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
·····································
• [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