cs.AI - 人工智能

    cs.CC - 计算复杂度 cs.CL - 计算与语言 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.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 math.PR - 概率 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 physics.geo-ph - 地球物理学 q-bio.NC - 神经元与认知 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Analysing Neural Network Topologies: a Game Theoretic Approach
    • [cs.AI]Explainability in Human-Agent Systems
    • [cs.AI]Usage of Decision Support Systems for Conflicts Modelling during Information Operations Recognition
    • [cs.CC]A Lower Bound for Relaxed Locally Decodable Codes
    • [cs.CL]A Systematic Study of Leveraging Subword Information for Learning Word Representations
    • [cs.CL]Amobee at SemEval-2019 Tasks 5 and 6: Multiple Choice CNN Over Contextual Embedding
    • [cs.CL]Audio-Text Sentiment Analysis using Deep Robust Complementary Fusion of Multi-Features and Multi-Modalities
    • [cs.CL]Automatic Accuracy Prediction for AMR Parsing
    • [cs.CL]Contextual Aware Joint Probability Model Towards Question Answering System
    • [cs.CL]DocBERT: BERT for Document Classification
    • [cs.CL]Effective Estimation of Deep Generative Language Models
    • [cs.CL]End-to-End Speech Translation with Knowledge Distillation
    • [cs.CL]Guiding CTC Posterior Spike Timings for Improved Posterior Fusion and Knowledge Distillation
    • [cs.CL]Mitigating the Impact of Speech Recognition Errors on Spoken Question Answering by Adversarial Domain Adaptation
    • [cs.CL]MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction
    • [cs.CL]Patent Analytics Based on Feature Vector Space Model: A Case of IoT
    • [cs.CL]Posterior-regularized REINFORCE for Instance Selection in Distant Supervision
    • [cs.CL]Reinforcement Learning Based Emotional Editing Constraint Conversation Generation
    • [cs.CL]Semantic Characteristics of Schizophrenic Speech
    • [cs.CV]3D Object Recognition with Ensemble Learning —- A Study of Point Cloud-Based Deep Learning Models
    • [cs.CV]A Comprehensive Study of Alzheimer’s Disease Classification Using Convolutional Neural Networks
    • [cs.CV]A-CNN: Annularly Convolutional Neural Networks on Point Clouds
    • [cs.CV]AT-GAN: A Generative Attack Model for Adversarial Transferring on Generative Adversarial Nets
    • [cs.CV]Aggregation Cross-Entropy for Sequence Recognition
    • [cs.CV]Are State-of-the-art Visual Place Recognition Techniques any Good for Aerial Robotics?
    • [cs.CV]Audio-Visual Model Distillation Using Acoustic Images
    • [cs.CV]BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral Image
    • [cs.CV]Bottleneck potentials in Markov Random Fields
    • [cs.CV]CaseNet: Content-Adaptive Scale Interaction Networks for Scene Parsing
    • [cs.CV]CenterNet: Object Detection with Keypoint Triplets
    • [cs.CV]Clustered Object Detection in Aerial Images
    • [cs.CV]Correlated Logistic Model With Elastic Net Regularization for Multilabel Image Classification
    • [cs.CV]Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization
    • [cs.CV]DENet: A Universal Network for Counting Crowd with Varying Densities and Scales
    • [cs.CV]DNN Architecture for High Performance Prediction on Natural Videos Loses Submodule’s Ability to Learn Discrete-World Dataset
    • [cs.CV]Deep Anomaly Detection for Generalized Face Anti-Spoofing
    • [cs.CV]Deep Fusion Network for Image Completion
    • [cs.CV]Detecting the Unexpected via Image Resynthesis
    • [cs.CV]Devil is in the Edges: Learning Semantic Boundaries from Noisy Annotations
    • [cs.CV]DistanceNet: Estimating Traveled Distance from Monocular Images using a Recurrent Convolutional Neural Network
    • [cs.CV]Downhole Track Detection via Multiscale Conditional Generative Adversarial Nets
    • [cs.CV]End-to-End Learning of Representations for Asynchronous Event-Based Data
    • [cs.CV]Event-based Vision: A Survey
    • [cs.CV]Events-to-Video: Bringing Modern Computer Vision to Event Cameras
    • [cs.CV]Gaze Training by Modulated Dropout Improves Imitation Learning
    • [cs.CV]General Purpose (GenP) Bioimage Ensemble of Handcrafted and Learned Features with Data Augmentation
    • [cs.CV]Guided Anisotropic Diffusion and Iterative Learning for Weakly Supervised Change Detection
    • [cs.CV]Histopathologic Image Processing: A Review
    • [cs.CV]IAN: Combining Generative Adversarial Networks for Imaginative Face Generation
    • [cs.CV]Interpreting Adversarial Examples with Attributes
    • [cs.CV]LO-Net: Deep Real-time Lidar Odometry
    • [cs.CV]Long-Term Video Generation of Multiple Futures Using Human Poses
    • [cs.CV]MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation
    • [cs.CV]Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers
    • [cs.CV]Multi-Scale Geometric Consistency Guided Multi-View Stereo
    • [cs.CV]Process of image super-resolution
    • [cs.CV]Question Guided Modular Routing Networks for Visual Question Answering
    • [cs.CV]REPAIR: Removing Representation Bias by Dataset Resampling
    • [cs.CV]Render4Completion: Synthesizing Multi-view Depth Maps for 3D Shape Completion
    • [cs.CV]TextCaps : Handwritten Character Recognition with Very Small Datasets
    • [cs.CV]USE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets
    • [cs.CV]nnU-Net: Breaking the Spell on Successful Medical Image Segmentation
    • [cs.CY]Comparison of Self-monitoring Feedback Data from Electronic Food and Nutrition Tracking Tools
    • [cs.DC]Low-Latency Graph Streaming Using Compressed Purely-Functional Trees
    • [cs.DC]Truxen: A Trusted Computing Enhanced Blockchain
    • [cs.DS]Improved Distributed Expander Decomposition and Nearly Optimal Triangle Enumeration
    • [cs.HC]Beyond Technical Motives: Perceived User Behavior in Abandoning Wearable Health & Wellness Trackers
    • [cs.HC]Collaboration Analysis Using Deep Learning
    • [cs.IR]Compressed Indexes for Fast Search of Semantic Data
    • [cs.IR]Document Expansion by Query Prediction
    • [cs.IR]How to define co-occurrence in different domains of study?
    • [cs.IR]Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
    • [cs.IR]Query Expansion for Cross-Language Question Re-Ranking
    • [cs.IR]Understanding the Behaviors of BERT in Ranking
    • [cs.IT]Algebraic geometry codes over abelian surfaces containing no absolutely irreducible curves of low genus
    • [cs.IT]Coherent Detection for Short-Packet Physical-Layer Network Coding with FSK Modulation
    • [cs.IT]Compute-and-forward relaying with LDPC codes over QPSK scheme
    • [cs.IT]Downlink Goodput Analysis for D2D Underlaying Massive MIMO Networks
    • [cs.IT]Fundamental Rate Limits of UAV-Enabled Multiple Access Channel with Trajectory Optimization
    • [cs.IT]Information and Memory in Dynamic Resource Allocation
    • [cs.IT]Remarks on the Rényi Entropy of a sum of IID random variables
    • [cs.IT]Simultaneous structures in convex signal recovery - revisiting the convex combination of norms
    • [cs.IT]Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna Reader
    • [cs.IT]UAV Positioning and Power Control for Two-Way Wireless Relaying
    • [cs.LG]3D Shape Synthesis for Conceptual Design and Optimization Using Variational Autoencoders
    • [cs.LG]A Survey on Traffic Signal Control Methods
    • [cs.LG]Adversarial Defense Through Network Profiling Based Path Extraction
    • [cs.LG]An Online Learning Approach for Dengue Fever Classification
    • [cs.LG]Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design
    • [cs.LG]Bayesian policy selection using active inference
    • [cs.LG]Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification
    • [cs.LG]Casting Light on Invisible Cities: Computationally Engaging with Literary Criticism
    • [cs.LG]Compositional Network Embedding
    • [cs.LG]Cross-Lingual Sentiment Quantification
    • [cs.LG]Decoupled Data Based Approach for Learning to Control Nonlinear Dynamical Systems
    • [cs.LG]Detection and Prediction of Cardiac Anomalies Using Wireless Body Sensors and Bayesian Belief Networks
    • [cs.LG]Dynamic Evaluation of Transformer Language Models
    • [cs.LG]Inductive Graph Representation Learning with Recurrent Graph Neural Networks
    • [cs.LG]Machine learning for early prediction of circulatory failure in the intensive care unit
    • [cs.LG]Neural Message Passing for Multi-Label Classification
    • [cs.LG]PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization
    • [cs.LG]People infer recursive visual concepts from just a few examples
    • [cs.LG]Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks
    • [cs.LG]Processing-In-Memory Acceleration of Convolutional Neural Networks for Energy-Efficiency, and Power-Intermittency Resilience
    • [cs.LG]Reducing Adversarial Example Transferability Using Gradient Regularization
    • [cs.LG]Relay: A High-Level IR for Deep Learning
    • [cs.LG]Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning
    • [cs.LG]Self-Attention Graph Pooling
    • [cs.LG]Sparseout: Controlling Sparsity in Deep Networks
    • [cs.LG]SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula
    • [cs.LG]Text Classification Algorithms: A Survey
    • [cs.LG]Vid2Game: Controllable Characters Extracted from Real-World Videos
    • [cs.MM]Adversarial Cross-Modal Retrieval via Learning and Transferring Single-Modal Similarities
    • [cs.NE]Offspring Population Size Matters when Comparing Evolutionary Algorithms with Self-Adjusting Mutation Rates
    • [cs.RO]Benchmarking Tether-based UAV Motion Primitives
    • [cs.RO]Contact Planning for the ANYmal Quadruped Robot using an Acyclic Reachability-Based Planner
    • [cs.RO]Explicit Motion Risk Representation
    • [cs.SD]A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition
    • [cs.SD]Expediting TTS Synthesis with Adversarial Vocoding
    • [cs.SD]Hard Sample Mining for the Improved Retraining of Automatic Speech Recognition
    • [cs.SD]MOSNet: Deep Learning based Objective Assessment for Voice Conversion
    • [cs.SE]Happiness and the productivity of software engineers
    • [cs.SI]Cultivating Online: Question Routing in a Question and Answering Community for Agriculture
    • [cs.SI]Novel Dense Subgraph Discovery Primitives: Risk Aversion and Exclusion Queries
    • [cs.SI]Understanding the Signature of Controversial Wikipedia Articles through Motifs in Editor Revision Networks
    • [cs.SI]Variational principle for scale-free network motifs
    • [eess.AS]Joined Audio-Visual Speech Enhancement and Recognition in the Cocktail Party: The Tug Of War Between Enhancement and Recognition Losses
    • [eess.AS]RawNet: Advanced end-to-end deep neural network using raw waveforms for text-independent speaker verification
    • [math.PR]Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models
    • [math.ST]An efficient stochastic Newton algorithm for parameter estimation in logistic regressions
    • [math.ST]Indirect Inference for Time Series Using the Empirical Characteristic Function and Control Variates
    • [math.ST]Nonparametric drift estimation for diffusions with jumps driven by a Hawkes process
    • [math.ST]The Fisher-Rao geometry of beta distributions applied to the study of canonical moments
    • [physics.ao-ph]CloudSegNet: A Deep Network for Nychthemeron Cloud Image Segmentation
    • [physics.geo-ph]Beyond Correlation: A Path-Invariant Measure for Seismogram Similarity
    • [q-bio.NC]Response of Selective Attention in Middle Temporal Area
    • [stat.CO]Scalable Bayesian Inference for Population Markov Jump Processes
    • [stat.ME]Constructing confidence sets after lasso selection by randomized estimator augmentation
    • [stat.ME]Estimation and uncertainty quantification for extreme quantile regions
    • [stat.ME]Exponential random graph model parameter estimation for very large directed networks
    • [stat.ME]The Sensitivity of Trivariate Granger Causality to Test Criteria and Data Errors
    • [stat.ML]Deep learning investigation for chess player attention prediction using eye-tracking and game data
    • [stat.ML]Forecasting with time series imaging
    • [stat.ML]SACOBRA with Online Whitening for Solving Optimization Problems with High Conditioning
    • [stat.ML]Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures
    • [stat.ML]X-Armed Bandits: Optimizing Quantiles and Other Risks

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    • [cs.AI]Analysing Neural Network Topologies: a Game Theoretic Approach
    Julian Stier, Gabriele Gianini, Michael Granitzer, Konstantin Ziegler
    http://arxiv.org/abs/1904.08166v1

    • [cs.AI]Explainability in Human-Agent Systems
    Avi Rosenfeld, Ariella Richardson
    http://arxiv.org/abs/1904.08123v1

    • [cs.AI]Usage of Decision Support Systems for Conflicts Modelling during Information Operations Recognition
    Oleh Andriichuk, Vitaliy Tsyganok, Dmitry Lande, Oleg Chertov, Yaroslava Porplenko
    http://arxiv.org/abs/1904.08303v1

    • [cs.CC]A Lower Bound for Relaxed Locally Decodable Codes
    Tom Gur, Oded Lachish
    http://arxiv.org/abs/1904.08112v1

    • [cs.CL]A Systematic Study of Leveraging Subword Information for Learning Word Representations
    Yi Zhu, Ivan Vulić, Anna Korhonen
    http://arxiv.org/abs/1904.07994v1

    • [cs.CL]Amobee at SemEval-2019 Tasks 5 and 6: Multiple Choice CNN Over Contextual Embedding
    Alon Rozental, Dadi Biton
    http://arxiv.org/abs/1904.08292v1

    • [cs.CL]Audio-Text Sentiment Analysis using Deep Robust Complementary Fusion of Multi-Features and Multi-Modalities
    Feiyang Chen, Ziqian Luo
    http://arxiv.org/abs/1904.08138v1

    • [cs.CL]Automatic Accuracy Prediction for AMR Parsing
    Juri Opitz, Anette Frank
    http://arxiv.org/abs/1904.08301v1

    • [cs.CL]Contextual Aware Joint Probability Model Towards Question Answering System
    Liu Yang, Lijing Song
    http://arxiv.org/abs/1904.08109v1

    • [cs.CL]DocBERT: BERT for Document Classification
    Ashutosh Adhikari, Achyudh Ram, Raphael Tang, Jimmy Lin
    http://arxiv.org/abs/1904.08398v1

    • [cs.CL]Effective Estimation of Deep Generative Language Models
    Tom Pelsmaeker, Wilker Aziz
    http://arxiv.org/abs/1904.08194v1

    • [cs.CL]End-to-End Speech Translation with Knowledge Distillation
    Yuchen Liu, Hao Xiong, Zhongjun He, Jiajun Zhang, Hua Wu, Haifeng Wang, Chengqing Zong
    http://arxiv.org/abs/1904.08075v1

    • [cs.CL]Guiding CTC Posterior Spike Timings for Improved Posterior Fusion and Knowledge Distillation
    Gakuto Kurata, Kartik Audhkhasi
    http://arxiv.org/abs/1904.08311v1

    • [cs.CL]Mitigating the Impact of Speech Recognition Errors on Spoken Question Answering by Adversarial Domain Adaptation
    Chia-Hsuan Lee, Yun-Nung Chen, Hung-Yi Lee
    http://arxiv.org/abs/1904.07904v1

    • [cs.CL]MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction
    Oscar Araque, Lorenzo Gatti, Kyriaki Kalimeri
    http://arxiv.org/abs/1904.08314v1

    • [cs.CL]Patent Analytics Based on Feature Vector Space Model: A Case of IoT
    Lei Lei, Jiaju Qi, Kan Zheng
    http://arxiv.org/abs/1904.08100v1

    • [cs.CL]Posterior-regularized REINFORCE for Instance Selection in Distant Supervision
    Qi Zhang, Siliang Tang, Xiang Ren, Fei Wu, Shiliang Pu, Yueting Zhuang
    http://arxiv.org/abs/1904.08051v1

    • [cs.CL]Reinforcement Learning Based Emotional Editing Constraint Conversation Generation
    Jia Li, Xiao Sun, Xing Wei, Changliang Li, Jianhua Tao
    http://arxiv.org/abs/1904.08061v1

    • [cs.CL]Semantic Characteristics of Schizophrenic Speech
    Kfir Bar, Vered Zilberstein, Ido Ziv, Heli Baram, Nachum Dershowitz, Samuel Itzikowitz, Eiran Vadim Harel
    http://arxiv.org/abs/1904.07953v1

    • [cs.CV]3D Object Recognition with Ensemble Learning —- A Study of Point Cloud-Based Deep Learning Models
    Daniel Koguciuk, Łukasz Chechliński
    http://arxiv.org/abs/1904.08159v1

    • [cs.CV]A Comprehensive Study of Alzheimer’s Disease Classification Using Convolutional Neural Networks
    Ziqiang Guan, Ritesh Kumar, Yi Ren Fung, Yeahuay Wu, Madalina Fiterau
    http://arxiv.org/abs/1904.07950v1

    • [cs.CV]A-CNN: Annularly Convolutional Neural Networks on Point Clouds
    Artem Komarichev, Zichun Zhong, Jing Hua
    http://arxiv.org/abs/1904.08017v1

    • [cs.CV]AT-GAN: A Generative Attack Model for Adversarial Transferring on Generative Adversarial Nets
    Xiaosen Wang, Kun He, Chuan Guo, Kilian Q. Weinberger, John E. Hopcroft
    http://arxiv.org/abs/1904.07793v2

    • [cs.CV]Aggregation Cross-Entropy for Sequence Recognition
    Zecheng Xie, Yaoxiong Huang, Yuanzhi Zhu, Lianwen Jin, Yuliang Liu, Lele Xie
    http://arxiv.org/abs/1904.08364v1

    • [cs.CV]Are State-of-the-art Visual Place Recognition Techniques any Good for Aerial Robotics?
    Mubariz Zaffar, Ahmad Khaliq, Shoaib Ehsan, Michael Milford, Kostas Alexis, Klaus McDonald-Maier
    http://arxiv.org/abs/1904.07967v1

    • [cs.CV]Audio-Visual Model Distillation Using Acoustic Images
    Andrés F. Pérez, Valentina Sanguineti, Pietro Morerio, Vittorio Murino
    http://arxiv.org/abs/1904.07933v1

    • [cs.CV]BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral Image
    Yaoming Cai, Xiaobo Liu, Zhihua Cai
    http://arxiv.org/abs/1904.08269v1

    • [cs.CV]Bottleneck potentials in Markov Random Fields
    Ahmed Abbas, Paul Swoboda
    http://arxiv.org/abs/1904.08080v1

    • [cs.CV]CaseNet: Content-Adaptive Scale Interaction Networks for Scene Parsing
    Xin Jin, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, Zhibo Chen
    http://arxiv.org/abs/1904.08170v1

    • [cs.CV]CenterNet: Object Detection with Keypoint Triplets
    Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, Qi Tian
    http://arxiv.org/abs/1904.08189v1

    • [cs.CV]Clustered Object Detection in Aerial Images
    Fan Yang, Heng Fan, Peng Chu, Erik Blasch, Haibin Ling
    http://arxiv.org/abs/1904.08008v1

    • [cs.CV]Correlated Logistic Model With Elastic Net Regularization for Multilabel Image Classification
    Qiang Li, Bo Xie, Jane You, Wei Bian, Dacheng Tao
    http://arxiv.org/abs/1904.08098v1

    • [cs.CV]Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization
    Li Yuan, Francis EH Tay, Ping Li, Li Zhou, Jiashi Feng
    http://arxiv.org/abs/1904.08265v1

    • [cs.CV]DENet: A Universal Network for Counting Crowd with Varying Densities and Scales
    Lei Liu, Jie Jiang, Wenjing Jia, Saeed Amirgholipour, Michelle Zeibots, Xiangjian He
    http://arxiv.org/abs/1904.08056v1

    • [cs.CV]DNN Architecture for High Performance Prediction on Natural Videos Loses Submodule’s Ability to Learn Discrete-World Dataset
    Lana Sinapayen, Atsushi Noda
    http://arxiv.org/abs/1904.07969v1

    • [cs.CV]Deep Anomaly Detection for Generalized Face Anti-Spoofing
    Daniel Pérez-Cabo, David Jiménez-Cabello, Artur Costa-Pazo, Roberto J. López-Sastre
    http://arxiv.org/abs/1904.08241v1

    • [cs.CV]Deep Fusion Network for Image Completion
    Xin Hong, Pengfei Xiong, Renhe Ji, Haoqiang Fan
    http://arxiv.org/abs/1904.08060v1

    • [cs.CV]Detecting the Unexpected via Image Resynthesis
    Krzysztof Lis, Krishna Nakka, Pascal Fua, Mathieu Salzmann
    http://arxiv.org/abs/1904.07595v2

    • [cs.CV]Devil is in the Edges: Learning Semantic Boundaries from Noisy Annotations
    David Acuna, Amlan Kar, Sanja Fidler
    http://arxiv.org/abs/1904.07934v1

    • [cs.CV]DistanceNet: Estimating Traveled Distance from Monocular Images using a Recurrent Convolutional Neural Network
    Robin Kreuzig, Matthias Ochs, Rudolf Mester
    http://arxiv.org/abs/1904.08105v1

    • [cs.CV]Downhole Track Detection via Multiscale Conditional Generative Adversarial Nets
    Jia Li, Xing Wei, Guoqiang Yang, Xiao Sun, Changliang Li
    http://arxiv.org/abs/1904.08177v1

    • [cs.CV]End-to-End Learning of Representations for Asynchronous Event-Based Data
    Daniel Gehrig, Antonio Loquercio, Konstantinos G. Derpanis, Davide Scaramuzza
    http://arxiv.org/abs/1904.08245v1

    • [cs.CV]Event-based Vision: A Survey
    Guillermo Gallego, Tobi Delbruck, Garrick Orchard, Chiara Bartolozzi, Brian Taba, Andrea Censi, Stefan Leutenegger, Andrew Davison, Joerg Conradt, Kostas Daniilidis, Davide Scaramuzza
    http://arxiv.org/abs/1904.08405v1

    • [cs.CV]Events-to-Video: Bringing Modern Computer Vision to Event Cameras
    Henri Rebecq, René Ranftl, Vladlen Koltun, Davide Scaramuzza
    http://arxiv.org/abs/1904.08298v1

    • [cs.CV]Gaze Training by Modulated Dropout Improves Imitation Learning
    Yuying Chen, Congcong Liu, Lei Tai, Ming Liu, Bertram E. Shi
    http://arxiv.org/abs/1904.08377v1

    • [cs.CV]General Purpose (GenP) Bioimage Ensemble of Handcrafted and Learned Features with Data Augmentation
    L. Nanni, S. Brahnam, S. Ghidoni, G. Maguolo
    http://arxiv.org/abs/1904.08084v1

    • [cs.CV]Guided Anisotropic Diffusion and Iterative Learning for Weakly Supervised Change Detection
    Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch, Yann Gousseau
    http://arxiv.org/abs/1904.08208v1

    • [cs.CV]Histopathologic Image Processing: A Review
    Jonathan de Matos, Alceu de Souza Britto Jr., Luiz E. S. Oliveira, Alessandro L. Koerich
    http://arxiv.org/abs/1904.07900v1

    • [cs.CV]IAN: Combining Generative Adversarial Networks for Imaginative Face Generation
    Abdullah Hamdi, Bernard Ghanem
    http://arxiv.org/abs/1904.07916v1

    • [cs.CV]Interpreting Adversarial Examples with Attributes
    Sadaf Gulshad, Jan Hendrik Metzen, Arnold Smeulders, Zeynep Akata
    http://arxiv.org/abs/1904.08279v1

    • [cs.CV]LO-Net: Deep Real-time Lidar Odometry
    Qing Li, Shaoyang Chen, Cheng Wang, Xin Li, Chenglu Wen, Ming Cheng, Jonathan Li
    http://arxiv.org/abs/1904.08242v1

    • [cs.CV]Long-Term Video Generation of Multiple Futures Using Human Poses
    Naoya Fushishita, Antonio Tejero-de-Pablos, Yusuke Mukuta, Tatsuya Harada
    http://arxiv.org/abs/1904.07538v2

    • [cs.CV]MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation
    Shuangjie Xu, Daizong Liu, Linchao Bao, Wei Liu, Pan Zhou
    http://arxiv.org/abs/1904.08141v1

    • [cs.CV]Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers
    Jingwen He, Chao Dong, Yu Qiao
    http://arxiv.org/abs/1904.08118v1

    • [cs.CV]Multi-Scale Geometric Consistency Guided Multi-View Stereo
    Qingshan Xu, Wenbing Tao
    http://arxiv.org/abs/1904.08103v1

    • [cs.CV]Process of image super-resolution
    Sebastien Lablanche, Gerard Lablanche
    http://arxiv.org/abs/1904.08396v1

    • [cs.CV]Question Guided Modular Routing Networks for Visual Question Answering
    Yanze Wu, Qiang Sun, Jianqi Ma, Bin Li, Yanwei Fu, Yao Peng, Xiangyang Xue
    http://arxiv.org/abs/1904.08324v1

    • [cs.CV]REPAIR: Removing Representation Bias by Dataset Resampling
    Yi Li, Nuno Vasconcelos
    http://arxiv.org/abs/1904.07911v1

    • [cs.CV]Render4Completion: Synthesizing Multi-view Depth Maps for 3D Shape Completion
    Tao Hu, Zhizhong Han, Abhinav Shrivastava, Matthias Zwicker
    http://arxiv.org/abs/1904.08366v1

    • [cs.CV]TextCaps : Handwritten Character Recognition with Very Small Datasets
    Vinoj Jayasundara, Sandaru Jayasekara, Hirunima Jayasekara, Jathushan Rajasegaran, Suranga Seneviratne, Ranga Rodrigo
    http://arxiv.org/abs/1904.08095v1

    • [cs.CV]USE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets
    Leonardo Rundo, Changhee Han, Yudai Nagano, Jin Zhang, Ryuichiro Hataya, Carmelo Militello, Andrea Tangherloni, Marco S. Nobile, Claudio Ferretti, Daniela Besozzi, Maria Carla Gilardi, Salvatore Vitabile, Giancarlo Mauri, Hideki Nakayama, Paolo Cazzaniga
    http://arxiv.org/abs/1904.08254v1

    • [cs.CV]nnU-Net: Breaking the Spell on Successful Medical Image Segmentation
    Fabian Isensee, Jens Petersen, Simon A. A. Kohl, Paul F. Jäger, Klaus H. Maier-Hein
    http://arxiv.org/abs/1904.08128v1

    • [cs.CY]Comparison of Self-monitoring Feedback Data from Electronic Food and Nutrition Tracking Tools
    Ahmed Fadhil
    http://arxiv.org/abs/1904.08376v1

    • [cs.DC]Low-Latency Graph Streaming Using Compressed Purely-Functional Trees
    Laxman Dhulipala, Julian Shun, Guy Blelloch
    http://arxiv.org/abs/1904.08380v1

    • [cs.DC]Truxen: A Trusted Computing Enhanced Blockchain
    Chao Zhang
    http://arxiv.org/abs/1904.08335v1

    • [cs.DS]Improved Distributed Expander Decomposition and Nearly Optimal Triangle Enumeration
    Yi-Jun Chang, Thatchaphol Saranurak
    http://arxiv.org/abs/1904.08037v1

    • [cs.HC]Beyond Technical Motives: Perceived User Behavior in Abandoning Wearable Health & Wellness Trackers
    Ahmed Fadhil
    http://arxiv.org/abs/1904.07986v1

    • [cs.HC]Collaboration Analysis Using Deep Learning
    Zhang Guo, Kevin Yu, Rebecca Pearlman, Nassir Navab, Roghayeh Barmaki
    http://arxiv.org/abs/1904.08066v1

    • [cs.IR]Compressed Indexes for Fast Search of Semantic Data
    Raffaele Perego, Giulio Ermanno Pibiri, Rossano Venturini
    http://arxiv.org/abs/1904.07619v2

    • [cs.IR]Document Expansion by Query Prediction
    Rodrigo Nogueira, Wei Yang, Jimmy Lin, Kyunghyun Cho
    http://arxiv.org/abs/1904.08375v1

    • [cs.IR]How to define co-occurrence in different domains of study?
    Mathieu Roche
    http://arxiv.org/abs/1904.08010v1

    • [cs.IR]Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
    Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu, Pipei Huang, Huan Zhao, Guoliang Kang, Qiwei Chen, Wei Li, Dik Lun Lee
    http://arxiv.org/abs/1904.08030v1

    • [cs.IR]Query Expansion for Cross-Language Question Re-Ranking
    Muhammad Mahbubur Rahman, Sorami Hisamoto, Kevin Duh
    http://arxiv.org/abs/1904.07982v1

    • [cs.IR]Understanding the Behaviors of BERT in Ranking
    Yifan Qiao, Chenyan Xiong, Zhenghao Liu, Zhiyuan Liu
    http://arxiv.org/abs/1904.07531v2

    • [cs.IT]Algebraic geometry codes over abelian surfaces containing no absolutely irreducible curves of low genus
    Fabien Herbaut, Yves Aubry, Elena Berardini, Marc Perret
    http://arxiv.org/abs/1904.08227v1

    • [cs.IT]Coherent Detection for Short-Packet Physical-Layer Network Coding with FSK Modulation
    Zhaorui Wang, Soung Chang Liew
    http://arxiv.org/abs/1904.08221v1

    • [cs.IT]Compute-and-forward relaying with LDPC codes over QPSK scheme
    Satoshi Takabe, Tadashi Wadayama, Ángeles Vazquez-Castro, Masahito Hayashi
    http://arxiv.org/abs/1904.08306v1

    • [cs.IT]Downlink Goodput Analysis for D2D Underlaying Massive MIMO Networks
    Zezhong Zhang, Zehua Zhou, Rui Wang, Yang Li
    http://arxiv.org/abs/1904.08121v1

    • [cs.IT]Fundamental Rate Limits of UAV-Enabled Multiple Access Channel with Trajectory Optimization
    Peiming Li, Jie Xu
    http://arxiv.org/abs/1904.08305v1

    • [cs.IT]Information and Memory in Dynamic Resource Allocation
    Kuang Xu, Yuan Zhong
    http://arxiv.org/abs/1904.08365v1

    • [cs.IT]Remarks on the Rényi Entropy of a sum of IID random variables
    Benjamin Jaye, Galyna V. Livshyts, Grigoris Paouris, Peter Pivovarov
    http://arxiv.org/abs/1904.08038v1

    • [cs.IT]Simultaneous structures in convex signal recovery - revisiting the convex combination of norms
    Martin Kliesch, Stanislaw J. Szarek, Peter Jung
    http://arxiv.org/abs/1904.07893v1

    • [cs.IT]Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna Reader
    Deepak Mishra, Erik G. Larsson
    http://arxiv.org/abs/1904.07978v1

    • [cs.IT]UAV Positioning and Power Control for Two-Way Wireless Relaying
    Lei Li, Tsung-Hui Chang, Shu Cai
    http://arxiv.org/abs/1904.08280v1

    • [cs.LG]3D Shape Synthesis for Conceptual Design and Optimization Using Variational Autoencoders
    Wentai Zhang, Zhangsihao Yang, Haoliang Jiang, Suyash Nigam, Soji Yamakawa, Tomotake Furuhata, Kenji Shimada, Levent Burak Kara
    http://arxiv.org/abs/1904.07964v1

    • [cs.LG]A Survey on Traffic Signal Control Methods
    Hua Wei, Guanjie Zheng, Vikash Gayah, Zhenhui Li
    http://arxiv.org/abs/1904.08117v1

    • [cs.LG]Adversarial Defense Through Network Profiling Based Path Extraction
    Yuxian Qiu, Jingwen Leng, Cong Guo, Quan Chen, Chao Li, Minyi Guo, Yuhao Zhu
    http://arxiv.org/abs/1904.08089v1

    • [cs.LG]An Online Learning Approach for Dengue Fever Classification
    Siddharth Srivastava, Sumit Soman, Astha Rai
    http://arxiv.org/abs/1904.08092v1

    • [cs.LG]Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design
    Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue
    http://arxiv.org/abs/1904.08102v1

    • [cs.LG]Bayesian policy selection using active inference
    Ozan Çatal, Johannes Nauta, Tim Verbelen, Pieter Simoens, Bart Dhoedt
    http://arxiv.org/abs/1904.08149v1

    • [cs.LG]Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification
    Sujay Khandagale, Han Xiao, Rohit Babbar
    http://arxiv.org/abs/1904.08249v1

    • [cs.LG]Casting Light on Invisible Cities: Computationally Engaging with Literary Criticism
    Shufan Wang, Mohit Iyyer
    http://arxiv.org/abs/1904.08386v1

    • [cs.LG]Compositional Network Embedding
    Tianshu Lyu, Fei Sun, Peng Jiang, Wenwu Ou
    http://arxiv.org/abs/1904.08157v1

    • [cs.LG]Cross-Lingual Sentiment Quantification
    Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani
    http://arxiv.org/abs/1904.07965v1

    • [cs.LG]Decoupled Data Based Approach for Learning to Control Nonlinear Dynamical Systems
    Ran Wang, Karthikeya Parunandi, Dan Yu, Dileep Kalathil, Suman Chakravorty
    http://arxiv.org/abs/1904.08361v1

    • [cs.LG]Detection and Prediction of Cardiac Anomalies Using Wireless Body Sensors and Bayesian Belief Networks
    Asim Darwaish, Farid Naït-Abdesselam, Ashfaq Khokhar
    http://arxiv.org/abs/1904.07976v1

    • [cs.LG]Dynamic Evaluation of Transformer Language Models
    Ben Krause, Emmanuel Kahembwe, Iain Murray, Steve Renals
    http://arxiv.org/abs/1904.08378v1

    • [cs.LG]Inductive Graph Representation Learning with Recurrent Graph Neural Networks
    Binxuan Huang, Kathleen M. Carley
    http://arxiv.org/abs/1904.08035v1

    • [cs.LG]Machine learning for early prediction of circulatory failure in the intensive care unit
    Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean Bodenham, Karsten Borgwardt, Gunnar Rätsch, Tobias M. Merz
    http://arxiv.org/abs/1904.07990v1

    • [cs.LG]Neural Message Passing for Multi-Label Classification
    Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi
    http://arxiv.org/abs/1904.08049v1

    • [cs.LG]PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization
    Gordon E. Moon, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan
    http://arxiv.org/abs/1904.07935v1

    • [cs.LG]People infer recursive visual concepts from just a few examples
    Brenden M. Lake, Steven T. Piantadosi
    http://arxiv.org/abs/1904.08034v1

    • [cs.LG]Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks
    Jaechang Lim, Seongok Ryu, Kyubyong Park, Yo Joong Choe, Jiyeon Ham, Woo Youn Kim
    http://arxiv.org/abs/1904.08144v1

    • [cs.LG]Processing-In-Memory Acceleration of Convolutional Neural Networks for Energy-Efficiency, and Power-Intermittency Resilience
    Arman Roohi, Shaahin Angizi, Deliang Fan, Ronald F DeMara
    http://arxiv.org/abs/1904.07864v1

    • [cs.LG]Reducing Adversarial Example Transferability Using Gradient Regularization
    George Adam, Petr Smirnov, Benjamin Haibe-Kains, Anna Goldenberg
    http://arxiv.org/abs/1904.07980v1

    • [cs.LG]Relay: A High-Level IR for Deep Learning
    Jared Roesch, Steven Lyubomirsky, Marisa Kirisame, Josh Pollock, Logan Weber, Ziheng Jiang, Tianqi Chen, Thierry Moreau, Zachary Tatlock
    http://arxiv.org/abs/1904.08368v1

    • [cs.LG]Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning
    Yuji Kanagawa, Tomoyuki Kaneko
    http://arxiv.org/abs/1904.08129v1

    • [cs.LG]Self-Attention Graph Pooling
    Junhyun Lee, Inyeop Lee, Jaewoo Kang
    http://arxiv.org/abs/1904.08082v1

    • [cs.LG]Sparseout: Controlling Sparsity in Deep Networks
    Najeeb Khan, Ian Stavness
    http://arxiv.org/abs/1904.08050v1

    • [cs.LG]SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula
    Colin Wan, Zheng Li, Yue Zhao
    http://arxiv.org/abs/1904.07998v1

    • [cs.LG]Text Classification Algorithms: A Survey
    Kamran Kowsari, Kiana Jafari Meimandi, Mojtaba Heidarysafa, Sanjana Mendu, Laura E. Barnes, Donald E. Brown
    http://arxiv.org/abs/1904.08067v1

    • [cs.LG]Vid2Game: Controllable Characters Extracted from Real-World Videos
    Oran Gafni, Lior Wolf, Yaniv Taigman
    http://arxiv.org/abs/1904.08379v1

    • [cs.MM]Adversarial Cross-Modal Retrieval via Learning and Transferring Single-Modal Similarities
    Xin Wen, Zhizhong Han, Xinyu Yin, Yu-Shen Liu
    http://arxiv.org/abs/1904.08042v1

    • [cs.NE]Offspring Population Size Matters when Comparing Evolutionary Algorithms with Self-Adjusting Mutation Rates
    Anna Rodionova, Kirill Antonov, Arina Buzdalova, Carola Doerr
    http://arxiv.org/abs/1904.08032v1

    • [cs.RO]Benchmarking Tether-based UAV Motion Primitives
    Xuesu Xiao, Jan Dufek, Robin Murphy
    http://arxiv.org/abs/1904.07996v1

    • [cs.RO]Contact Planning for the ANYmal Quadruped Robot using an Acyclic Reachability-Based Planner
    Mathieu Geisert, Thomas Yates, Asil Orgen, Pierre Fernbach, Ioannis Havoutis
    http://arxiv.org/abs/1904.08238v1

    • [cs.RO]Explicit Motion Risk Representation
    Xuesu Xiao, Jan Dufek, Robin Murphy
    http://arxiv.org/abs/1904.08003v1

    • [cs.SD]A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition
    Jiabin Xue, Jiqing Han, Tieran Zheng, Xiang Gao, Jiaxing Guo
    http://arxiv.org/abs/1904.08039v1

    • [cs.SD]Expediting TTS Synthesis with Adversarial Vocoding
    Paarth Neekhara, Chris Donahue, Miller Puckette, Shlomo Dubnov, Julian McAuley
    http://arxiv.org/abs/1904.07944v1

    • [cs.SD]Hard Sample Mining for the Improved Retraining of Automatic Speech Recognition
    Jiabin Xue, Jiqing Han, Tieran Zheng, Jiaxing Guo, Boyong Wu
    http://arxiv.org/abs/1904.08031v1

    • [cs.SD]MOSNet: Deep Learning based Objective Assessment for Voice Conversion
    Chen-Chou Lo, Szu-Wei Fu, Wen-Chin Huang, Xin Wang, Junichi Yamagishi, Yu Tsao, Hsin-Min Wang
    http://arxiv.org/abs/1904.08352v1

    • [cs.SE]Happiness and the productivity of software engineers
    Daniel Graziotin, Fabian Fagerholm
    http://arxiv.org/abs/1904.08239v1

    • [cs.SI]Cultivating Online: Question Routing in a Question and Answering Community for Agriculture
    Xiaoxue Shen, Liyang Gu, Adele Lu Jia
    http://arxiv.org/abs/1904.08199v1

    • [cs.SI]Novel Dense Subgraph Discovery Primitives: Risk Aversion and Exclusion Queries
    Charalampos E. Tsourakakis, Tianyi Chen, Naonori Kakimura, Jakub Pachocki
    http://arxiv.org/abs/1904.08178v1

    • [cs.SI]Understanding the Signature of Controversial Wikipedia Articles through Motifs in Editor Revision Networks
    James R. Ashford, Liam D. Turner, Roger M. Whitaker, Alun Preece, Diane Felmlee, Don Towsley
    http://arxiv.org/abs/1904.08139v1

    • [cs.SI]Variational principle for scale-free network motifs
    Clara Stegehuis, Remco van der Hofstad, Johan S. H. van Leeuwaarden
    http://arxiv.org/abs/1904.08114v1

    • [eess.AS]Joined Audio-Visual Speech Enhancement and Recognition in the Cocktail Party: The Tug Of War Between Enhancement and Recognition Losses
    Luca Pasa, Giovanni Morrone, Leonardo Badino
    http://arxiv.org/abs/1904.08248v1

    • [eess.AS]RawNet: Advanced end-to-end deep neural network using raw waveforms for text-independent speaker verification
    Jee-weon Jung, Hee-Soo Heo, Ju-ho Kim, Hye-jin Shim, Ha-Jin Yu
    http://arxiv.org/abs/1904.08104v1

    • [math.PR]Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models
    Ramakrishna Tipireddy, David A Barajas-Solano, Alexandre M. Tartakovsky
    http://arxiv.org/abs/1904.08069v1

    • [math.ST]An efficient stochastic Newton algorithm for parameter estimation in logistic regressions
    Bernard Bercu, Antoine Godichon-Baggioni, Bruno Portier
    http://arxiv.org/abs/1904.07908v1

    • [math.ST]Indirect Inference for Time Series Using the Empirical Characteristic Function and Control Variates
    Richard A. Davis, Thiago do Rêgo Sousa, Claudia Klüppelberg
    http://arxiv.org/abs/1904.08276v1

    • [math.ST]Nonparametric drift estimation for diffusions with jumps driven by a Hawkes process
    Charlotte Dion, Sarah Lemler
    http://arxiv.org/abs/1904.08232v1

    • [math.ST]The Fisher-Rao geometry of beta distributions applied to the study of canonical moments
    Alice Le Brigant, Stéphane Puechmorel
    http://arxiv.org/abs/1904.08247v1

    • [physics.ao-ph]CloudSegNet: A Deep Network for Nychthemeron Cloud Image Segmentation
    Soumyabrata Dev, Atul Nautiyal, Yee Hui Lee, Stefan Winkler
    http://arxiv.org/abs/1904.07979v1

    • [physics.geo-ph]Beyond Correlation: A Path-Invariant Measure for Seismogram Similarity
    Joshua Dickey, Brett Borghetti, William Junek, Richard Martin
    http://arxiv.org/abs/1904.07936v1

    • [q-bio.NC]Response of Selective Attention in Middle Temporal Area
    Linda Wang
    http://arxiv.org/abs/1904.07952v1

    • [stat.CO]Scalable Bayesian Inference for Population Markov Jump Processes
    Iker Perez, Theodore Kypraios
    http://arxiv.org/abs/1904.08356v1

    • [stat.ME]Constructing confidence sets after lasso selection by randomized estimator augmentation
    Seunghyun Min, Qing Zhou
    http://arxiv.org/abs/1904.08018v1

    • [stat.ME]Estimation and uncertainty quantification for extreme quantile regions
    Boris Beranger, Simone A. Padoan, Scott A. Sisson
    http://arxiv.org/abs/1904.08251v1

    • [stat.ME]Exponential random graph model parameter estimation for very large directed networks
    Alex Stivala, Garry Robins, Alessandro Lomi
    http://arxiv.org/abs/1904.08063v1

    • [stat.ME]The Sensitivity of Trivariate Granger Causality to Test Criteria and Data Errors
    Leo Carlos-Sandberg, Christopher D. Clack
    http://arxiv.org/abs/1904.07920v1

    • [stat.ML]Deep learning investigation for chess player attention prediction using eye-tracking and game data
    Justin Le Louedec, Thomas Guntz, James Crowley, Dominique Vaufreydaz
    http://arxiv.org/abs/1904.08155v1

    • [stat.ML]Forecasting with time series imaging
    Xixi Li, Yanfei Kang, Feng Li
    http://arxiv.org/abs/1904.08064v1

    • [stat.ML]SACOBRA with Online Whitening for Solving Optimization Problems with High Conditioning
    Samineh Bagheri, Wolfgang Konen, Thomas Bäck
    http://arxiv.org/abs/1904.08397v1

    • [stat.ML]Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures
    Filipe Rodrigues, Carlos Lima Azevedo
    http://arxiv.org/abs/1904.08353v1

    • [stat.ML]X-Armed Bandits: Optimizing Quantiles and Other Risks
    Léonard Torossian, Aurélien Garivier, Victor Picheny
    http://arxiv.org/abs/1904.08205v1