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今日学术视野(2019.3.15)

今日学术视野(2019.3.15)

作者: ZQtGe6 | 来源:发表于2019-03-15 05:03 被阅读101次

    cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DC - 分布式、并行与集群计算
    cs.GR - 计算机图形学
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.MA - 多代理系统
    cs.NE - 神经与进化计算
    cs.RO - 机器人学
    cs.SI - 社交网络与信息网络
    eess.AS - 语音处理
    eess.SP - 信号处理
    math.OC - 优化与控制
    math.ST - 统计理论
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.CO - 统计计算
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cs.AI]Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent
    • [cs.AI]Efficient Search-Based Weighted Model Integration
    • [cs.AI]Iterated two-phase local search for the Set-Union Knapsack Problem
    • [cs.AI]MMKG: Multi-Modal Knowledge Graphs
    • [cs.CL]"Hang in There": Lexical and Visual Analysis to Identify Posts Warranting Empathetic Responses
    • [cs.CL]Adversarial attacks against Fact Extraction and VERification
    • [cs.CL]Benchmarking Natural Language Understanding Services for building Conversational Agents
    • [cs.CL]Bootstrapping Method for Developing Part-of-Speech Tagged Corpus in Low Resource Languages Tagset - A Focus on an African Igbo
    • [cs.CL]Contextualised concept embedding for efficiently adapting natural language processing models for phenotype identification
    • [cs.CL]End-To-End Speech Recognition Using A High Rank LSTM-CTC Based Model
    • [cs.CL]GASC: Genre-Aware Semantic Change for Ancient Greek
    • [cs.CL]Market Trend Prediction using Sentiment Analysis: Lessons Learned and Paths Forward
    • [cs.CL]Overview of the Ugglan Entity Discovery and Linking System
    • [cs.CL]Persona-Aware Tips Generation
    • [cs.CL]Practical Semantic Parsing for Spoken Language Understanding
    • [cs.CL]Scaling Multi-Domain Dialogue State Tracking via Query Reformulation
    • [cs.CL]Sub-event detection from Twitter streams as a sequence labeling problem
    • [cs.CL]Syntax-aware Neural Semantic Role Labeling with Supertags
    • [cs.CL]Topological Analysis of Syntactic Structures
    • [cs.CL]Transforma at SemEval-2019 Task 6: Offensive Language Analysis using Deep Learning Architecture
    • [cs.CR]Learning Symmetric and Asymmetric Steganography via Adversarial Training
    • [cs.CR]SoK - Security and Privacy in the Age of Drones: Threats, Challenges, Solution Mechanisms, and Scientific Gaps
    • [cs.CV]All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification
    • [cs.CV]An End-to-End Network for Panoptic Segmentation
    • [cs.CV]CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation
    • [cs.CV]Connection Sensitive Attention U-NET for Accurate Retinal Vessel Segmentation
    • [cs.CV]Depth Coefficients for Depth Completion
    • [cs.CV]Dual Residual Network for Accurate Human Activity Recognition
    • [cs.CV]Face Liveness Detection Based on Client Identity Using Siamese Network
    • [cs.CV]Hardness-Aware Deep Metric Learning
    • [cs.CV]Hyperspectral Data Augmentation
    • [cs.CV]Learning Feature Aggregation in Temporal Domain for Re-Identification
    • [cs.CV]LiDAR-assisted Large-scale Privacy Protection in Street-view Cycloramas
    • [cs.CV]Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis
    • [cs.CV]Privacy Preserving Image-Based Localization
    • [cs.CV]RVOS: End-to-End Recurrent Network for Video Object Segmentation
    • [cs.CV]Towards Accurate Camera Geopositioning by Image Matching
    • [cs.CV]Towards Unsupervised Cancer Subtyping: Predicting Prognosis Using A Histologic Visual Dictionary
    • [cs.CV]Tracking without bells and whistles
    • [cs.CV]Two-Stream Oriented Video Super-Resolution for Action Recognition
    • [cs.CV]Universally Slimmable Networks and Improved Training Techniques
    • [cs.CV]Unsupervised Discovery of Parts, Structure, and Dynamics
    • [cs.CV]Visual Semantic Information Pursuit: A Survey
    • [cs.CY]Empirical analysis of the variability in the flow-density relationship for smart motorways
    • [cs.CY]Evaluating the Contextual Integrity of Privacy Regulation: Parents' IoT Toy Privacy Norms Versus COPPA
    • [cs.CY]Improving the quality of healthcare through Internet of Things
    • [cs.CY]Lost Silence: An emergency response early detection service through continuous processing of telecommunication data streams
    • [cs.CY]Teaching Programming Concepts by Developing Games
    • [cs.DC]An Integrated P2P Framework for E-Learning
    • [cs.DC]Asynchronous Federated Optimization
    • [cs.DC]Power-Performance Tradeoffs in Data Center Servers: DVFS, CPU pinning, Horizontal, and Vertical Scaling
    • [cs.GR]A Visually Plausible Grasping System for Object Manipulation and Interaction in Virtual Reality Environments
    • [cs.IR]SciLens: Evaluating the Quality of Scientific News Articles Using Social Media and Scientific Literature Indicators
    • [cs.IT]Age-of-Information vs. Value-of-Information Scheduling for Cellular Networked Control Systems
    • [cs.IT]Construction of Isodual Quasi-cyclic Codes over Finite Fields
    • [cs.IT]MDS codes over finite fields
    • [cs.IT]New Characterizations for the Multi-output Correlation-Immune Boolean Functions
    • [cs.IT]Secure and Efficient Compressed Sensing Based Encryption With Sparse Matrices
    • [cs.IT]Squares of Matrix-product Codes
    • [cs.IT]The Fourier Spectral Characterization for the Correlation-Immune Functions over Fp
    • [cs.LG]A Distributed Hierarchical SGD Algorithm with Sparse Global Reduction
    • [cs.LG]A Review of Reinforcement Learning for Autonomous Building Energy Management
    • [cs.LG]A Sequential Set Generation Method for Predicting Set-Valued Outputs
    • [cs.LG]Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy
    • [cs.LG]AutoML @ NeurIPS 2018 challenge: Design and Results
    • [cs.LG]Confident Kernel Sparse Coding and Dictionary Learning
    • [cs.LG]DREAM-NAP: Decay Replay Mining to Predict Next Process Activities
    • [cs.LG]DeepCount: Crowd Counting with WiFi via Deep Learning
    • [cs.LG]DeepOBS: A Deep Learning Optimizer Benchmark Suite
    • [cs.LG]Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning
    • [cs.LG]Improving Transparency of Deep Neural Inference Process
    • [cs.LG]Learning Gaussian Policies from Corrective Human Feedback
    • [cs.LG]Non-Negative Local Sparse Coding for Subspace Clustering
    • [cs.LG]On the Pitfalls of Measuring Emergent Communication
    • [cs.LG]Online Budgeted Learning for Classifier Induction
    • [cs.LG]Personal Dynamic Cost-Aware Sensing for Latent Context Detection
    • [cs.LG]Richness of Deep Echo State Network Dynamics
    • [cs.LG]ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series Modeling
    • [cs.LG]Task-oriented Design through Deep Reinforcement Learning
    • [cs.LG]What relations are reliably embeddable in Euclidean space?
    • [cs.LG]Zero-shot Domain Adaptation Based on Attribute Information
    • [cs.MA]Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems
    • [cs.NE]Effective reinforcement learning based local search for the maximum k-plex problem
    • [cs.NE]NeuroCore: Guiding CDCL with Unsat-Core Predictions
    • [cs.RO]A Framework for On-line Learning of Underwater Vehicles Dynamic Models
    • [cs.RO]A Path Planning Framework for a Flying Robot in Close Proximity of Humans
    • [cs.RO]A Sliding Mode Force and Position Controller Synthesis for Series Elastic Actuators
    • [cs.RO]Arithmetic-Geometric Mean Robustness for Control from Signal Temporal Logic Specifications
    • [cs.RO]Automated Construction of Metric Maps using a Stochastic Robotic Swarm Leveraging Received Signal Strength
    • [cs.RO]Cleaning tasks knowledge transfer between heterogeneous robots: a deep learning approach
    • [cs.RO]Exploiting Symmetries to Design EKFs with Consistency Properties for Navigation and SLAM
    • [cs.RO]Hypothesis-based Belief Planning for Dexterous Grasping
    • [cs.RO]STRATA: A Unified Framework for Task Assignments in Large Teams of Heterogeneous Robots
    • [cs.RO]Search-based 3D Planning and Trajectory Optimization for Safe Micro Aerial Vehicle Flight Under Sensor Visibility Constraints
    • [cs.RO]Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models
    • [cs.SI]Learning Resolution Parameters for Graph Clustering
    • [eess.AS]Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling
    • [eess.SP]Accessing From The Sky: A Tutorial on UAV Communications for 5G and Beyond
    • [eess.SP]An Accurate Sample Rejection Estimator for the Estimation of Outage Probability of EGC Receivers
    • [math.OC]Computational Bayes-Predictive Stochastic Programming: Finite Sample Bound
    • [math.OC]Novel Approach Towards Global Optimality of Optimal Power Flow Using Quadratic Convex Optimization
    • [math.ST]Dimension reduction as an optimization problem over a set of generalized functions
    • [math.ST]Matrix factorization for multivariate time series analysis
    • [math.ST]The Log-Concave Maximum Likelihood Estimator is Optimal in High Dimensions
    • [quant-ph]An Analytic Semi-device-independent Entanglement Quantification for Bipartite Quantum States
    • [stat.AP]Better-than-expert detection of early coronary artery occlusion from 12 lead electrocardiograms using deep learning
    • [stat.AP]Nonparametric estimation and bootstrap inference on trends in atmospheric time series: an application to ethane
    • [stat.CO]A novel Bayesian approach for variable selection in linear regression models
    • [stat.ME]Doubly Robust Inference when Combining Probability and Non-probability Samples with High-dimensional Data
    • [stat.ME]Neyman-Pearson Criterion (NPC): A Model Selection Criterion for Asymmetric Binary Classification
    • [stat.ME]Simultaneous Confidence Band for Stationary Covariance Function of Dense Functional Data
    • [stat.ML]An Exponential Efron-Stein Inequality for Lq Stable Learning Rules
    • [stat.ML]Continual Learning in Practice
    • [stat.ML]Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
    • [stat.ML]Predicting class-imbalanced business risk using resampling, regularization, and model ensembling algorithms
    • [stat.ML]Transmission Matrix Inference via Pseudolikelihood Decimation
    • [stat.ML]Unbiased Measurement of Feature Importance in Tree-Based Methods
    • [stat.ML]Variational Estimators for Bayesian Optimal Experimental Design

    ·····································

    • [cs.AI]Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent
    Edward Lockhart, Marc Lanctot, Julien Pérolat, Jean-Baptiste Lespiau, Dustin Morrill, Finbarr Timbers, Karl Tuyls
    http://arxiv.org/abs/1903.05614v1

    • [cs.AI]Efficient Search-Based Weighted Model Integration
    Zhe Zeng, Guy Van den Broeck
    http://arxiv.org/abs/1903.05334v1

    • [cs.AI]Iterated two-phase local search for the Set-Union Knapsack Problem
    Zequn Wei, Jin-Kao Hao
    http://arxiv.org/abs/1903.04966v2

    • [cs.AI]MMKG: Multi-Modal Knowledge Graphs
    Ye Liu, Hui Li, Alberto Garcia-Duran, Mathias Niepert, Daniel Onoro-Rubio, David S. Rosenblum
    http://arxiv.org/abs/1903.05485v1

    • [cs.CL]"Hang in There": Lexical and Visual Analysis to Identify Posts Warranting Empathetic Responses
    Mimansa Jaiswal, Sairam Tabibu, Erik Cambria
    http://arxiv.org/abs/1903.05210v1

    • [cs.CL]Adversarial attacks against Fact Extraction and VERification
    James Thorne, Andreas Vlachos
    http://arxiv.org/abs/1903.05543v1

    • [cs.CL]Benchmarking Natural Language Understanding Services for building Conversational Agents
    Xingkun Liu, Arash Eshghi, Pawel Swietojanski, Verena Rieser
    http://arxiv.org/abs/1903.05566v1

    • [cs.CL]Bootstrapping Method for Developing Part-of-Speech Tagged Corpus in Low Resource Languages Tagset - A Focus on an African Igbo
    Onyenwe Ikechukwu E, Onyedinma Ebele G, Aniegwu Godwin E, Ezeani Ignatius M
    http://arxiv.org/abs/1903.05225v1

    • [cs.CL]Contextualised concept embedding for efficiently adapting natural language processing models for phenotype identification
    Honghan Wu, Karen Hodgson, Sue Dyson, Katherine I. Morley, Zina M. Ibrahim, Ehtesham Iqbal, Robert Stewart, Richard JB Dobson, Cathie Sudlow
    http://arxiv.org/abs/1903.03995v2

    • [cs.CL]End-To-End Speech Recognition Using A High Rank LSTM-CTC Based Model
    Yangyang Shi, Mei-Yuh Hwang, Xin Lei
    http://arxiv.org/abs/1903.05261v1

    • [cs.CL]GASC: Genre-Aware Semantic Change for Ancient Greek
    Valerio Perrone, Marco Palma, Simon Hengchen, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray
    http://arxiv.org/abs/1903.05587v1

    • [cs.CL]Market Trend Prediction using Sentiment Analysis: Lessons Learned and Paths Forward
    Andrius Mudinas, Dell Zhang, Mark Levene
    http://arxiv.org/abs/1903.05440v1

    • [cs.CL]Overview of the Ugglan Entity Discovery and Linking System
    Marcus Klang, Firas Dib, Pierre Nugues
    http://arxiv.org/abs/1903.05498v1

    • [cs.CL]Persona-Aware Tips Generation
    Piji Li, Zihao Wang, Lidong Bing, Wai Lam
    http://arxiv.org/abs/1903.02156v2

    • [cs.CL]Practical Semantic Parsing for Spoken Language Understanding
    Marco Damonte, Rahul Goel, Tagyoung Chung
    http://arxiv.org/abs/1903.04521v2

    • [cs.CL]Scaling Multi-Domain Dialogue State Tracking via Query Reformulation
    Pushpendre Rastogi, Arpit Gupta, Tongfei Chen, Lambert Mathias
    http://arxiv.org/abs/1903.05164v1

    • [cs.CL]Sub-event detection from Twitter streams as a sequence labeling problem
    Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder
    http://arxiv.org/abs/1903.05396v1

    • [cs.CL]Syntax-aware Neural Semantic Role Labeling with Supertags
    Jungo Kasai, Dan Friedman, Robert Frank, Dragomir Radev, Owen Rambow
    http://arxiv.org/abs/1903.05260v1

    • [cs.CL]Topological Analysis of Syntactic Structures
    Alexander Port, Taelin Karidi, Matilde Marcolli
    http://arxiv.org/abs/1903.05181v1

    • [cs.CL]Transforma at SemEval-2019 Task 6: Offensive Language Analysis using Deep Learning Architecture
    Ryan Ong
    http://arxiv.org/abs/1903.05280v1

    • [cs.CR]Learning Symmetric and Asymmetric Steganography via Adversarial Training
    Zheng Li, Ge Han, Yunqing Wei, Shanqing Guo
    http://arxiv.org/abs/1903.05297v1

    • [cs.CR]SoK - Security and Privacy in the Age of Drones: Threats, Challenges, Solution Mechanisms, and Scientific Gaps
    Ben Nassi, Asaf Shabtai, Ryusuke Masuoka, Yuval Elovici
    http://arxiv.org/abs/1903.05155v1

    • [cs.CV]All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification
    Weijie Chen, Di Xie, Yuan Zhang, Shiliang Pu
    http://arxiv.org/abs/1903.05285v1

    • [cs.CV]An End-to-End Network for Panoptic Segmentation
    Huanyu Liu, Chao Peng, Changqian Yu, Jingbo Wang, Xu Liu, Gang Yu, Wei Jiang
    http://arxiv.org/abs/1903.05027v2

    • [cs.CV]CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation
    Yanning Zhou, Omer Fahri Onder, Qi Dou, Efstratios Tsougenis, Hao Chen, Pheng-Ann Heng
    http://arxiv.org/abs/1903.05358v1

    • [cs.CV]Connection Sensitive Attention U-NET for Accurate Retinal Vessel Segmentation
    Ruirui Li, Mingming Li, Jiacheng Li
    http://arxiv.org/abs/1903.05558v1

    • [cs.CV]Depth Coefficients for Depth Completion
    Saif Imran, Yunfei Long, Xiaoming Liu, Daniel Morris
    http://arxiv.org/abs/1903.05421v1

    • [cs.CV]Dual Residual Network for Accurate Human Activity Recognition
    Jun Long, WuQing Sun, Zhan Yang, Osolo Ian Raymond, Bin Li
    http://arxiv.org/abs/1903.05359v1

    • [cs.CV]Face Liveness Detection Based on Client Identity Using Siamese Network
    Huiling Hao, Mingtao Pei
    http://arxiv.org/abs/1903.05369v1

    • [cs.CV]Hardness-Aware Deep Metric Learning
    Wenzhao Zheng, Zhaodong Chen, Jiwen Lu, Jie Zhou
    http://arxiv.org/abs/1903.05503v1

    • [cs.CV]Hyperspectral Data Augmentation
    Jakub Nalepa, Michal Myller, Michal Kawulok
    http://arxiv.org/abs/1903.05580v1

    • [cs.CV]Learning Feature Aggregation in Temporal Domain for Re-Identification
    Jakub Špaňhel, Jakub Sochor, Roman Juránek, Petr Dobeš, Vojtěch Bartl, Adam Herout
    http://arxiv.org/abs/1903.05244v1

    • [cs.CV]LiDAR-assisted Large-scale Privacy Protection in Street-view Cycloramas
    Clint Sebastian, Bas Boom, Egor Bondarev, Peter H. N. de With
    http://arxiv.org/abs/1903.05598v1

    • [cs.CV]Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis
    Qi Mao, Hsin-Ying Lee, Hung-Yu Tseng, Siwei Ma, Ming-Hsuan Yang
    http://arxiv.org/abs/1903.05628v1

    • [cs.CV]Privacy Preserving Image-Based Localization
    Pablo Speciale, Johannes L. Schönberger, Sing Bing Kang, Sudipta N. Sinha, Marc Pollefeys
    http://arxiv.org/abs/1903.05572v1

    • [cs.CV]RVOS: End-to-End Recurrent Network for Video Object Segmentation
    Carles Ventura, Miriam Bellver, Andreu Girbau, Amaia Salvador, Ferran Marques, Xavier Giro-i-Nieto
    http://arxiv.org/abs/1903.05612v1

    • [cs.CV]Towards Accurate Camera Geopositioning by Image Matching
    Raffaele Imbriaco, Clint Sebastian, Egor Bondarev, Peter de With
    http://arxiv.org/abs/1903.05454v1

    • [cs.CV]Towards Unsupervised Cancer Subtyping: Predicting Prognosis Using A Histologic Visual Dictionary
    Hassan Muhammad, Carlie S. Sigel, Gabriele Campanella, Thomas Boerner, Linda M. Pak, Stefan Büttner, Jan N. M. IJzermans, Bas Groot Koerkamp, Michael Doukas, William R. Jarnagin, Amber Simpson, Thomas J. Fuchs
    http://arxiv.org/abs/1903.05257v1

    • [cs.CV]Tracking without bells and whistles
    Philipp Bergmann, Tim Meinhardt, Laura Leal-Taixe
    http://arxiv.org/abs/1903.05625v1

    • [cs.CV]Two-Stream Oriented Video Super-Resolution for Action Recognition
    Haochen Zhang, Dong Liu, Zhiwei Xiong
    http://arxiv.org/abs/1903.05577v1

    • [cs.CV]Universally Slimmable Networks and Improved Training Techniques
    Jiahui Yu, Thomas Huang
    http://arxiv.org/abs/1903.05134v1

    • [cs.CV]Unsupervised Discovery of Parts, Structure, and Dynamics
    Zhenjia Xu, Zhijian Liu, Chen Sun, Kevin Murphy, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu
    http://arxiv.org/abs/1903.05136v1

    • [cs.CV]Visual Semantic Information Pursuit: A Survey
    Daqi Liu, Miroslaw Bober, Josef Kittler
    http://arxiv.org/abs/1903.05434v1

    • [cs.CY]Empirical analysis of the variability in the flow-density relationship for smart motorways
    Kieran Kalair, Colm Connaughton
    http://arxiv.org/abs/1903.05112v1

    • [cs.CY]Evaluating the Contextual Integrity of Privacy Regulation: Parents' IoT Toy Privacy Norms Versus COPPA
    Noah Apthorpe, Sarah Varghese, Nick Feamster
    http://arxiv.org/abs/1903.05152v1

    • [cs.CY]Improving the quality of healthcare through Internet of Things
    Cornel Turcu, Cristina Turcu
    http://arxiv.org/abs/1903.05221v1

    • [cs.CY]Lost Silence: An emergency response early detection service through continuous processing of telecommunication data streams
    Qianru Zhou, Stephen McLaughlin, Alasdair J. G. Gray, Shangbin Wu, Chengxiang Wang
    http://arxiv.org/abs/1903.05372v1

    • [cs.CY]Teaching Programming Concepts by Developing Games
    Kailash Chandra, Shyamal Suhana Chandra
    http://arxiv.org/abs/1903.05207v1

    • [cs.DC]An Integrated P2P Framework for E-Learning
    Nikita Bhagatkar, Kapil Dolas, R. K. Ghosh
    http://arxiv.org/abs/1903.05474v1

    • [cs.DC]Asynchronous Federated Optimization
    Cong Xie, Sanmi Koyejo, Indranil Gupta
    http://arxiv.org/abs/1903.03934v2

    • [cs.DC]Power-Performance Tradeoffs in Data Center Servers: DVFS, CPU pinning, Horizontal, and Vertical Scaling
    Jakub Krzywda, Ahmed Ali-Eldin, Trevor E. Carlson, Per-Olov Östberg, Erik Elmroth
    http://arxiv.org/abs/1903.05488v1

    • [cs.GR]A Visually Plausible Grasping System for Object Manipulation and Interaction in Virtual Reality Environments
    Sergiu Oprea, Pablo Martinez-Gonzalez, Alberto Garcia-Garcia, John Alejandro Castro-Vargas, Sergio Orts-Escolano, Jose Garcia-Rodriguez
    http://arxiv.org/abs/1903.05238v1

    • [cs.IR]SciLens: Evaluating the Quality of Scientific News Articles Using Social Media and Scientific Literature Indicators
    Panayiotis Smeros, Carlos Castillo, Karl Aberer
    http://arxiv.org/abs/1903.05538v1

    • [cs.IT]Age-of-Information vs. Value-of-Information Scheduling for Cellular Networked Control Systems
    Onur Ayan, Mikhail Vilgelm, Markus Klügel, Sandra Hirche, Wolfgang Kellerer
    http://arxiv.org/abs/1903.05356v1

    • [cs.IT]Construction of Isodual Quasi-cyclic Codes over Finite Fields
    Fatma-Zahra Benahmed, Kenza Guenda, Aicha Batoul, T. Aaron Gulliver
    http://arxiv.org/abs/1903.04911v1

    • [cs.IT]MDS codes over finite fields
    Ted Hurley
    http://arxiv.org/abs/1903.05265v1

    • [cs.IT]New Characterizations for the Multi-output Correlation-Immune Boolean Functions
    Jinjin Chai, Zilong Wang, Guang Gong
    http://arxiv.org/abs/1903.05351v1

    • [cs.IT]Secure and Efficient Compressed Sensing Based Encryption With Sparse Matrices
    Wonwoo Cho, Nam Yul Yu
    http://arxiv.org/abs/1903.05436v1

    • [cs.IT]Squares of Matrix-product Codes
    Ignacio Cascudo, Jaron Skovsted Gundersen, Diego Ruano
    http://arxiv.org/abs/1903.05494v1

    • [cs.IT]The Fourier Spectral Characterization for the Correlation-Immune Functions over Fp
    Zilong Wang, Jinjin Chai, Guang Gong
    http://arxiv.org/abs/1903.05350v1

    • [cs.LG]A Distributed Hierarchical SGD Algorithm with Sparse Global Reduction
    Fan Zhou, Guojing Cong
    http://arxiv.org/abs/1903.05133v1

    • [cs.LG]A Review of Reinforcement Learning for Autonomous Building Energy Management
    Karl Mason, Santiago Grijalva
    http://arxiv.org/abs/1903.05196v1

    • [cs.LG]A Sequential Set Generation Method for Predicting Set-Valued Outputs
    Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
    http://arxiv.org/abs/1903.05153v1

    • [cs.LG]Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy
    Yunhao Tang, Mingzhang Yin, Mingyuan Zhou
    http://arxiv.org/abs/1903.05284v1

    • [cs.LG]AutoML @ NeurIPS 2018 challenge: Design and Results
    Hugo Jair Escalante, Wei Tu, Isabelle Guyon, Daniel L. Silver, Evelyne Viegas, Yuqiang Chen, Wenyuan Dai, Qiang Yang
    http://arxiv.org/abs/1903.05263v1

    • [cs.LG]Confident Kernel Sparse Coding and Dictionary Learning
    Babak Hosseini, Barbara Hammer
    http://arxiv.org/abs/1903.05219v1

    • [cs.LG]DREAM-NAP: Decay Replay Mining to Predict Next Process Activities
    Julian Theis, Houshang Darabi
    http://arxiv.org/abs/1903.05084v1

    • [cs.LG]DeepCount: Crowd Counting with WiFi via Deep Learning
    Shangqing Liu, Yanchao Zhao, Fanggang Xue, Bing Chen, Xiang Chen
    http://arxiv.org/abs/1903.05316v1

    • [cs.LG]DeepOBS: A Deep Learning Optimizer Benchmark Suite
    Frank Schneider, Lukas Balles, Philipp Hennig
    http://arxiv.org/abs/1903.05499v1

    • [cs.LG]Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning
    Liam Li, Evan Sparks, Kevin Jamieson, Ameet Talwalkar
    http://arxiv.org/abs/1903.05176v1

    • [cs.LG]Improving Transparency of Deep Neural Inference Process
    Hiroshi Kuwajima, Masayuki Tanaka, Masatoshi Okutomi
    http://arxiv.org/abs/1903.05501v1

    • [cs.LG]Learning Gaussian Policies from Corrective Human Feedback
    Daan Wout, Jan Scholten, Carlos Celemin, Jens Kober
    http://arxiv.org/abs/1903.05216v1

    • [cs.LG]Non-Negative Local Sparse Coding for Subspace Clustering
    Babak Hosseini, Barbara Hammer
    http://arxiv.org/abs/1903.05239v1

    • [cs.LG]On the Pitfalls of Measuring Emergent Communication
    Ryan Lowe, Jakob Foerster, Y-Lan Boureau, Joelle Pineau, Yann Dauphin
    http://arxiv.org/abs/1903.05168v1

    • [cs.LG]Online Budgeted Learning for Classifier Induction
    Eran Fainman, Bracha Shapira, Lior Rokach, Yisroel Mirsky
    http://arxiv.org/abs/1903.05382v1

    • [cs.LG]Personal Dynamic Cost-Aware Sensing for Latent Context Detection
    Saar Tal, Bracha Shapira, Lior Rokach
    http://arxiv.org/abs/1903.05376v1

    • [cs.LG]Richness of Deep Echo State Network Dynamics
    Claudio Gallicchio, Alessio Micheli
    http://arxiv.org/abs/1903.05174v1

    • [cs.LG]ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series Modeling
    Bing Yu, Haoteng Yin, Zhanxing Zhu
    http://arxiv.org/abs/1903.05631v1

    • [cs.LG]Task-oriented Design through Deep Reinforcement Learning
    Junyoung Choi, Minsung Hyun, Nojun Kwak
    http://arxiv.org/abs/1903.05271v1

    • [cs.LG]What relations are reliably embeddable in Euclidean space?
    Robi Bhattacharjee, Sanjoy Dasgupta
    http://arxiv.org/abs/1903.05347v1

    • [cs.LG]Zero-shot Domain Adaptation Based on Attribute Information
    Masato Ishii, Takashi Takenouchi, Masashi Sugiyama
    http://arxiv.org/abs/1903.05312v1

    • [cs.MA]Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems
    Kleanthis Malialis, Sam Devlin, Daniel Kudenko
    http://arxiv.org/abs/1903.05431v1

    • [cs.NE]Effective reinforcement learning based local search for the maximum k-plex problem
    Yan Jin, John H. Drake, Una Benlic, Kun He
    http://arxiv.org/abs/1903.05537v1

    • [cs.NE]NeuroCore: Guiding CDCL with Unsat-Core Predictions
    Daniel Selsam, Nikolaj Bjørner
    http://arxiv.org/abs/1903.04671v2

    • [cs.RO]A Framework for On-line Learning of Underwater Vehicles Dynamic Models
    Bilal Wehbe, Marc Hildebrandt, Frank Kirchner
    http://arxiv.org/abs/1903.05355v1

    • [cs.RO]A Path Planning Framework for a Flying Robot in Close Proximity of Humans
    Hyung-Jin Yoon, Christopher Widdowson, Thiago Marinho, Ranxiao Frances Wang, Naira Hovakimyan
    http://arxiv.org/abs/1903.05156v1

    • [cs.RO]A Sliding Mode Force and Position Controller Synthesis for Series Elastic Actuators
    Emre Sariyildiz, Rahim Mutlu, Haoyong Yu
    http://arxiv.org/abs/1903.05337v1

    • [cs.RO]Arithmetic-Geometric Mean Robustness for Control from Signal Temporal Logic Specifications
    Noushin Mehdipour, Cristian-Ioan Vasile, Calin Belta
    http://arxiv.org/abs/1903.05186v1

    • [cs.RO]Automated Construction of Metric Maps using a Stochastic Robotic Swarm Leveraging Received Signal Strength
    Ragesh K. Ramachandran, Spring Berman
    http://arxiv.org/abs/1903.05392v1

    • [cs.RO]Cleaning tasks knowledge transfer between heterogeneous robots: a deep learning approach
    Jaeseok Kim, Nino Cauli, Pedro Vicente, Bruno Damas, Alexandre Bernardino, José Santos-Victor, Filippo Cavallo
    http://arxiv.org/abs/1903.05635v1

    • [cs.RO]Exploiting Symmetries to Design EKFs with Consistency Properties for Navigation and SLAM
    Martin Brossard, Axel Barrau, Silvère Bonnabel
    http://arxiv.org/abs/1903.05384v1

    • [cs.RO]Hypothesis-based Belief Planning for Dexterous Grasping
    Claudio Zito, Valerio Ortenzi, Maxime Adjigble, Marek Kopicki, Rustam Stolkin, Jeremy L. Wyatt
    http://arxiv.org/abs/1903.05517v1

    • [cs.RO]STRATA: A Unified Framework for Task Assignments in Large Teams of Heterogeneous Robots
    Harish Ravichandar, Kenneth Shaw, Sonia Chernova
    http://arxiv.org/abs/1903.05149v1

    • [cs.RO]Search-based 3D Planning and Trajectory Optimization for Safe Micro Aerial Vehicle Flight Under Sensor Visibility Constraints
    Matthias Nieuwenhuisen, Sven Behnke
    http://arxiv.org/abs/1903.05165v1

    • [cs.RO]Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models
    Adith Boloor, Xin He, Christopher Gill, Yevgeniy Vorobeychik, Xuan Zhang
    http://arxiv.org/abs/1903.05157v1

    • [cs.SI]Learning Resolution Parameters for Graph Clustering
    Nate Veldt, David F. Gleich, Anthony Wirth
    http://arxiv.org/abs/1903.05246v1

    • [eess.AS]Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling
    Peidong Wang, Ke Tan, DeLiang Wang
    http://arxiv.org/abs/1903.04567v2

    • [eess.SP]Accessing From The Sky: A Tutorial on UAV Communications for 5G and Beyond
    Yong Zeng, Qingqing Wu, Rui Zhang
    http://arxiv.org/abs/1903.05289v1

    • [eess.SP]An Accurate Sample Rejection Estimator for the Estimation of Outage Probability of EGC Receivers
    Nadhir Ben Rached, Abla Kammoun, Mohamed-Slim Alouini, Raul Tempone
    http://arxiv.org/abs/1903.05481v1

    • [math.OC]Computational Bayes-Predictive Stochastic Programming: Finite Sample Bound
    Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
    http://arxiv.org/abs/1903.05220v1

    • [math.OC]Novel Approach Towards Global Optimality of Optimal Power Flow Using Quadratic Convex Optimization
    Hadrien Godard, Sourour Elloumi, Amélie Lambert, Jean Maeght, Manuel Ruiz
    http://arxiv.org/abs/1903.05390v1

    • [math.ST]Dimension reduction as an optimization problem over a set of generalized functions
    Rustem Takhanov
    http://arxiv.org/abs/1903.05083v1

    • [math.ST]Matrix factorization for multivariate time series analysis
    Pierre Alquier, Nicolas Marie
    http://arxiv.org/abs/1903.05589v1

    • [math.ST]The Log-Concave Maximum Likelihood Estimator is Optimal in High Dimensions
    Yuval Dagan, Gil Kur
    http://arxiv.org/abs/1903.05315v1

    • [quant-ph]An Analytic Semi-device-independent Entanglement Quantification for Bipartite Quantum States
    Zhaohui Wei
    http://arxiv.org/abs/1903.05303v1

    • [stat.AP]Better-than-expert detection of early coronary artery occlusion from 12 lead electrocardiograms using deep learning
    Rob Brisk, Raymond R Bond. Dewar D Finlay, James McLaughlin, Alicja Piadlo, Stephen J Leslie, David E Gossman, Ian B A Menown, David J McEneaney
    http://arxiv.org/abs/1903.04421v2

    • [stat.AP]Nonparametric estimation and bootstrap inference on trends in atmospheric time series: an application to ethane
    Marina Friedrich, Eric Beutner, Hanno Reuvers, Stephan Smeekes, Jean-Pierre Urbain, Whitney Bader, Bruno Franco, Bernard Lejeune, Emmanuel Mahieu
    http://arxiv.org/abs/1903.05403v1

    • [stat.CO]A novel Bayesian approach for variable selection in linear regression models
    Konstantin Posch, Maximilian Arbeiter, Jürgen Pilz
    http://arxiv.org/abs/1903.05367v1

    • [stat.ME]Doubly Robust Inference when Combining Probability and Non-probability Samples with High-dimensional Data
    Shu Yang, Jae Kwang Kim, Rui Song
    http://arxiv.org/abs/1903.05212v1

    • [stat.ME]Neyman-Pearson Criterion (NPC): A Model Selection Criterion for Asymmetric Binary Classification
    Yiling Chen, Jingyi Jessica Li, Xin Tong
    http://arxiv.org/abs/1903.05262v1

    • [stat.ME]Simultaneous Confidence Band for Stationary Covariance Function of Dense Functional Data
    Jiangyan Wang, Guanqun Cao, Li Wang, Lijian Yang
    http://arxiv.org/abs/1903.05522v1

    • [stat.ML]An Exponential Efron-Stein Inequality for Lq Stable Learning Rules
    Karim Abou-Moustafa, Csaba Szepesvari
    http://arxiv.org/abs/1903.05457v1

    • [stat.ML]Continual Learning in Practice
    Tom Diethe, Tom Borchert, Eno Thereska, Borja de Balle Pigem, Neil Lawrence
    http://arxiv.org/abs/1903.05202v1

    • [stat.ML]Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
    Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
    http://arxiv.org/abs/1903.05594v1

    • [stat.ML]Predicting class-imbalanced business risk using resampling, regularization, and model ensembling algorithms
    Yan Wang, Xuelei Sherry Ni
    http://arxiv.org/abs/1903.05535v1

    • [stat.ML]Transmission Matrix Inference via Pseudolikelihood Decimation
    Daniele Ancora, Luca Leuzzi
    http://arxiv.org/abs/1903.05379v1

    • [stat.ML]Unbiased Measurement of Feature Importance in Tree-Based Methods
    Zhengze Zhou, Giles Hooker
    http://arxiv.org/abs/1903.05179v1

    • [stat.ML]Variational Estimators for Bayesian Optimal Experimental Design
    Adam Foster, Martin Jankowiak, Eli Bingham, Paul Horsfall, Yee Whye Teh, Tom Rainforth, Noah Goodman
    http://arxiv.org/abs/1903.05480v1

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