今日学术视野(2020.5.30)

astro-ph.CO - 宇宙学和天体物理学

astro-ph.EP - 地球与行星天体 cs.AI - 人工智能 cs.CG - 计算几何学 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.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.ET - 新兴技术 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.DS - 动力系统 math.NT - 数论 math.OC - 优化与控制 math.ST - 统计理论 physics.chem-ph -化学物理 physics.comp-ph - 计算物理学 physics.data-an - 数据分析、 统计和概率 physics.soc-ph - 物理学与社会 q-bio.MN - 分子网络 q-fin.PM - 投资组合管理 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习 • [astro-ph.CO]Mass Estimation of Galaxy Clusters with Deep Learning II: CMB Cluster Lensing • [astro-ph.EP]A Hermite-Gaussian Based Radial Velocity Estimation Method • [cs.AI]AI Forensics: Did the Artificial Intelligence System Do It? Why? • [cs.AI]An Exploratory Study of Hierarchical Fuzzy Systems Approach in Recommendation System • [cs.AI]Good Counterfactuals and Where to Find Them: A Case-Based Technique for Generating Counterfactuals for Explainable AI (XAI) • [cs.AI]Learning LWF Chain Graphs: an Order Independent Algorithm • [cs.AI]The Adversarial Resilience Learning Architecture for AI-based Modelling, Exploration, and Operation of Complex Cyber-Physical Systems • [cs.AI]Unlucky Explorer: A Complete non-Overlapping Map Exploration • [cs.CG]A Practical Index Structure Supporting Fréchet Proximity Queries Among Trajectories • [cs.CL]A Corpus for Large-Scale Phonetic Typology • [cs.CL]A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews • [cs.CL]Adversarial Attacks and Defense on Textual Data: A Review • [cs.CL]Cats climb entails mammals move: preserving hyponymy in compositional distributional semantics • [cs.CL]ConCET: Entity-Aware Topic Classification for Open-Domain Conversational Agents • [cs.CL]Contextual Dialogue Act Classification for Open-Domain Conversational Agents • [cs.CL]Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs • [cs.CL]HAT: Hardware-Aware Transformers for Efficient Natural Language Processing • [cs.CL]In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonology • [cs.CL]Joint Modelling of Emotion and Abusive Language Detection • [cs.CL]Language (Technology) is Power: A Critical Survey of “Bias” in NLP • [cs.CL]Language Models are Few-Shot Learners • [cs.CL]Language Representation Models for Fine-Grained Sentiment Classification • [cs.CL]Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction • [cs.CL]Phone Features Improve Speech Translation • [cs.CL]Subword RNNLM Approximations for Out-Of-Vocabulary Keyword Search • [cs.CL]The SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion • [cs.CL]Transition-based Semantic Dependency Parsing with Pointer Networks • [cs.CL]Variational Neural Machine Translation with Normalizing Flows • [cs.CL]Would you Like to Talk about Sports Now? Towards Contextual Topic Suggestion for Open-Domain Conversational Agents • [cs.CR]Assessing Centrality Without Knowing Connections • [cs.CR]Blockchain is Watching You: Profiling and Deanonymizing Ethereum Users • [cs.CR]Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques • [cs.CV]3D human pose estimation with adaptive receptive fields and dilated temporal convolutions • [cs.CV]AFAT: Adaptive Failure-Aware Tracker for Robust Visual Object Tracking • [cs.CV]Anomaly Detection Based on Deep Learning Using Video for Prevention of Industrial Accidents • [cs.CV]AutoSweep: Recovering 3D Editable Objectsfrom a Single Photograph • [cs.CV]Boosting Few-Shot Learning With Adaptive Margin Loss • [cs.CV]CGGAN: A Context Guided Generative Adversarial Network For Single Image Dehazing • [cs.CV]CNN-based Approach for Cervical Cancer Classification in Whole-Slide Histopathology Images • [cs.CV]D2D: Keypoint Extraction with Describe to Detect Approach • [cs.CV]Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification • [cs.CV]Disentanglement Then Reconstruction: Learning Compact Features for Unsupervised Domain Adaptation • [cs.CV]End-to-End Object Detection with Transformers • [cs.CV]Explainable deep learning models in medical image analysis • [cs.CV]False Positive Removal for 3D Vehicle Detection with Penetrated Point Classifier • [cs.CV]Few-Shot Open-Set Recognition using Meta-Learning • [cs.CV]Improving Generalized Zero-Shot Learning by Semantic Discriminator • [cs.CV]L^2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion • [cs.CV]Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection • [cs.CV]Network Fusion for Content Creation with Conditional INNs • [cs.CV]P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds • [cs.CV]Quantifying the Complexity of Standard Benchmarking Datasets for Long-Term Human Trajectory Prediction • [cs.CV]Robust Modeling of Epistemic Mental States • [cs.CV]Self-supervised Modal and View Invariant Feature Learning • [cs.CV]Stereo Vision Based Single-Shot 6D Object Pose Estimation for Bin-Picking by a Robot Manipulator • [cs.CV]TOAN: Target-Oriented Alignment Network for Fine-Grained Image Categorization with Few Labeled Samples • [cs.CV]Traditional Method Inspired Deep Neural Network for Edge Detection • [cs.CV]Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild • [cs.CV]Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets • [cs.CV]Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Move’s discrepancies • [cs.CY]An Ambient-Physical System to Infer Concentration in Open-plan Workplace • [cs.CY]HazeDose: Design and Analysis of a Personal Air Pollution Inhaled Dose Estimation System using Wearable Sensors • [cs.CY]IMDb data from two generations (1979 to 2019). Part one: Dataset • [cs.CY]Modular Politics: Toward a Governance Layer for Online Communities • [cs.CY]Operationalizing the Legal Principle of Data Minimization for Personalization • [cs.CY]Scaling Participation — What Does the Concept of Managed Communities Offer for Participatory Design? • [cs.DC]A Distributed Multi-GPU System for Large-Scale Node Embedding at Tencent • [cs.DC]A Theory of Auto-Scaling for Resource Reservation in Cloud Services • [cs.DC]Brief Announcement: On the Limits of Parallelizing Convolutional Neural Networks on GPUs • [cs.DC]GraFS: Graph Analytics Fusion and Synthesis • [cs.DC]HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism • [cs.DC]Network Partitioning and Avoidable Contention • [cs.DC]Parallel Load Balancing on Constrained Client-Server Topologies • [cs.DC]Parallelizing Machine Learning as a Service for the End-User • [cs.DC]ProTuner: Tuning Programs with Monte Carlo Tree Search • [cs.DC]The Manufacturing Data and Machine Learning Platform: Enabling Real-time Monitoring and Control of Scientific Experiments via IoT • [cs.DL]The POLUSA Dataset: 0.9M Political News Articles Balanced by Time and Outlet Popularity • [cs.DS]Distributed algorithms for covering, packing and maximum weighted matching • [cs.ET]Pattern Denoising in Molecular Associative Memory using Pairwise Markov Random Field Models • [cs.GT]Chaos, Extremism and Optimism: Volume Analysis of Learning in Games • [cs.HC]Heatmap-Based Method for Estimating Drivers’ Cognitive Distraction • [cs.IR]A Re-visit of the Popularity Baseline in Recommender Systems • [cs.IR]JointMap: Joint Query Intent Understanding For Modeling Intent Hierarchies in E-commerce Search • [cs.IR]Studying Ranking-Incentivized Web Dynamics • [cs.IR]User Behavior Retrieval for Click-Through Rate Prediction • [cs.IR]User Intent Inference for Web Search and Conversational Agents • [cs.IT]Approximate Message Passing with Unitary Transformation for Robust Bilinear Recovery • [cs.IT]Fundamental Limits of Stochastic Caching Networks • [cs.IT]List Decoding of Arikan’s PAC Codes • [cs.IT]Multi-access Coded Caching Schemes From Cross Resolvable Designs • [cs.IT]On Functions of Markov Random Fields • [cs.IT]On two-weight codes • [cs.IT]Optimal Anticodes, Diameter Perfect Codes, Chains and Weights • [cs.IT]Performance Limits of Fluid Antenna Systems • [cs.LG]A Feature-map Discriminant Perspective for Pruning Deep Neural Networks • [cs.LG]Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity • [cs.LG]COVID-19 and Your Smartphone: BLE-based Smart Contact Tracing • [cs.LG]CPAC-Conv: CP-decomposition to Approximately Compress Convolutional Layers in Deep Learning • [cs.LG]Demystifying Orthogonal Monte Carlo and Beyond • [cs.LG]Domain Knowledge Integration By Gradient Matching For Sample-Efficient Reinforcement Learning • [cs.LG]Explaining Neural Networks by Decoding Layer Activations • [cs.LG]Exploiting Non-Linear Redundancy for Neural Model Compression • [cs.LG]Generalised Interpretable Shapelets for Irregular Time Series • [cs.LG]Looking back to lower-level information in few-shot learning • [cs.LG]Parameter Sharing is Surprisingly Useful for Multi-Agent Deep Reinforcement Learning • [cs.LG]Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size • [cs.LG]QEBA: Query-Efficient Boundary-Based Blackbox Attack • [cs.LG]Tensor Decomposition for Multi-agent Predictive State Representation • [cs.LG]Towards the Infeasibility of Membership Inference on Deep Models • [cs.LG]VMI-VAE: Variational Mutual Information Maximization Framework for VAE With Discrete and Continuous Priors • [cs.LG]Variational Autoencoder with Embedded Student-$t$ Mixture Model for Authorship Attribution • [cs.NE]Antenna Optimization Using a New Evolutionary Algorithm Based on Tukey-Lambda Probability Distribution • [cs.NE]Dynamic Bi-Objective Routing of Multiple Vehicles • [cs.NE]From Prediction to Prescription: AI-Based Optimization of Non-Pharmaceutical Interventions for the COVID-19 Pandemic • [cs.NE]Genetic optimization algorithms applied toward mission computability models • [cs.NE]Learning Various Length Dependence by Dual Recurrent Neural Networks • [cs.NE]More Effective Randomized Search Heuristics for Graph Coloring Through Dynamic Optimization • [cs.NE]Physics-based polynomial neural networks for one-shot learning of dynamical systems from one or a few samples • [cs.NE]Towards Decision Support in Dynamic Bi-Objective Vehicle Routing • [cs.NI]Modeling the Location Selection of Mirror Servers in Content Delivery Networks • [cs.NI]Simulation and Optimization of Content Delivery Networks considering User Profiles and Preferences of Internet Service Providers • [cs.RO]Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environments • [cs.RO]Graph-based Proprioceptive Localization Using a Discrete Heading-Length Feature Sequence Matching Approach • [cs.RO]Graph-based Proprioceptive Localization Using a Discrete Heading-Length Feature Sequence Matching Approach • [cs.RO]Interaction-Aware Trajectory Prediction of Connected Vehicles using CNN-LSTM Networks • [cs.RO]IoT-based Remote Control Study of a Robotic Trans-esophageal Ultrasound Probe via LAN and 5G • [cs.RO]LyRN (Lyapunov Reaching Network): A Real-Time Closed Loop approach from Monocular Vision • [cs.RO]Perception-aware time optimal path parameterization for quadrotors • [cs.SE]Active Fuzzing for Testing and Securing Cyber-Physical Systems • [cs.SE]MACER: A Modular Framework for Accelerated Compilation Error Repair • [cs.SE]Using Source Code Density to Improve the Accuracy of Automatic Commit Classification into Maintenance Activities • [cs.SI]Challenges in Combating COVID-19 Infodemic — Data, Tools, and Ethics • [cs.SI]Complex networks for event detection in heterogeneous high volume news streams • [cs.SI]Deceptive Deletions for Protecting Withdrawn Posts on Social Platforms • [cs.SI]Higher Order Temporal Analysis of Global Terrorism Data • [cs.SI]Pandemic News: Facebook Pages of Mainstream News Media and the Coronavirus Crisis — A Computational Content Analysis • [econ.EM]Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S • [econ.EM]Machine learning time series regressions with an application to nowcasting • [eess.AS]Bayesian Restoration of Audio Degraded by Low-Frequency Pulses Modeled via Gaussian Process • [eess.AS]Modality Dropout for Improved Performance-driven Talking Faces • [eess.AS]Speech-to-Singing Conversion based on Boundary Equilibrium GAN • [eess.AS]Unsupervised Audio Source Separation using Generative Priors • [eess.AS]When Can Self-Attention Be Replaced by Feed Forward Layers? • [eess.IV]A Normalized Fully Convolutional Approach to Head and Neck Cancer Outcome Prediction • [eess.IV]An ENAS Based Approach for Constructing Deep Learning Models for Breast Cancer Recognition from Ultrasound Images • [eess.IV]Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems • [eess.IV]Deep Learning for Automatic Pneumonia Detection • [eess.IV]Early Screening of SARS-CoV-2 by Intelligent Analysis of X-Ray Images • [eess.IV]How to do Physics-based Learning • [eess.IV]Image Restoration from Parametric Transformations using Generative Models • [eess.IV]Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification • [eess.IV]Multiple resolution residual network for automatic thoracic organs-at-risk segmentation from CT • [eess.IV]Prediction of Thrombectomy Functional Outcomes using Multimodal Data • [eess.IV]Segmentation of the Myocardium on Late-Gadolinium Enhanced MRI based on 2.5 D Residual Squeeze and Excitation Deep Learning Model • [eess.IV]Towards computer-aided severity assessment: training and validation of deep neural networks for geographic extent and opacity extent scoring of chest X-rays for SARS-CoV-2 lung disease severity • [eess.SP]A Maneuver-based Urban Driving Dataset and Model for Cooperative Vehicle Applications • [eess.SP]A Vision to Smart Radio Environment: Surface Wave Communication Superhighways • [eess.SP]Codebook-Based Beam Tracking for Conformal ArrayEnabled UAV MmWave Networks • [eess.SY]A Novel Ramp Metering Approach Based on Machine Learning and Historical Data • [math.DS]Kernel-based approximation of the Koopman generator and Schrödinger operator • [math.NT]Simultaneous Diagonalization of Incomplete Matrices and Applications • [math.OC]Derivation of Symmetric PCA Learning Rules from a Novel Objective Function • [math.ST]Comments on the presence of serial correlation in the random coefficients of an autoregressive process • [math.ST]Group testing with nested pools • [math.ST]Hawkes process and Edgeworth expansion with application to maximum likelihood estimator • [physics.chem-ph]Machine learning and excited-state molecular dynamics • [physics.comp-ph]ODEN: A Framework to Solve Ordinary Differential Equations using Artificial Neural Networks • [physics.comp-ph]Physically interpretable machine learning algorithm on multidimensional non-linear fields • [physics.data-an]Responses and Degrees of Freedom of PVAR for a Continuous Power-Law PSD • [physics.soc-ph]Revealing consensus and dissensus between network partitions • [q-bio.MN]Inferring Signaling Pathways with Probabilistic Programming • [q-fin.PM]Deep Learning for Portfolio Optimisation • [q-fin.ST]Daily Middle-Term Probabilistic Forecasting of Power Consumption in North-East England • [q-fin.ST]Using Machine Learning to Forecast Future Earnings • [stat.AP]Clinical trials impacted by the COVID-19 pandemic: Adaptive designs to the rescue? • [stat.AP]Forecasting the local progression of the Covid-19 epidemic from medical emergency calls: the example of the Paris area • [stat.AP]Optimal multi-wave sampling for regression modelling in two-phase designs • [stat.CO]copent: Estimating Copula Entropy in R • [stat.ME]Analysis of time-to-event for observational studies: Guidance to the use of intensity models • [stat.ME]Assessing variable activity for Bayesian regression trees • [stat.ME]Boundary-free Estimators of the Mean Residual Life Function by Transformation • [stat.ME]Boundary-free Kernel-smoothed Goodness-of-fit Tests for Data on General Interval • [stat.ME]Composition Estimation via Shrinkage • [stat.ME]Synthetic control method with convex hull restrictions: A Bayesian maximum a posteriori approach • [stat.ML]Breiman’s “Two Cultures” Revisited and Reconciled • [stat.ML]Calibrated Surrogate Losses for Adversarially Robust Classification • [stat.ML]Hyperbolic Manifold Regression • [stat.ML]Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models • [stat.ML]Review of Mathematical frameworks for Fairness in Machine Learning • [stat.ML]Robust estimation via generalized quasi-gradients • [stat.ML]Travel Time Prediction using Tree-Based Ensembles ····································· • [astro-ph.CO]Mass Estimation of Galaxy Clusters with Deep Learning II: CMB Cluster Lensing N. Gupta, C. L. Reichardt http://arxiv.org/abs/2005.13985v1 • [astro-ph.EP]A Hermite-Gaussian Based Radial Velocity Estimation Method Parker Holzer, Jessi Cisewski-Kehe, Debra Fischer, Lily Zhao http://arxiv.org/abs/2005.14083v1 • [cs.AI]AI Forensics: Did the Artificial Intelligence System Do It? Why? Johannes Schneider, Frank Breitinger http://arxiv.org/abs/2005.13635v1 • [cs.AI]An Exploratory Study of Hierarchical Fuzzy Systems Approach in Recommendation System Tajul Rosli Razak, Iman Hazwam Abd Halim, Muhammad Nabil Fikri Jamaludin, Mohammad Hafiz Ismail, Shukor Sanim Mohd Fauzi http://arxiv.org/abs/2005.14026v1 • [cs.AI]Good Counterfactuals and Where to Find Them: A Case-Based Technique for Generating Counterfactuals for Explainable AI (XAI) Mark T. Keane, Barry Smyth http://arxiv.org/abs/2005.13997v1 • [cs.AI]Learning LWF Chain Graphs: an Order Independent Algorithm Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi http://arxiv.org/abs/2005.14037v1 • [cs.AI]The Adversarial Resilience Learning Architecture for AI-based Modelling, Exploration, and Operation of Complex Cyber-Physical Systems Eric MSP Veith, Nils Wenninghoff, Emilie Frost http://arxiv.org/abs/2005.13601v1 • [cs.AI]Unlucky Explorer: A Complete non-Overlapping Map Exploration Mohammad Sina Kiarostami, Saleh Khalaj Monfared, Mohammadreza Daneshvaramoli, Ali Oliayi, Negar Yousefian, Dara Rahmati, Saeid Gorgin http://arxiv.org/abs/2005.14156v1 • [cs.CG]A Practical Index Structure Supporting Fréchet Proximity Queries Among Trajectories Joachim Gudmundsson, Michael Horton, John Pfeifer, Martin P. Seybold http://arxiv.org/abs/2005.13773v1 • [cs.CL]A Corpus for Large-Scale Phonetic Typology Elizabeth Salesky, Eleanor Chodroff, Tiago Pimentel, Matthew Wiesner, Ryan Cotterell, Alan W Black, Jason Eisner http://arxiv.org/abs/2005.13962v1 • [cs.CL]A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews Edison Marrese-Taylor, Cristian Rodriguez-Opazo, Jorge A. Balazs, Stephen Gould, Yutaka Matsuo http://arxiv.org/abs/2005.13362v2 • [cs.CL]Adversarial Attacks and Defense on Textual Data: A Review Aminul Huq, Mst. Tasnim Pervin http://arxiv.org/abs/2005.14108v1 • [cs.CL]Cats climb entails mammals move: preserving hyponymy in compositional distributional semantics Gemma De las Cuevas, Andreas Klinger, Martha Lewis, Tim Netzer http://arxiv.org/abs/2005.14134v1 • [cs.CL]ConCET: Entity-Aware Topic Classification for Open-Domain Conversational Agents Ali Ahmadvand, Harshita Sahijwani, Jason Ingyu Choi, Eugene Agichtein http://arxiv.org/abs/2005.13798v1 • [cs.CL]Contextual Dialogue Act Classification for Open-Domain Conversational Agents Ali Ahmadvand, Jason Ingyu Choi, Eugene Agichtein http://arxiv.org/abs/2005.13804v1 • [cs.CL]Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs Dong Bok Lee, Seanie Lee, Woo Tae Jeong, Donghwan Kim, Sung Ju Hwang http://arxiv.org/abs/2005.13837v1 • [cs.CL]HAT: Hardware-Aware Transformers for Efficient Natural Language Processing Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han http://arxiv.org/abs/2005.14187v1 • [cs.CL]In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonology Chundra A. Cathcart, Florian Wandl http://arxiv.org/abs/2005.13575v1 • [cs.CL]Joint Modelling of Emotion and Abusive Language Detection Santhosh Rajamanickam, Pushkar Mishra, Helen Yannakoudakis, Ekaterina Shutova http://arxiv.org/abs/2005.14028v1 • [cs.CL]Language (Technology) is Power: A Critical Survey of “Bias” in NLP Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna Wallach http://arxiv.org/abs/2005.14050v1 • [cs.CL]Language Models are Few-Shot Learners Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei http://arxiv.org/abs/2005.14165v1 • [cs.CL]Language Representation Models for Fine-Grained Sentiment Classification Brian Cheang, Bailey Wei, David Kogan, Howey Qiu, Masud Ahmed http://arxiv.org/abs/2005.13619v1 • [cs.CL]Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction Laila Rasmy, Yang Xiang, Ziqian Xie, Cui Tao, Degui Zhi http://arxiv.org/abs/2005.12833v1 • [cs.CL]Phone Features Improve Speech Translation Elizabeth Salesky, Alan W Black http://arxiv.org/abs/2005.13681v1 • [cs.CL]Subword RNNLM Approximations for Out-Of-Vocabulary Keyword Search Mittul Singh, Sami Virpioja, Peter Smit, Mikko Kurimo http://arxiv.org/abs/2005.13827v1 • [cs.CL]The SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion Katharina Kann, Arya McCarthy, Garrett Nicolai, Mans Hulden http://arxiv.org/abs/2005.13756v1 • [cs.CL]Transition-based Semantic Dependency Parsing with Pointer Networks Daniel Fernández-González, Carlos Gómez-Rodríguez http://arxiv.org/abs/2005.13344v2 • [cs.CL]Variational Neural Machine Translation with Normalizing Flows Hendra Setiawan, Matthias Sperber, Udhay Nallasamy, Matthias Paulik http://arxiv.org/abs/2005.13978v1 • [cs.CL]Would you Like to Talk about Sports Now? Towards Contextual Topic Suggestion for Open-Domain Conversational Agents Ali Ahmadvand, Harshita Sahijwani, Eugene Agichtein http://arxiv.org/abs/2005.13803v1 • [cs.CR]Assessing Centrality Without Knowing Connections Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague http://arxiv.org/abs/2005.13787v1 • [cs.CR]Blockchain is Watching You: Profiling and Deanonymizing Ethereum Users Ferenc Béres, István András Seres, András A. Benczúr, Mikerah Quintyne-Collins http://arxiv.org/abs/2005.14051v1 • [cs.CR]Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques Han Qiu, Yi Zeng, Qinkai Zheng, Tianwei Zhang, Meikang Qiu, Gerard Memmi http://arxiv.org/abs/2005.13712v1 • [cs.CV]3D human pose estimation with adaptive receptive fields and dilated temporal convolutions Michael Shin, Eduardo Castillo, Irene Font Peradejordi, Shobhna Jayaraman http://arxiv.org/abs/2005.13797v1 • [cs.CV]AFAT: Adaptive Failure-Aware Tracker for Robust Visual Object Tracking Tianyang Xu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler http://arxiv.org/abs/2005.13708v1 • [cs.CV]Anomaly Detection Based on Deep Learning Using Video for Prevention of Industrial Accidents Satoshi Hashimoto, Yonghoon Ji, Kenichi Kudo, Takayuki Takahashi, Kazunori Umeda http://arxiv.org/abs/2005.13734v1 • [cs.CV]AutoSweep: Recovering 3D Editable Objectsfrom a Single Photograph Xin Chen, Yuwei Li, Xi Luo, Tianjia Shao, Jingyi Yu, Kun Zhou, Youyi Zheng http://arxiv.org/abs/2005.13312v2 • [cs.CV]Boosting Few-Shot Learning With Adaptive Margin Loss Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Liwei Wang http://arxiv.org/abs/2005.13826v1 • [cs.CV]CGGAN: A Context Guided Generative Adversarial Network For Single Image Dehazing Zhaorun Zhou, Zhenghao Shi, Mingtao Guo, Yaning Feng, Minghua Zhao http://arxiv.org/abs/2005.13884v1 • [cs.CV]CNN-based Approach for Cervical Cancer Classification in Whole-Slide Histopathology Images Ferdaous Idlahcen, Mohammed Majid Himmi, Abdelhak Mahmoudi http://arxiv.org/abs/2005.13924v1 • [cs.CV]D2D: Keypoint Extraction with Describe to Detect Approach Yurun Tian, Vassileios Balntas, Tony Ng, Axel Barroso-Laguna, Yiannis Demiris, Krystian Mikolajczyk http://arxiv.org/abs/2005.13605v1 • [cs.CV]Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification Zhuotun Zhu, Ke Yan, Dakai Jin, Jinzheng Cai, Tsung-Ying Ho, Adam P Harrison, Dazhou Guo, Chun-Hung Chao, Xianghua Ye, Jing Xiao, Alan Yuille, Le Lu http://arxiv.org/abs/2005.13705v1 • [cs.CV]Disentanglement Then Reconstruction: Learning Compact Features for Unsupervised Domain Adaptation Lihua Zhou, Mao Ye, Xinpeng Li, Ce Zhu, Yiguang Liu, Xue Li http://arxiv.org/abs/2005.13947v1 • [cs.CV]End-to-End Object Detection with Transformers Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko http://arxiv.org/abs/2005.12872v3 • [cs.CV]Explainable deep learning models in medical image analysis Amitojdeep Singh, Sourya Sengupta, Vasudevan Lakshminarayanan http://arxiv.org/abs/2005.13799v1 • [cs.CV]False Positive Removal for 3D Vehicle Detection with Penetrated Point Classifier Sungmin Woo, Sangwon Hwang, Woojin Kim, Junhyeop Lee, Dogyoon Lee, Sangyoun Lee http://arxiv.org/abs/2005.13153v2 • [cs.CV]Few-Shot Open-Set Recognition using Meta-Learning Bo Liu, Hao Kang, Haoxiang Li, Gang Hua, Nuno Vasconcelos http://arxiv.org/abs/2005.13713v1 • [cs.CV]Improving Generalized Zero-Shot Learning by Semantic Discriminator Xinpeng Li, Mao Ye, Lihua Zhou, Dan Zhang, Ce Zhu, Yiguang Liu http://arxiv.org/abs/2005.13956v1 • [cs.CV]L^2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion Tunai Porto Marques, Alexandra Branzan Albu http://arxiv.org/abs/2005.13736v1 • [cs.CV]Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection Oliver Rippel, Patrick Mertens, Dorit Merhof http://arxiv.org/abs/2005.14140v1 • [cs.CV]Network Fusion for Content Creation with Conditional INNs Robin Rombach, Patrick Esser, Björn Ommer http://arxiv.org/abs/2005.13580v1 • [cs.CV]P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds Haozhe Qi, Chen Feng, Zhiguo Cao, Feng Zhao, Yang Xiao http://arxiv.org/abs/2005.13888v1 • [cs.CV]Quantifying the Complexity of Standard Benchmarking Datasets for Long-Term Human Trajectory Prediction Ronny Hug, Stefan Becker, Wolfgang Hübner, Michael Arens http://arxiv.org/abs/2005.13934v1 • [cs.CV]Robust Modeling of Epistemic Mental States AKMMahbubur Rahman, ASM Iftekhar Anam, Mohammed Yeasin http://arxiv.org/abs/2005.13982v1 • [cs.CV]Self-supervised Modal and View Invariant Feature Learning Longlong Jing, Yucheng Chen, Ling Zhang, Mingyi He, Yingli Tian http://arxiv.org/abs/2005.14169v1 • [cs.CV]Stereo Vision Based Single-Shot 6D Object Pose Estimation for Bin-Picking by a Robot Manipulator Yoshihiro Nakano http://arxiv.org/abs/2005.13759v1 • [cs.CV]TOAN: Target-Oriented Alignment Network for Fine-Grained Image Categorization with Few Labeled Samples Huaxi Huang, Junjie Zhang, Jian Zhang, Qiang Wu, Chang Xu http://arxiv.org/abs/2005.13820v1 • [cs.CV]Traditional Method Inspired Deep Neural Network for Edge Detection Jan Kristanto Wibisono, Hsueh-Ming Hang http://arxiv.org/abs/2005.13862v1 • [cs.CV]Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild Weixia Zhang, Kede Ma, Guangtao Zhai, Xiaokang Yang http://arxiv.org/abs/2005.13983v1 • [cs.CV]Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets Ke Yan, Jinzheng Cai, Adam P. Harrison, Dakai Jin, Jing Xiao, Le Lu http://arxiv.org/abs/2005.13753v1 • [cs.CV]Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Move’s discrepancies Mattias P Heinrich, Lasse Hansen http://arxiv.org/abs/2005.14107v1 • [cs.CY]An Ambient-Physical System to Infer Concentration in Open-plan Workplace Mohammad Saiedur Rahaman, Jonathan Liono, Yongli Ren, Jeffrey Chan, Shaw Kudo, Tim Rawling, Flora D. Salim http://arxiv.org/abs/2005.13535v1 • [cs.CY]HazeDose: Design and Analysis of a Personal Air Pollution Inhaled Dose Estimation System using Wearable Sensors Ke Hu, Ashfaqur Rahman, Hassan Habibi Gharakheili, Vijay Sivaraman http://arxiv.org/abs/2005.13745v1 • [cs.CY]IMDb data from two generations (1979 to 2019). Part one: Dataset M. Bahraminasr, A. Vafaei Sadr http://arxiv.org/abs/2005.14147v1 • [cs.CY]Modular Politics: Toward a Governance Layer for Online Communities Primavera De Filippi, Seth Frey, Nathan Schneider, Joshua Z. Tan, Amy X. Zhang http://arxiv.org/abs/2005.13701v1 • [cs.CY]Operationalizing the Legal Principle of Data Minimization for Personalization Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck http://arxiv.org/abs/2005.13718v1 • [cs.CY]Scaling Participation — What Does the Concept of Managed Communities Offer for Participatory Design? Stefan Hochwarter, Babak A. Farshchian http://arxiv.org/abs/2005.14045v1 • [cs.DC]A Distributed Multi-GPU System for Large-Scale Node Embedding at Tencent Wanjing Wei, Yangzihao Wang, Pin Gao, Shijie Sun, Donghai Yu http://arxiv.org/abs/2005.13789v1 • [cs.DC]A Theory of Auto-Scaling for Resource Reservation in Cloud Services Konstantinos Psychas, Javad Ghaderi http://arxiv.org/abs/2005.13744v1 • [cs.DC]Brief Announcement: On the Limits of Parallelizing Convolutional Neural Networks on GPUs Behnam Pourghassemi, Chenghao Zhang, Joo Hwan Lee, Aparna Chandramowlishwaran http://arxiv.org/abs/2005.13823v1 • [cs.DC]GraFS: Graph Analytics Fusion and Synthesis Farzin Houshmand, Mohsen Lesani, Keval Vora http://arxiv.org/abs/2005.13632v1 • [cs.DC]HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism Jay H. Park, Gyeongchan Yun, Chang M. Yi, Nguyen T. Nguyen, Seungmin Lee, Jaesik Choi, Sam H. Noh, Young-ri Choi http://arxiv.org/abs/2005.14038v1 • [cs.DC]Network Partitioning and Avoidable Contention Yishai Oltchik, Oded Schwartz http://arxiv.org/abs/2005.14150v1 • [cs.DC]Parallel Load Balancing on Constrained Client-Server Topologies Andrea Clementi, Emanuele Natale, Isabella Ziccardi http://arxiv.org/abs/2005.13583v1 • [cs.DC]Parallelizing Machine Learning as a Service for the End-User Daniela Loreti, Marco Lippi, Paolo Torroni http://arxiv.org/abs/2005.14080v1 • [cs.DC]ProTuner: Tuning Programs with Monte Carlo Tree Search Ameer Haj-Ali, Hasan Genc, Qijing Huang, William Moses, John Wawrzynek, Krste Asanović, Ion Stoica http://arxiv.org/abs/2005.13685v1 • [cs.DC]The Manufacturing Data and Machine Learning Platform: Enabling Real-time Monitoring and Control of Scientific Experiments via IoT Jakob R. Elias, Ryan Chard, Joseph A. Libera, Ian Foster, Santanu Chaudhuri http://arxiv.org/abs/2005.13669v1 • [cs.DL]The POLUSA Dataset: 0.9M Political News Articles Balanced by Time and Outlet Popularity Lukas Gebhard, Felix Hamborg http://arxiv.org/abs/2005.14024v1 • [cs.DS]Distributed algorithms for covering, packing and maximum weighted matching Christos Koufogiannakis, Neal E. Young http://arxiv.org/abs/2005.13628v1 • [cs.ET]Pattern Denoising in Molecular Associative Memory using Pairwise Markov Random Field Models Dharani Punithan, Byoung-Tak Zhang http://arxiv.org/abs/2005.13780v1 • [cs.GT]Chaos, Extremism and Optimism: Volume Analysis of Learning in Games Yun Kuen Cheung, Georgios Piliouras http://arxiv.org/abs/2005.13996v1 • [cs.HC]Heatmap-Based Method for Estimating Drivers’ Cognitive Distraction Antonyo Musabini, Mounsif Chetitah http://arxiv.org/abs/2005.14136v1 • [cs.IR]A Re-visit of the Popularity Baseline in Recommender Systems Yitong Ji, Aixin Sun, Jie Zhang, Chenliang Li http://arxiv.org/abs/2005.13829v1 • [cs.IR]JointMap: Joint Query Intent Understanding For Modeling Intent Hierarchies in E-commerce Search Ali Ahmadvand, Surya Kallumadi, Faizan Javed, Eugene Agichtein http://arxiv.org/abs/2005.13783v1 • [cs.IR]Studying Ranking-Incentivized Web Dynamics Ziv Vasilisky, Moshe Tennenholtz, Oren Kurland http://arxiv.org/abs/2005.13810v1 • [cs.IR]User Behavior Retrieval for Click-Through Rate Prediction Jiarui Qin, Weinan Zhang, Xin Wu, Jiarui Jin, Yuchen Fang, Yong Yu http://arxiv.org/abs/2005.14171v1 • [cs.IR]User Intent Inference for Web Search and Conversational Agents Ali Ahmadvand http://arxiv.org/abs/2005.13808v1 • [cs.IT]Approximate Message Passing with Unitary Transformation for Robust Bilinear Recovery Zhengdao Yuan, Qinghua Guo, Man Luo http://arxiv.org/abs/2005.14132v1 • [cs.IT]Fundamental Limits of Stochastic Caching Networks Adeel Malik, Berksan Serbetci, Emanuele Parrinello, Petros Elia http://arxiv.org/abs/2005.13847v1 • [cs.IT]List Decoding of Arikan’s PAC Codes Hanwen Yao, Arman Fazeli, Alexander Vardy http://arxiv.org/abs/2005.13711v1 • [cs.IT]Multi-access Coded Caching Schemes From Cross Resolvable Designs Digvijay Katyal, Pooja Nayak M, B. Sundar Rajan http://arxiv.org/abs/2005.13731v1 • [cs.IT]On Functions of Markov Random Fields Bernhard C. Geiger, Ali Al-Bashabsheh http://arxiv.org/abs/2005.13908v1 • [cs.IT]On two-weight codes P. G. Boyvalenkov, K. V. Delchev, D. V. Zinoviev, V. A. Zinoviev http://arxiv.org/abs/2005.13623v1 • [cs.IT]Optimal Anticodes, Diameter Perfect Codes, Chains and Weights Luciano Panek, Nayene Michele Paião Panek http://arxiv.org/abs/2005.13715v1 • [cs.IT]Performance Limits of Fluid Antenna Systems Kai-Kit Wong, Arman Shojaeifard, Kin-Fai Tong, Yangyang Zhang http://arxiv.org/abs/2005.13737v1 • [cs.LG]A Feature-map Discriminant Perspective for Pruning Deep Neural Networks Zejiang Hou, Sun-Yuan Kung http://arxiv.org/abs/2005.13796v1 • [cs.LG]Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity Nam Ho-Nguyen, Stephen J. Wright http://arxiv.org/abs/2005.13815v1 • [cs.LG]COVID-19 and Your Smartphone: BLE-based Smart Contact Tracing Pai Chet Ng, Petros Spachos, Konstantinos Plataniotis http://arxiv.org/abs/2005.13754v1 • [cs.LG]CPAC-Conv: CP-decomposition to Approximately Compress Convolutional Layers in Deep Learning Yinan Wang, Weihong, Guo, Xiaowei Yue http://arxiv.org/abs/2005.13746v1 • [cs.LG]Demystifying Orthogonal Monte Carlo and Beyond Han Lin, Haoxian Chen, Tianyi Zhang, Clement Laroche, Krzysztof Choromanski http://arxiv.org/abs/2005.13590v1 • [cs.LG]Domain Knowledge Integration By Gradient Matching For Sample-Efficient Reinforcement Learning Parth Chadha http://arxiv.org/abs/2005.13778v1 • [cs.LG]Explaining Neural Networks by Decoding Layer Activations Johannes Schneider, Michalis Vlachos http://arxiv.org/abs/2005.13630v1 • [cs.LG]Exploiting Non-Linear Redundancy for Neural Model Compression Muhammad A. Shah, Raphael Olivier, Bhiksha Raj http://arxiv.org/abs/2005.14070v1 • [cs.LG]Generalised Interpretable Shapelets for Irregular Time Series Patrick Kidger, James Morrill, Terry Lyons http://arxiv.org/abs/2005.13948v1 • [cs.LG]Looking back to lower-level information in few-shot learning Zhongjie Yu, Sebastian Raschka http://arxiv.org/abs/2005.13638v1 • [cs.LG]Parameter Sharing is Surprisingly Useful for Multi-Agent Deep Reinforcement Learning Justin K Terry, Nathaniel Grammel, Ananth Hari, Luis Santos, Benjamin Black, Dinesh Manocha http://arxiv.org/abs/2005.13625v1 • [cs.LG]Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size Christoph Hertrich, Martin Skutella http://arxiv.org/abs/2005.14105v1 • [cs.LG]QEBA: Query-Efficient Boundary-Based Blackbox Attack Huichen Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, Bo Li http://arxiv.org/abs/2005.14137v1 • [cs.LG]Tensor Decomposition for Multi-agent Predictive State Representation Bilian Chen, Biyang Ma, Yifeng Zeng, Langcai Cao, Jing Tang http://arxiv.org/abs/2005.13706v1 • [cs.LG]Towards the Infeasibility of Membership Inference on Deep Models Shahbaz Rezaei, Xin Liu http://arxiv.org/abs/2005.13702v1 • [cs.LG]VMI-VAE: Variational Mutual Information Maximization Framework for VAE With Discrete and Continuous Priors Andriy Serdega, Dae-Shik Kim http://arxiv.org/abs/2005.13953v1 • [cs.LG]Variational Autoencoder with Embedded Student-$t$ Mixture Model for Authorship Attribution Benedikt Boenninghoff, Steffen Zeiler, Robert M. Nickel, Dorothea Kolossa http://arxiv.org/abs/2005.13930v1 • [cs.NE]Antenna Optimization Using a New Evolutionary Algorithm Based on Tukey-Lambda Probability Distribution Vahraz Jamnejad, Ahmad Hoorfar http://arxiv.org/abs/2005.13594v1 • [cs.NE]Dynamic Bi-Objective Routing of Multiple Vehicles Jakob Bossek, Christian Grimme, Heike Trautmann http://arxiv.org/abs/2005.13872v1 • [cs.NE]From Prediction to Prescription: AI-Based Optimization of Non-Pharmaceutical Interventions for the COVID-19 Pandemic Risto Miikkulainen, Olivier Francon, Elliot Meyerson, Xin Qiu, Elisa Canzani, Babak Hodjat http://arxiv.org/abs/2005.13766v1 • [cs.NE]Genetic optimization algorithms applied toward mission computability models Mee Seong Im, Venkat R. Dasari http://arxiv.org/abs/2005.13105v1 • [cs.NE]Learning Various Length Dependence by Dual Recurrent Neural Networks Chenpeng Zhang, Shuai Li, Mao Ye, Ce Zhu, Xue Li http://arxiv.org/abs/2005.13867v1 • [cs.NE]More Effective Randomized Search Heuristics for Graph Coloring Through Dynamic Optimization Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt http://arxiv.org/abs/2005.13825v1 • [cs.NE]Physics-based polynomial neural networks for one-shot learning of dynamical systems from one or a few samples Andrei Ivanov, Uwe Iben, Anna Golovkina http://arxiv.org/abs/2005.11699v2 • [cs.NE]Towards Decision Support in Dynamic Bi-Objective Vehicle Routing Jakob Bossek, Christian Grimme, Günter Rudolph, Heike Trautmann http://arxiv.org/abs/2005.13865v1 • [cs.NI]Modeling the Location Selection of Mirror Servers in Content Delivery Networks Peter Hillmann, Tobias Uhlig, Gabi Dreo Rodosek, Oliver Rose http://arxiv.org/abs/2005.13905v1 • [cs.NI]Simulation and Optimization of Content Delivery Networks considering User Profiles and Preferences of Internet Service Providers Peter Hillmann, Tobias Uhlig, Gabi Dreo Rodosek, Oliver Rose http://arxiv.org/abs/2005.13896v1 • [cs.RO]Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environments Hartmut Surmann, Christian Jestel, Robin Marchel, Franziska Musberg, Houssem Elhadj, Mahbube Ardani http://arxiv.org/abs/2005.13857v1 • [cs.RO]Graph-based Proprioceptive Localization Using a Discrete Heading-Length Feature Sequence Matching Approach Hsin-Min Cheng, Dezhen Song http://arxiv.org/abs/ 1000 /2005.13704v1 1000 /2005.13704v1) • [cs.RO]Graph-based Proprioceptive Localization Using a Discrete Heading-Length Feature Sequence Matching Approach Hsin-Min Cheng, Dezhen Song http://arxiv.org/abs/2005.13704v1 • [cs.RO]Interaction-Aware Trajectory Prediction of Connected Vehicles using CNN-LSTM Networks Xiaoyu Mo, Yang Xing, Chen Lv http://arxiv.org/abs/2005.12134v2 • [cs.RO]IoT-based Remote Control Study of a Robotic Trans-esophageal Ultrasound Probe via LAN and 5G Shuangyi Wang, Xilong Hou, Richard Housden, Zengguang Hou, Davinder Singh, Kawal Rhode http://arxiv.org/abs/2005.13749v1 • [cs.RO]LyRN (Lyapunov Reaching Network): A Real-Time Closed Loop approach from Monocular Vision Zheyu Zhuang, Xin Yu, Robert Mahony http://arxiv.org/abs/2005.12072v2 • [cs.RO]Perception-aware time optimal path parameterization for quadrotors Igor Spasojevic, Varun Murali, Sertac Karaman http://arxiv.org/abs/2005.13986v1 • [cs.SE]Active Fuzzing for Testing and Securing Cyber-Physical Systems Yuqi Chen, Bohan Xuan, Christopher M. Poskitt, Jun Sun, Fan Zhang http://arxiv.org/abs/2005.14124v1 • [cs.SE]MACER: A Modular Framework for Accelerated Compilation Error Repair Darshak Chhatbar, Umair Z. Ahmed, Purushottam Kar http://arxiv.org/abs/2005.14015v1 • [cs.SE]Using Source Code Density to Improve the Accuracy of Automatic Commit Classification into Maintenance Activities Sebastian Hönel, Morgan Ericsson, Welf Löwe, Anna Wingkvist http://arxiv.org/abs/2005.13904v1 • [cs.SI]Challenges in Combating COVID-19 Infodemic — Data, Tools, and Ethics Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu http://arxiv.org/abs/2005.13691v1 • [cs.SI]Complex networks for event detection in heterogeneous high volume news streams Iraklis Moutidis, Hywel T. P. Williams http://arxiv.org/abs/2005.13751v1 • [cs.SI]Deceptive Deletions for Protecting Withdrawn Posts on Social Platforms Mohsen Minaei, S Chandra Mouli, Mainack Mondal, Bruno Ribeiro, Aniket Kate http://arxiv.org/abs/2005.14113v1 • [cs.SI]Higher Order Temporal Analysis of Global Terrorism Data Madelyn Dunning, Sumit Purohit http://arxiv.org/abs/2005.14002v1 • [cs.SI]Pandemic News: Facebook Pages of Mainstream News Media and the Coronavirus Crisis — A Computational Content Analysis Thorsten Quandt, Svenja Boberg, Tim Schatto-Eckrodt, Lena Frischlich http://arxiv.org/abs/2005.13290v2 • [econ.EM]Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S Victor Chernozhukov, Hiroyuki Kasaha, Paul Schrimpf http://arxiv.org/abs/2005.14168v1 • [econ.EM]Machine learning time series regressions with an application to nowcasting Andrii Babii, Eric Ghysels, Jonas Striaukas http://arxiv.org/abs/2005.14057v1 • [eess.AS]Bayesian Restoration of Audio Degraded by Low-Frequency Pulses Modeled via Gaussian Process Hugo Tremonte de Carvalho, Flávio Rainho Ávila, Luiz Wagner Pereira Biscainho http://arxiv.org/abs/2005.14181v1 • [eess.AS]Modality Dropout for Improved Performance-driven Talking Faces Ahmed Hussen Abdelaziz, Barry-John Theobald, Paul Dixon, Reinhard Knothe, Nicholas Apostoloff, Sachin Kajareker http://arxiv.org/abs/2005.13616v1 • [eess.AS]Speech-to-Singing Conversion based on Boundary Equilibrium GAN Da-Yi Wu, Yi-Hsuan Yang http://arxiv.org/abs/2005.13835v1 • [eess.AS]Unsupervised Audio Source Separation using Generative Priors Vivek Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias http://arxiv.org/abs/2005.13769v1 • [eess.AS]When Can Self-Attention Be Replaced by Feed Forward Layers? Shucong Zhang, Erfan Loweimi, Peter Bell, Steve Renals http://arxiv.org/abs/2005.13895v1 • [eess.IV]A Normalized Fully Convolutional Approach to Head and Neck Cancer Outcome Prediction William Le, Francisco Perdigón Romero http://arxiv.org/abs/2005.14017v1 • [eess.IV]An ENAS Based Approach for Constructing Deep Learning Models for Breast Cancer Recognition from Ultrasound Images Mohammed Ahmed, Hongbo Du, Alaa AlZoubi http://arxiv.org/abs/2005.13695v1 • [eess.IV]Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems Anna Kuzina, Evgenii Egorov, Evgeny Burnaev http://arxiv.org/abs/2005.12639v2 • [eess.IV]Deep Learning for Automatic Pneumonia Detection Tatiana Gabruseva, Dmytro Poplavskiy, Alexandr A. Kalinin http://arxiv.org/abs/2005.13899v1 • [eess.IV]Early Screening of SARS-CoV-2 by Intelligent Analysis of X-Ray Images D. Gil, K. Díaz-Chito, C. Sánchez, A. Hernández-Sabaté http://arxiv.org/abs/2005.13928v1 • [eess.IV]How to do Physics-based Learning Michael Kellman, Michael Lustig, Laura Waller http://arxiv.org/abs/2005.13531v2 • [eess.IV]Image Restoration from Parametric Transformations using Generative Models Kalliopi Basioti, George V. Moustakides http://arxiv.org/abs/2005.14036v1 • [eess.IV]Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification Danilo Avola, Luigi Cinque, Alessio Fagioli, Sebastiano Filetti, Giorgio Grani, Emanuele Rodolà http://arxiv.org/abs/2005.14117v1 • [eess.IV]Multiple resolution residual network for automatic thoracic organs-at-risk segmentation from CT Hyemin Um, Jue Jiang, Maria Thor, Andreas Rimner, Leo Luo, Joseph O. Deasy, Harini Veeraraghavan http://arxiv.org/abs/2005.13690v1 • [eess.IV]Prediction of Thrombectomy Functional Outcomes using Multimodal Data Zeynel A. Samak, Philip Clatworthy, Majid Mirmehdi http://arxiv.org/abs/2005.13061v2 • [eess.IV]Segmentation of the Myocardium on Late-Gadolinium Enhanced MRI based on 2.5 D Residual Squeeze and Excitation Deep Learning Model Abdul Qayyum, Alain Lalande, Thomas Decourselle, Thibaut Pommier, Alexandre Cochet, Fabrice Meriaudeau http://arxiv.org/abs/2005.13643v1 • [eess.IV]Towards computer-aided severity assessment: training and validation of deep neural networks for geographic extent and opacity extent scoring of chest X-rays for SARS-CoV-2 lung disease severity Alexander Wong, Zhong Qiu Lin, Linda Wang, Audrey G. Chung, Beiyi Shen, Almas Abbasi, Mahsa Hoshmand-Kochi, Timothy Q. Duong http://arxiv.org/abs/2005.12855v2 • [eess.SP]A Maneuver-based Urban Driving Dataset and Model for Cooperative Vehicle Applications Behrad Toghi, Divas Grover, Rodolfo Valiente Romero, Yaser P. Fallah http://arxiv.org/abs/2005.13781v1 • [eess.SP]A Vision to Smart Radio Environment: Surface Wave Communication Superhighways Kai-Kit Wong, Kin-Fai Tong, Zhiyuan Chu, Yangyang Zhang http://arxiv.org/abs/2005.14082v1 • [eess.SP]Codebook-Based Beam Tracking for Conformal ArrayEnabled UAV MmWave Networks Jinglin Zhang, Wenjun Xu, Hui Gao, Miao Pan, Zhu Han, Ping Zhang http://arxiv.org/abs/2005.14064v1 • [eess.SY]A Novel Ramp Metering Approach Based on Machine Learning and Historical Data Anahita Sanandaji, Saeed Ghanbartehrani, Zahra Mokhtari, Kimia Tajik http://arxiv.org/abs/2005.13992v1 • [math.DS]Kernel-based approximation of the Koopman generator and Schrödinger operator Stefan Klus, Feliks Nüske, Boumediene Hamzi http://arxiv.org/abs/2005.13231v1 • [math.NT]Simultaneous Diagonalization of Incomplete Matrices and Applications Jean-Sébastien Coron, Luca Notarnicola, Gabor Wiese http://arxiv.org/abs/2005.13629v1 • [math.OC]Derivation of Symmetric PCA Learning Rules from a Novel Objective Function Ralf Möller http://arxiv.org/abs/2005.11689v2 • [math.ST]Comments on the presence of serial correlation in the random coefficients of an autoregressive process Frédéric Proïa, Marius Soltane http://arxiv.org/abs/2005.13951v1 • [math.ST]Group testing with nested pools Inés Armendáriz, Pablo A. Ferrari, Daniel Fraiman, Silvina Ponce Dawson http://arxiv.org/abs/2005.13650v1 • [math.ST]Hawkes process and Edgeworth expansion with application to maximum likelihood estimator Masatoshi Goda http://arxiv.org/abs/2005.13846v1 • [physics.chem-ph]Machine learning and excited-state molecular dynamics Julia Westermayr, Philipp Marquetand http://arxiv.org/abs/2005.14139v1 • [physics.comp-ph]ODEN: A Framework to Solve Ordinary Differential Equations using Artificial Neural Networks Liam L. H. Lau, Denis Werth http://arxiv.org/abs/2005.14090v1 • [physics.comp-ph]Physically interpretable machine learning algorithm on multidimensional non-linear fields Rem-Sophia Mouradi, Cédric Goeury, Olivier Thual, Fabrice Zaoui, Pablo Tassi http://arxiv.org/abs/2005.13912v1 • [physics.data-an]Responses and Degrees of Freedom of PVAR for a Continuous Power-Law PSD François Vernotte, Enrico Rubiola, Siyuan Chen http://arxiv.org/abs/2005.13631v1 • [physics.soc-ph]Revealing consensus and dissensus between network partitions Tiago P. Peixoto http://arxiv.org/abs/2005.13977v1 • [q-bio.MN]Inferring Signaling Pathways with Probabilistic Programming David Merrell, Anthony Gitter http://arxiv.org/abs/2005.14062v1 • [q-fin.PM]Deep Learning for Portfolio Optimisation Zihao Zhang, Stefan Zohren, Stephen Roberts http://arxiv.org/abs/2005.13665v1 • [q-fin.ST]Daily Middle-Term Probabilistic Forecasting of Power Consumption in North-East England Roberto Baviera, Giuseppe Messuti http://arxiv.org/abs/2005.13005v1 • [q-fin.ST]Using Machine Learning to Forecast Future Earnings Xinyue Cui, Zhaoyu Xu, Yue Zhou http://arxiv.org/abs/org/abs/2005.13995v1 • [stat.AP]Clinical trials impacted by the COVID-19 pandemic: Adaptive designs to the rescue? Cornelia Ursula Kunz, Silke Jörgens, Frank Bretz, Nigel Stallard, Kelly Van Lancker, Dong Xi, Sarah Zohar, Christoph Gerlinger, Tim Friede http://arxiv.org/abs/2005.13979v1 • [stat.AP]Forecasting the local progression of the Covid-19 epidemic from medical emergency calls: the example of the Paris area Stéphane Gaubert, Marianne Akian, Xavier Allamigeon, Marin Boyet, Baptiste Colin, Théotime Grohens, Laurent Massoulié, David P. Parsons, Frédéric Adnet, Érick Chanzy, Laurent Goix, Frédéric Lapostolle, Éric Lecarpentier, Christophe Leroy, Thomas Loeb, Jean-Sébastien Marx, Caroline Télion, Laurent Tréluyer, Pierre Carli http://arxiv.org/abs/2005.14186v1 • [stat.AP]Optimal multi-wave sampling for regression modelling in two-phase designs Tong Chen, Thomas Lumley http://arxiv.org/abs/2005.13739v1 • [stat.CO]copent: Estimating Copula Entropy in R Jian Ma http://arxiv.org/abs/2005.14025v1 • [stat.ME]Analysis of time-to-event for observational studies: Guidance to the use of intensity models Per Kragh Andersen, Maja Pohar Perme, Hans C van Houwelingen, Richard J Cook, Pierre Joly, Torben Martinussen, Jeremy MG Taylor, Michal Abrahamowicz, Terry M Therneau http://arxiv.org/abs/2005.13271v2 • [stat.ME]Assessing variable activity for Bayesian regression trees Akira Horiguchi, Matthew T. Pratola, Thomas J. Santner http://arxiv.org/abs/2005.13622v1 • [stat.ME]Boundary-free Estimators of the Mean Residual Life Function by Transformation Rizky Reza Fauzi, Yoshihiko Maesono http://arxiv.org/abs/2005.13805v1 • [stat.ME]Boundary-free Kernel-smoothed Goodness-of-fit Tests for Data on General Interval Rizky Reza Fauzi, Yoshihiko Maesono http://arxiv.org/abs/2005.13794v1 • [stat.ME]Composition Estimation via Shrinkage Chong Gu http://arxiv.org/abs/2005.13988v1 • [stat.ME]Synthetic control method with convex hull restrictions: A Bayesian maximum a posteriori approach Gyuhyeong Goh, Jisang Yu http://arxiv.org/abs/2005.13719v1 • [stat.ML]Breiman’s “Two Cultures” Revisited and Reconciled Subhadeep, Mukhopadhyay, Kaijun Wang http://arxiv.org/abs/2005.13596v1 • [stat.ML]Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao, Clayton Scott, Masashi Sugiyama http://arxiv.org/abs/2005.13748v1 • [stat.ML]Hyperbolic Manifold Regression Gian Maria Marconi, Lorenzo Rosasco, Carlo Ciliberto http://arxiv.org/abs/2005.13885v1 • [stat.ML]Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models Zhijian Ou, Yunfu Song http://arxiv.org/abs/2005.14001v1 • [stat.ML]Review of Mathematical frameworks for Fairness in Machine Learning Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes http://arxiv.org/abs/2005.13755v1 • [stat.ML]Robust estimation via generalized quasi-gradients Banghua Zhu, Jiantao Jiao, Jacob Steinhardt http://arxiv.org/abs/2005.14073v1 • [stat.ML]Travel Time Prediction using Tree-Based Ensembles He Huang, Martin Pouls, Anne Meyer, Markus Pauly http://arxiv.org/abs/2005.13818v1