jackknife Empirical Likelihood Approach for K-sample Tests
    • [stat.ME]Optimum Testing Time of Software using Size-Biased Concepts
    • [stat.ME]Testing for Externalities in Network Formation Using Simulation
    • [stat.ML]Conditional independence testing: a predictive perspective
    • [stat.ML]Estimating the Standard Error of Cross-Validation-Based Estimators of Classification Rules Performance
    • [stat.ML]No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization

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    • [cs.AI]Clinical acceptance of software based on artificial intelligence technologies (radiology)
    S. P. Morozov, A. V. Vladzymyrskyy, V. G. Klyashtornyy, A. E. Andreychenko, N. S. Kulberg, V. A. Gombolevsky
    http://arxiv.org/abs/1908.00381v1

    • [cs.AI]Deduction Theorem: The Problematic Nature of Common Practice in Game Theory
    Holger I. Meinhardt
    http://arxiv.org/abs/1908.00409v1

    • [cs.AI]Domain-Independent Cost-Optimal Planning in ASP
    David Spies, Jia-Huai You, Ryan Hayward
    http://arxiv.org/abs/1908.00112v1

    • [cs.AI]EcoLens: Visual Analysis of Urban Region Dynamics Using Traffic Data
    Zhuochen Jin, Nan Cao, Yang Shi, Hanghang Tong, Yingcai Wu
    http://arxiv.org/abs/1908.00181v1

    • [cs.AI]Neural Simplex Architecture
    Dung Phan, Nicola Paoletti, Radu Grosu, Nils Jansen, Scott A. Smolka, Scott D. Stoller
    http://arxiv.org/abs/1908.00528v1

    • [cs.CL]Dolphin: A Verbal Fluency Evaluation System for Elementary Education
    Zitao Liu, Guowei Xu, Tianqiao Liu, Wenbiao Ding, Yujia Song, Chaoyou Guo, Cong Kong, Gale Yan Huang
    http://arxiv.org/abs/1908.00358v1

    • [cs.CL]GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension
    Yu Chen, Lingfei Wu, Mohammed J. Zaki
    http://arxiv.org/abs/1908.00059v1

    • [cs.CL]JUCBNMT at WMT2018 News Translation Task: Character Based Neural Machine Translation of Finnish to English
    Sainik Kumar Mahata, Dipankar Das, Sivaji Bandyopadhyay
    http://arxiv.org/abs/1908.00323v1

    • [cs.CL]MSnet: A BERT-based Network for Gendered Pronoun Resolution
    Zili Wang
    http://arxiv.org/abs/1908.00308v1

    • [cs.CL]MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible
    Marcely Zanon Boito, William N. Havard, Mahault Garnerin, Éric Le Ferrand, Laurent Besacier
    http://arxiv.org/abs/1907.12895v2

    • [cs.CL]Sentiment Analysis at SEPLN (TASS)-2019: Sentiment Analysis at Tweet level using Deep Learning
    Avishek Garain, Sainik Kumar Mahata
    http://arxiv.org/abs/1908.00321v1

    • [cs.CL]Simple and Effective Text Matching with Richer Alignment Features
    Runqi Yang, Jianhai Zhang, Xing Gao, Feng Ji, Haiqing Chen
    http://arxiv.org/abs/1908.00300v1

    • [cs.CR]KiloGrams: Very Large N-Grams for Malware Classification
    Edward Raff, William Fleming, Richard Zak, Hyrum Anderson, Bill Finlayson, Charles Nicholas, Mark McLean
    http://arxiv.org/abs/1908.00200v1

    • [cs.CR]Optimal Deployments of Defense Mechanisms for the Internet of Things
    Mengmeng Ge, Jin-Hee Cho, Charles A. Kamhoua, Dong Seong Kim
    http://arxiv.org/abs/1908.00324v1

    • [cs.CV]3D Virtual Garment Modeling from RGB Images
    Yi Xu, Shanglin Yang, Wei Sun, Li Tan, Kefeng Li, Hui Zhou
    http://arxiv.org/abs/1908.00114v1

    • [cs.CV]A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
    Pengyi Zhang, Yunxin Zhong, Yulin Deng, Xiaoying Tang, Xiaoqiong Li
    http://arxiv.org/abs/1908.00473v1

    • [cs.CV]A Unified Point-Based Framework for 3D Segmentation
    Hungyueh Chiang, Yenliang Lin, Yuehcheng Liu, Winston H. Hsu
    http://arxiv.org/abs/1908.00478v1

    • [cs.CV]An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation
    Vincent Michalski, Vikram Voleti, Samira Ebrahimi Kahou, Anthony Ortiz, Pascal Vincent, Chris Pal, Doina Precup
    http://arxiv.org/abs/1908.00061v1

    • [cs.CV]Cascaded Context Pyramid for Full-Resolution 3D Semantic Scene Completion
    Pingping Zhang, Wei Liu, Yinjie Lei, Huchuan Lu, Xiaoyun Yang
    http://arxiv.org/abs/1908.00382v1

    • [cs.CV]Central Similarity Hashing via Hadamard matrix
    Li Yuan, Tao Wang, Xiaopeng Zhang, Zequn Jie, Francis EH Tay, Jiashi Feng
    http://arxiv.org/abs/1908.00347v1

    • [cs.CV]Competing Ratio Loss for Discriminative Multi-class Image Classification
    Ke Zhang, Xinsheng Wang, Yurong Guo, Zhenbing Zhao, Zhanyu Ma, Tony X. Han
    http://arxiv.org/abs/1907.13349v2

    • [cs.CV]Content and Colour Distillation for Learning Image Translations with the Spatial Profile Loss
    M. Saquib Sarfraz, Constantin Seibold, Haroon Khalid, Rainer Stiefelhagen
    http://arxiv.org/abs/1908.00274v1

    • [cs.CV]Convolutional Auto-encoding of Sentence Topics for Image Paragraph Generation
    Jing Wang, Yingwei Pan, Ting Yao, Jinhui Tang, Tao Mei
    http://arxiv.org/abs/1908.00249v1

    • [cs.CV]Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation
    Yadan Luo, Zi Huang, Zheng Zhang, Jingjing Li, Yang Yang
    http://arxiv.org/abs/1908.00169v1

    • [cs.CV]DIODE: A Dense Indoor and Outdoor DEpth Dataset
    Igor Vasiljevic, Nick Kolkin, Shanyi Zhang, Ruotian Luo, Haochen Wang, Falcon Z. Dai, Andrea F. Daniele, Mohammadreza Mostajabi, Steven Basart, Matthew R. Walter, Gregory Shakhnarovich
    http://arxiv.org/abs/1908.00463v1

    • [cs.CV]DROGON: A Causal Reasoning Framework for Future Trajectory Forecast
    Chiho Choi, Abhishek Patil, Srikanth Malla
    http://arxiv.org/abs/1908.00024v1

    • [cs.CV]Efficient Machine Learning for Large-Scale Urban Land-Use Forecasting in Sub-Saharan Africa
    Daniel Omeiza
    http://arxiv.org/abs/1908.00340v1

    • [cs.CV]Extract and Merge: Merging extracted humans from different images utilizing Mask R-CNN
    Asati Minkesh, Kraisittipong Worranitta, Miyachi Taizo
    http://arxiv.org/abs/1908.00398v1

    • [cs.CV]Falls Prediction Based on Body Keypoints and Seq2Seq Architecture
    Minjie Hua, Yibing Nan, Shiguo Lian
    http://arxiv.org/abs/1908.00275v1

    • [cs.CV]Few-Shot Meta-Denoising
    Leslie Casas, Gustavo Carneiro, Nassir Navab, Vasileios Belagiannis
    http://arxiv.org/abs/1908.00111v1

    • [cs.CV]Generative Image Inpainting with Submanifold Alignment
    Ang Li, Jianzhong Qi, Rui Zhang, Xingjun Ma, Kotagiri Ramamohanarao
    http://arxiv.org/abs/1908.00211v1

    • [cs.CV]Image Captioning with Unseen Objects
    Berkan Demirel, Ramazan Gokberk Cinbis, Nazli Ikizler-Cinbis
    http://arxiv.org/abs/1908.00047v1

    • [cs.CV]Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes
    Nicolas Marchal, Charlotte Moraldo, Roland Siegwart, Hermann Blum, Cesar Cadena, Abel Gawel
    http://arxiv.org/abs/1908.00448v1

    • [cs.CV]Learning to Adapt Invariance in Memory for Person Re-identification
    Zhun Zhong, Liang Zheng, Zhiming Luo, Shaozi Li, Yi Yang
    http://arxiv.org/abs/1908.00485v1

    • [cs.CV]Moulding Humans: Non-parametric 3D Human Shape Estimation from Single Images
    Valentin Gabeur, Jean-Sebastien Franco, Xavier Martin, Cordelia Schmid, Gregory Rogez
    http://arxiv.org/abs/1908.00439v1

    • [cs.CV]Multi-path Learning for Object Pose Estimation Across Domains
    Martin Sundermeyer, Maximilian Durner, En Yen Puang, Zoltan-Csaba Marton, Rudolph Triebel
    http://arxiv.org/abs/1908.00151v1

    • [cs.CV]OCT Fingerprints: Resilience to Presentation Attacks
    Tarang Chugh, Anil K. Jain
    http://arxiv.org/abs/1908.00102v1

    • [cs.CV]Physical Cue based Depth-Sensing by Color Coding with Deaberration Network
    Nao Mishima, Tatsuo Kozakaya, Akihisa Moriya, Ryuzo Okada, Shinsaku Hiura
    http://arxiv.org/abs/1908.00329v1

    • [cs.CV]Pseudo-Labeling Curriculum for Unsupervised Domain Adaptation
    Jaehoon Choi, Minki Jeong, Taekyung Kim, Changick Kim
    http://arxiv.org/abs/1908.00262v1

    • [cs.CV]Pyramid Real Image Denoising Network
    Yiyun Zhao, Zhuqing Jiang, Aidong Men, Guodong Ju
    http://arxiv.org/abs/1908.00273v1

    • [cs.CV]Scalable Place Recognition Under Appearance Change for Autonomous Driving
    Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin, Yu Liu, Thanh-Toan Do, Ian Reid
    http://arxiv.org/abs/1908.00178v1

    • [cs.CV]ScarfNet: Multi-scale Features with Deeply Fused and Redistributed Semantics for Enhanced Object Detection
    Jin Hyeok Yoo, Seong Hyeon Park, Jun Won Choi
    http://arxiv.org/abs/1908.00328v1

    • [cs.CV]ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences
    Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker
    http://arxiv.org/abs/1908.00120v1

    • [cs.CV]Simultaneous Iris and Periocular Region Detection Using Coarse Annotations
    Diego R. Lucio, Rayson Laroca, Luiz A. Zanlorensi, Gladston Moreira, David Menotti
    http://arxiv.org/abs/1908.00069v1

    • [cs.CV]Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling
    Jia Zheng, Junfei Zhang, Jing Li, Rui Tang, Shenghua Gao, Zihan Zhou
    http://arxiv.org/abs/1908.00222v1

    • [cs.CV]Two-Stream Video Classification with Cross-Modality Attention
    Lu Chi, Guiyu Tian, Yadong Mu, Qi Tian
    http://arxiv.org/abs/1908.00497v1

    • [cs.CV]Visual Place Recognition for Aerial Robotics: Exploring Accuracy-Computation Trade-off for Local Image Descriptors
    Bruno Ferrarini, Maria Waheed, Sania Waheed, Shoaib Ehsan, Michael Milford, Klaus D. McDonald-Maier
    http://arxiv.org/abs/1908.00258v1

    • [cs.CY]Auditing News Curation Systems: A Case Study Examining Algorithmic and Editorial Logic in Apple News
    Jack Bandy, Nicholas Diakopoulos
    http://arxiv.org/abs/1908.00456v1

    • [cs.CY]GrfKids: Development of a Greek language teaching platform via a Learning Management System for primary school pupils with Russian as a mother tongue
    Eleni Michailidi, Ioannis Skordas, Maria Papatsimouli, Lazaros Lazaridis, Heracles Michailidis, Stavroula Tavoultzidou, George F. Fragulis
    http://arxiv.org/abs/1908.00337v1

    • [cs.DC]A performance comparison of Dask and Apache Spark for data-intensive neuroimaging pipelines
    Mathieu Dugré, Valérie Hayot-Sasson, Tristan Glatard
    http://arxiv.org/abs/1907.13030v2

    • [cs.DC]An Asymptotically Optimal Channel Hopping Sequence with Maximum Rendezvous Diversity
    Cheng-Shang Chang, Jang-Ping Sheu
    http://arxiv.org/abs/1908.00198v1

    • [cs.DC]Distributed Streaming Analytics on Large-scale Oceanographic Data using Apache Spark
    Janak Dahal, Elias Ioup, Shaikh Arifuzzaman, Mahdi Abdelguerfi
    http://arxiv.org/abs/1907.13264v2

    • [cs.DC]GLU3.0: Fast GPU-based Parallel Sparse LU Factorization for Circuit Simulation
    Shaoyi Peng, Sheldon X. -D. Tan
    http://arxiv.org/abs/1908.00204v1

    • [cs.DC]Popt4jlib: A Parallel/Distributed Optimization Library for Java
    Ioannis T. Christou
    http://arxiv.org/abs/1908.00338v1

    • [cs.DS]Distributed Data Summarization in Well-Connected Networks
    Hsin-Hao Su, Hoa T. Vu
    http://arxiv.org/abs/1908.00236v1

    • [cs.DS]New Techniques for Graph Edit Distance Computation
    David B. Blumenthal
    http://arxiv.org/abs/1908.00265v1

    • [cs.DS]Sublinear Subwindow Search
    Max Reuter, Gheorghe-Teodor Bercea
    http://arxiv.org/abs/1908.00140v1

    • [cs.GR]Software-Enhanced Teaching and Visualization Capabilities of an Ultra-High-Resolution Video Wall
    Ramses van Zon, Marcelo Ponce
    http://arxiv.org/abs/1908.00056v1

    • [cs.HC]Ablate, Variate, and Contemplate: Visual Analytics for Discovering Neural Architectures
    Dylan Cashman, Adam Perer, Remco Chang, Hendrik Strobelt
    http://arxiv.org/abs/1908.00387v1

    • [cs.HC]Cultural association based on machine learning for team formation
    Hrishikesh Kulkarni, Bradly Alicea
    http://arxiv.org/abs/1908.00234v1

    • [cs.HC]FairSight: Visual Analytics for Fairness in Decision Making
    Yongsu Ahn, Yu-Ru Lin
    http://arxiv.org/abs/1908.00176v1

    • [cs.IR]Answering Complex Questions by Joining Multi-Document Evidence with Quasi Knowledge Graphs
    Xiaolu Lu, Soumajit Pramanik, Rishiraj Saha Roy, Abdalghani Abujabal, Yafang Wang, Gerhard Weikum
    http://arxiv.org/abs/1908.00469v1

    • [cs.IR]MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation
    Hoyeop Lee, Jinbae Im, Seongwon Jang, Hyunsouk Cho, Sehee Chung
    http://arxiv.org/abs/1908.00413v1

    • [cs.IR]Personalized, Health-Aware Recipe Recommendation: An Ensemble Topic Modeling Based Approach
    Mansura A. Khan, Ellen Rushe, Barry Smyth, David Coyle
    http://arxiv.org/abs/1908.00148v1

    • [cs.IR]Session-Based Hotel Recommendations: Challenges and Future Directions
    Jens Adamczak, Gerard-Paul Leyson, Peter Knees, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Julia Neidhardt, Wolfgang Wörndl, Philipp Monreal
    http://arxiv.org/abs/1908.00071v1

    • [cs.IR]Sudden Death: A New Way to Compare Recommendation Diversification
    Derek Bridge, Mesut Kaya, Pablo Castells
    http://arxiv.org/abs/1908.00419v1

    • [cs.IT]General Information Theory: Time and Information
    Yilun Liu, Lidong Zhu
    http://arxiv.org/abs/1908.00301v1

    • [cs.IT]Pilot-Based Channel Estimation Design in Covert Wireless Communication
    Tingzhen Xu, Linlin Sun, Shihao Yan, Jinsong Hu, Feng Shu
    http://arxiv.org/abs/1908.00226v1

    • [cs.LG]Accelerating CNN Training by Sparsifying Activation Gradients
    Xucheng Ye, Jianlei Yang, Pengcheng Dai, Yiran Chen, Weisheng Zhao
    http://arxiv.org/abs/1908.00173v1

    • [cs.LG]Adversarial Robustness Curves
    Christina Göpfert, Jan Philip Göpfert, Barbara Hammer
    http://arxiv.org/abs/1908.00096v1

    • [cs.LG]Chainer: A Deep Learning Framework for Accelerating the Research Cycle
    Seiya Tokui, Ryosuke Okuta, Takuya Akiba, Yusuke Niitani, Toru Ogawa, Shunta Saito, Shuji Suzuki, Kota Uenishi, Brian Vogel, Hiroyuki Yamazaki Vincent
    http://arxiv.org/abs/1908.00213v1

    • [cs.LG]Continual Learning via Online Leverage Score Sampling
    Dan Teng, Sakyasingha Dasgupta
    http://arxiv.org/abs/1908.00355v1

    • [cs.LG]Deep Gaussian networks for function approximation on data defined manifolds
    Hrushikesh Mhaskar
    http://arxiv.org/abs/1908.00156v1

    • [cs.LG]Featuring the topology with the unsupervised machine learning
    Kenji Fukushima, Shotaro Shiba Funai, Hideaki Iida
    http://arxiv.org/abs/1908.00281v1

    • [cs.LG]Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview
    Jiawei Zhang
    http://arxiv.org/abs/1908.00187v1

    • [cs.LG]How Good is SGD with Random Shuffling?
    Itay Safran, Ohad Shamir
    http://arxiv.org/abs/1908.00045v1

    • [cs.LG]Learning Joint Acoustic-Phonetic Word Embeddings
    Mohamed El-Geish
    http://arxiv.org/abs/1908.00493v1

    • [cs.LG]Learning-Aided Physical Layer Attacks Against Multicarrier Communications in IoT
    Alireza Nooraiepour, Waheed U. Bajwa, Narayan B. Mandayam
    http://arxiv.org/abs/1908.00195v1

    • [cs.LG]Machine Learning at the Network Edge: A Survey
    M. G. Sarwar Murshed, Christopher Murphy, Daqing Hou, Nazar Khan, Ganesh Ananthanarayanan, Faraz Hussain
    http://arxiv.org/abs/1908.00080v1

    • [cs.LG]Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes
    Alekh Agarwal, Sham M. Kakade, Jason D. Lee, Gaurav Mahajan
    http://arxiv.org/abs/1908.00261v1

    • [cs.LG]Reinforcement Learning for Personalized Dialogue Management
    Floris den Hengst, Mark Hoogendoorn, Frank van Harmelen, Joost Bosman
    http://arxiv.org/abs/1908.00286v1

    • [cs.LG]Tree-Transformer: A Transformer-Based Method for Correction of Tree-Structured Data
    Jacob Harer, Chris Reale, Peter Chin
    http://arxiv.org/abs/1908.00449v1

    • [cs.LO]Solving a Flowshop Scheduling Problem with Answer Set Programming: Exploiting the Problem to Reduce the Number of Combinations
    Carmen Leticia García-Mata, Pedro Rafael Márquez-Gutiérrez
    http://arxiv.org/abs/1908.00183v1

    • [cs.MM]Quality Assessment of In-the-Wild Videos
    Dingquan Li, Tingting Jiang, Ming Jiang
    http://arxiv.org/abs/1908.00375v1

    • [cs.NE]Estimation of Tire-Road Friction for Autonomous Vehicles: a Neural Network Approach
    Alexandre M. Ribeiro, Alexandra B. Moutinho, André R. Fioravanti, Ely C. de Paiva
    http://arxiv.org/abs/1908.00452v1

    • [cs.RO]A Framework for Depth Estimation and Relative Localization of Ground Robots using Computer Vision
    Romulo T. Rodrigues, Pedro Miraldo, Dimos V. Dimarogonas, A. Pedro Aguiar
    http://arxiv.org/abs/1908.00309v1

    • [cs.RO]Automatic pre-grasps generation for unknown 3D objects
    IA Sainul, Sankha Deb, AK Deb
    http://arxiv.org/abs/1908.00221v1

    • [cs.RO]DEDUCE: Diverse scEne Detection methods in Unseen Challenging Environments
    Anwesan Pal, Carlos Nieto-Granda, Henrik I. Christensen
    http://arxiv.org/abs/1908.00191v1

    • [cs.RO]Deep Kinematic Models for Physically Realistic Prediction of Vehicle Trajectories
    Henggang Cui, Thi Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Jeff Schneider, David Bradley, Nemanja Djuric
    http://arxiv.org/abs/1908.00219v1

    • [cs.RO]Deep Sensor Fusion for Real-Time Odometry Estimation
    Michelle Valente, Cyril Joly, Arnaud de La Fortelle
    http://arxiv.org/abs/1908.00524v1

    • [cs.RO]Learning When to Drive in Intersections by Combining Reinforcement Learning and Model Predictive Control
    Tommy Tram, Ivo Batkovic, Mohammad Ali, Jonas Sjöberg
    http://arxiv.org/abs/1908.00177v1

    • [cs.SI]Cross-domain Network Representations
    Shan Xue, Jie Lu, Guangquan Zhang
    http://arxiv.org/abs/1908.00205v1

    • [cs.SI]Hateful People or Hateful Bots? Detection and Characterization of Bots Spreading Religious Hatred in Arabic Social Media
    Nuha Albadi, Maram Kurdi, Shivakant Mishra
    http://arxiv.org/abs/1908.00153v1

    • [cs.SI]Maximum likelihood estimation of power-law degree distributions using friendship paradox based sampling
    Buddhika Nettasinghe, Vikram Krishnamurthy
    http://arxiv.org/abs/1908.00310v1

    • [cs.SI]Measuring the Clustering Strength of a Network via the Normalized Clustering Coefficient
    Ting Li, Xianshi Yu, Bing-Yi Jing
    http://arxiv.org/abs/1908.00523v1

    • [cs.SI]Sampling on networks: estimating eigenvector centrality on incomplete graphs
    Nicolò Ruggeri, Caterina De Bacco
    http://arxiv.org/abs/1908.00388v1

    • [cs.SI]Supervised Learning of the Global Risk Network Activation from Media Event Reports
    Xiang Niu, Gyorgy Korniss, Boleslaw K. Szymanski
    http://arxiv.org/abs/1908.00164v1

    • [eess.IV]GANs ‘N Lungs: improving pneumonia prediction
    Tatiana Malygina, Elena Ericheva, Ivan Drokin
    http://arxiv.org/abs/1908.00433v1

    • [eess.IV]InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations
    Wenbin He, Junpeng Wang, Hanqi Guo, Ko-Chih Wang, Han-Wei Shen, Mukund Raj, Youssef S. G. Nashed, Tom Peterka
    http://arxiv.org/abs/1908.00407v1

    • [eess.IV]Multiparametric Deep Learning Tissue Signatures for Muscular Dystrophy: Preliminary Results
    Alex E. Bocchieri, Vishwa S. Parekh, Kathryn R. Wagner. Shivani Ahlawat, Vladimir Braverman, Doris G. Leung, Michael A. Jacobs
    http://arxiv.org/abs/1908.00175v1

    • [eess.IV]Single-Shot High Dynamic Range Imaging with Spatially Varying Exposures Considering Hue Distortion
    Chihiro Go, Yuma Kinoshita, Sayaka Shiota, Hitoshi Kiya
    http://arxiv.org/abs/1908.00186v1

    • [eess.SP]Achievable Degrees of Freedom for Closed-form Solution to Interference Alignment and Cancellation in Gaussian Interference Multiple Access Channel
    Qu Xin, Chung G. Kang
    http://arxiv.org/abs/1908.00248v1

    • [eess.SP]Directional Measurements in Urban Street Canyons from Macro Rooftop Sites at 28 GHz for 90% Outdoor Coverage
    Jinfeng Du, Dmitry Chizhik, Reinaldo A. Valenzuela, Rodolfo Feick, Guillermo Castro, Mauricio Rodriguez, Tingjun Chen, Manav Kohli, Gil Zussman
    http://arxiv.org/abs/1908.00512v1

    • [eess.SP]FCFGS-CV-Based Channel Estimation for Wideband MmWave Massive MIMO Systems with Low-Resolution ADCs
    In-soo Kim, Junil Choi
    http://arxiv.org/abs/1908.00532v1

    • [eess.SP]First Experimental Demonstration of Probabilistic Enumerative Sphere Shaping in Optical Fiber Communications
    Sebastiaan Goossens, Sjoerd van der Heide, Menno van den Hout, Abdelkerim Amari, Yunus Can Gültekin, Olga Vassilieva, Inwoong Kim, Tadashi Ikeuchi, Frans M. J. Willems, Alex Alvarado, Chigo Okonkwo
    http://arxiv.org/abs/1908.00453v1

    • [eess.SP]Gradient Pursuit-Based Channel Estimation for MmWave Massive MIMO Systems with One-Bit ADCs
    In-soo Kim, Junil Choi
    http://arxiv.org/abs/1908.00508v1

    • [eess.SP]Learning to Denoise and Decode: A Novel Residual Neural Network Decoder for Polar Codes
    Zhiwei Cao, Hongfei Zhu, Yuping Zhao, Dou Li
    http://arxiv.org/abs/1908.00460v1

    • [eess.SP]LoadCNN: A Efficient Green Deep Learning Model for Day-ahead Individual Resident Load Forecasting
    Yunyou Huang, Nana Wang, Tianshu Hao, Wanling Gao, Cheng Huang, Jianqing Li, Jianfeng Zhan
    http://arxiv.org/abs/1908.00298v1

    • [eess.SP]Max-Min Fairness Design for MIMO Interference Channels: a Minorization-Maximization Approach
    Mohammad Mahdi Naghsh, Maryam Masjedi, Arman Adibi, Petre Stoica
    http://arxiv.org/abs/1908.00160v1

    • [math.CO]Existence of some optimal maximal entanglement entanglement-assisted quantum codes
    Masaaki Harada
    http://arxiv.org/abs/1908.00244v1

    • [math.CO]On the existence of paradoxical motions of generically rigid graphs on the sphere
    Matteo Gallet, Georg Grasegger, Jan Legerský, Josef Schicho
    http://arxiv.org/abs/1908.00467v1

    • [math.NA]On the stable sampling rate for binary measurements and wavelet reconstruction
    Anders Christian Hansen, Laura Thesing
    http://arxiv.org/abs/1908.00185v1

    • [math.OC]Adaptive Kernel Learning in Heterogeneous Networks
    Hrusikesha Pradhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat
    http://arxiv.org/abs/1908.00510v1

    • [math.OC]Gradient Flow Algorithms for Density Propagation in Stochastic Systems
    Kenneth F. Caluya, Abhishek Halder
    http://arxiv.org/abs/1908.00533v1

    • [math.OC]Neural networks-based backward scheme for fully nonlinear PDEs
    Huyen Pham, Huyên Pham, Xavier Warin
    http://arxiv.org/abs/1908.00412v1

    • [math.OC]pySOT and POAP: An event-driven asynchronous framework for surrogate optimization
    David Eriksson, David Bindel, Christine A. Shoemaker
    http://arxiv.org/abs/1908.00420v1

    • [math.ST]Bias Correction and Robust Inference in Semiparametric Models
    Jungjun Choi, Xiye Yang
    http://arxiv.org/abs/1908.00414v1

    • [math.ST]General proof of a limit related to AR(k) model of Statistics
    Jan Vrbik
    http://arxiv.org/abs/1908.00428v1

    • [physics.med-ph]Meta-QSM: An Image-Resolution-Arbitrary Network for QSM Reconstruction
    Juan Liu, Kevin M. Koch
    http://arxiv.org/abs/1908.00206v1

    • [physics.soc-ph]Influencer identification in dynamical complex systems
    Sen Pei, Jiannan Wang, Flaviano Morone, Hernán A Makse
    http://arxiv.org/abs/1907.13017v2

    • [stat.AP]Bivariate temporal orders for causal inference
    Marcel Młyńczak
    http://arxiv.org/abs/1908.00123v1

    • [stat.AP]Groundwater pumping to increase food production causes persistent groundwater drought in India
    Akarsh Asoka, Vimal Mishra
    http://arxiv.org/abs/1908.00255v1

    • [stat.AP]Mapping the uncertainty of 19th century West African slave origins using a Markov decision process model
    Zachary Mullen, Ashton Wiens, Eric Vance, Henry Lovejoy
    http://arxiv.org/abs/1908.00431v1

    • [stat.AP]Network Dependence and Confounding by Network Structure Lead to Invalid Inference
    Youjin Lee, Elizabeth L. Ogburn
    http://arxiv.org/abs/1908.00520v1

    • [stat.AP]Projection pursuit based generalized betas accounting for higher order co-moment effects in financial market analysis
    Sven Serneels
    http://arxiv.org/abs/1908.00141v1

    • [stat.CO]Updating Variational Bayes: Fast sequential posterior inference
    Nathaniel Tomasetti, Catherine S. Forbes, Anastasios Panagiotelis
    http://arxiv.org/abs/1908.00225v1

    • [stat.ME]Finite-sample properties of robust location and scale estimators
    Chanseok Park, Haewon Kim, Min Wang
    http://arxiv.org/abs/1908.00462v1

    • [stat.ME]Forecasting functional time series using weighted likelihood methodology
    Ufuk Beyaztas, Han Lin Shang
    http://arxiv.org/abs/1908.00336v1

    • [stat.ME]Jackknife Empirical Likelihood Approach for K-sample Tests
    Yongli Sang, Xin Dang, Yichuan Zhao
    http://arxiv.org/abs/1908.00477v1

    • [stat.ME]Optimum Testing Time of Software using Size-Biased Concepts
    Ashis Kumar Chakraborty, Parna Chatterjee, Poulami Chakraborty, Aleena Chanda
    http://arxiv.org/abs/1908.00307v1

    • [stat.ME]Testing for Externalities in Network Formation Using Simulation
    Bryan S. Graham, Andrin Pelican
    http://arxiv.org/abs/1908.00099v1

    • [stat.ML]Conditional independence testing: a predictive perspective
    Marco Henrique de Almeida Inácio, Rafael Izbicki, Rafael Bassi Stern
    http://arxiv.org/abs/1908.00105v1

    • [stat.ML]Estimating the Standard Error of Cross-Validation-Based Estimators of Classification Rules Performance
    Waleed A. Yousef
    http://arxiv.org/abs/1908.00325v1

    • [stat.ML]No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization
    Thiago de P. Vasconcelos, Daniel A. R. M. A. de Souza, César L. C. Mattos, João P. P. Gomes
    http://arxiv.org/abs/1908.00361v1