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今日学术视野(2019.1.18)

今日学术视野(2019.1.18)

作者: ZQtGe6 | 来源:发表于2019-01-18 05:28 被阅读128次

    cs.AI - 人工智能
    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.ET - 新兴技术
    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.PL - 编程语言
    cs.RO - 机器人学
    cs.SD - 声音处理
    cs.SI - 社交网络与信息网络
    eess.SP - 信号处理
    hep-ex - 高能物理实验
    math.NA - 数值分析
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.ed-ph - 物理教育
    physics.soc-ph - 物理学与社会
    q-bio.GN - 基因组学
    q-bio.PE - 人口与发展
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cs.AI]Evolutionarily-Curated Curriculum Learning for Deep Reinforcement Learning Agents
    • [cs.AI]IEDM, an Ontology for Irradiation Experiment Data Management
    • [cs.AI]Robot Sequential Decision Making using LSTM-based Learning and Logical-probabilistic Reasoning
    • [cs.AI]Soft Constraints for Inference with Declarative Knowledge
    • [cs.CL]A Tweet Dataset Annotated for Named Entity Recognition and Stance Detection
    • [cs.CL]Answering Comparative Questions: Better than Ten-Blue-Links?
    • [cs.CL]Assessing BERT's Syntactic Abilities
    • [cs.CL]Dependency or Span, End-to-End Uniform Semantic Role Labeling
    • [cs.CL]Formal models of Structure Building in Music, Language and Animal Songs
    • [cs.CL]Investigating Antigram Behaviour using Distributional Semantics
    • [cs.CL]Learning from Dialogue after Deployment: Feed Yourself, Chatbot!
    • [cs.CL]Sentence transition matrix: An efficient approach that preserves sentence semantics
    • [cs.CL]Variable-sized input, character-level recurrent neural networks in lead generation: predicting close rates from raw user inputs
    • [cs.CV]A Comprehensive Performance Evaluation for 3D Transformation Estimation Techniques
    • [cs.CV]A Functional Representation for Graph Matching
    • [cs.CV]Actions Speak Louder Than (Pass)words: Passive Authentication of Smartphone Users via Deep Temporal Features
    • [cs.CV]Attention-aware Multi-stroke Style Transfer
    • [cs.CV]DAFE-FD: Density Aware Feature Enrichment for Face Detection
    • [cs.CV]Deep Grid Net (DGN): A Deep Learning System for Real-Time Driving Context Understanding
    • [cs.CV]Deep Supervised Hashing leveraging Quadratic Spherical Mutual Information for Content-based Image Retrieval
    • [cs.CV]DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
    • [cs.CV]Domain Adaptation for Structured Output via Discriminative Representations
    • [cs.CV]Light-weighted Saliency Detection with Distinctively Lower Memory Cost and Model Size
    • [cs.CV]Lightweight Markerless Monocular Face Capture with 3D Spatial Priors
    • [cs.CV]MRI to CT Translation with GANs
    • [cs.CV]Nonrigid reconstruction of 3D breast surfaces with a low-cost RGBD camera for surgical planning and aesthetic evaluation
    • [cs.CV]Real-world Underwater Enhancement: Challenging, Benchmark and Efficient Solutions
    • [cs.CV]Technical Report on Visual Quality Assessment for Frame Interpolation
    • [cs.CV]UAN: Unified Attention Network for Convolutional Neural Networks
    • [cs.CY]Artificial Intelligence for Social Good
    • [cs.CY]Teaching Electronics and Programming in Norwegian Schools Using the air:bit Sensor Kit
    • [cs.CY]Tracking the Digital Traces of Russian Trolls: Distinguishing the Roles and Strategy of Trolls On Twitter
    • [cs.DC]Achlys : Towards a framework for distributed storage and generic computing applications for wireless IoT edge networks with Lasp on GRiSP
    • [cs.DS]The Bayesian Prophet: A Low-Regret Framework for Online Decision Making
    • [cs.ET]On complexity of branching droplets in electrical field
    • [cs.IR]It's Only Words And Words Are All I Have
    • [cs.IR]Large-Scale Joint Topic, Sentiment & User Preference Analysis for Online Reviews
    • [cs.IT]Adaptive Learning-Based Task Offloading for Vehicular Edge Computing Systems
    • [cs.IT]An Exponential Lower Bound on the Sub-Packetization of MSR Codes
    • [cs.IT]Asymptotic Analysis on LDPC-BICM Scheme for Compute-and-Forward Relaying
    • [cs.IT]Channel Conditions for the Optimality of Interference Decoding Schemes for K-user Gaussian Interference Channels
    • [cs.IT]Coded Federated Computing in Wireless Networks with Straggling Devices and Imperfect CSI
    • [cs.IT]Coded Matrix Multiplication on a Group-Based Model
    • [cs.IT]Hybrid Beamformer Design for High Dynamic Range Ambient Backscatter Receivers
    • [cs.IT]Linear complementary dual, maximum distance separable codes
    • [cs.IT]Low-Complexity Joint Channel Estimation and List Decoding of Short Codes
    • [cs.IT]Relative Age of Information: A New Metric for Status Update Systems
    • [cs.IT]STORNS: Stochastic Radio Access Network Slicing
    • [cs.IT]Status from a Random Field: How Densely Should One Update?
    • [cs.IT]Using auto-encoders for solving ill-posed linear inverse problems
    • [cs.IT]Utility Regions for DF Relay in OFDMA-based Secure Communication with Untrusted Users
    • [cs.LG]A review of single-source unsupervised domain adaptation
    • [cs.LG]AI Pipeline - bringing AI to you. End-to-end integration of data, algorithms and deployment tools
    • [cs.LG]CFOF: A Concentration Free Measure for Anomaly Detection
    • [cs.LG]MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks
    • [cs.LG]Memory Augmented Deep Generative models for Forecasting the Next Shot Location in Tennis
    • [cs.LG]ReNeg and Backseat Driver: Learning from Demonstration with Continuous Human Feedback
    • [cs.LG]Representation Learning on Graphs: A Reinforcement Learning Application
    • [cs.LG]TensorFlow.js: Machine Learning for the Web and Beyond
    • [cs.NE]The Discrete Langevin Machine: Bridging the Gap Between Thermodynamic and Neuromorphic Systems
    • [cs.PL]Predicting Variable Types in Dynamically Typed Programming Languages
    • [cs.RO]GridSim: A Vehicle Kinematics Engine for Deep Neuroevolutionary Control in Autonomous Driving
    • [cs.RO]Timely Negotiation and Correction of Shared Intentions With Body Motion
    • [cs.RO]Uncertainty-Aware Driver Trajectory Prediction at Urban Intersections
    • [cs.SD]Spectrogram Feature Losses for Music Source Separation
    • [cs.SI]Beyond Uniform Reverse Sampling: A Hybrid Sampling Technique for Misinformation Prevention
    • [cs.SI]Location, Occupation, and Semantics based Socioeconomic Status Inference on Twitter
    • [cs.SI]Weighted Label Propagation Algorithm based on Local Edge Betweenness
    • [eess.SP]Seizure Detection using Least EEG Channels by Deep Convolutional Neural Network
    • [hep-ex]LHC analysis-specific datasets with Generative Adversarial Networks
    • [math.NA]Algorithms for \ell_p-based semi-supervised learning on graphs
    • [math.OC]DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
    • [math.OC]Optimization Models for Machine Learning: A Survey
    • [math.ST]Bayesian sequential least-squares estimation for the drift of a Wiener process
    • [math.ST]Joint temporal and contemporaneous aggregation of random-coefficient AR(1) processes with infinite variance
    • [math.ST]On posterior contraction of parameters and interpretability in Bayesian mixture modeling
    • [math.ST]The median of a jittered Poisson distribution
    • [math.ST]Tracy-Widom limit for the largest eigenvalue of high-dimensional covariance matrices in elliptical distributions
    • [physics.ed-ph]Using CoCalc as a Training Tool for Mathematics Teachers Pre-Service Training
    • [physics.soc-ph]On the frequency and severity of interstate wars
    • [q-bio.GN]Determining Multifunctional Genes and Diseases in Human Using Gene Ontology
    • [q-bio.PE]On a family of stochastic SVIR influenza epidemic models and maximum likelihood estimation
    • [quant-ph]Machine learning applied to quantum synchronization-assisted probing
    • [quant-ph]The RGB No-Signalling Game
    • [stat.AP]How to Host a Data Competition: Statistical Advice for Design and Analysis of a Data Competition
    • [stat.AP]Improving linear quantile regression for replicated data
    • [stat.AP]Multivariate mixed membership modeling: Inferring domain-specific risk profiles
    • [stat.AP]Novel metrics for quantifying the capacity of subgroup-defining variables to yield efficient treatment rules
    • [stat.AP]Six-Day Footraces in the Post-Pedestrianism Era
    • [stat.ME]A Note on the Estimation Method of Intervention Effects based on Statistical Decision Theory
    • [stat.ME]A nonparametric super-efficient estimator of the average treatment effect
    • [stat.ME]Learning Temporal Evolution of Spatial Dependence with Generalized Spatiotemporal Gaussian Process Models
    • [stat.ME]On the Estimation of Population Size from a Dependent Triple Record System
    • [stat.ME]Smooth Adjustment for Correlated Effects
    • [stat.ME]Two-stage Circular-circular Regression with Rounding Error: An Application to Cataract Surgery Data
    • [stat.ML]A Primer on PAC-Bayesian Learning
    • [stat.ML]Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques
    • [stat.ML]The Winning Solution to the IEEE CIG 2017 Game Data Mining Competition

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

    • [cs.AI]Evolutionarily-Curated Curriculum Learning for Deep Reinforcement Learning Agents
    Michael Cerny Green, Benjamin Sergent, Pushyami Shandilya, Vibhor Kumar
    http://arxiv.org/abs/1901.05431v1

    • [cs.AI]IEDM, an Ontology for Irradiation Experiment Data Management
    Blerina Gkotse, Pierre Jouvelot, Federico Ravotti
    http://arxiv.org/abs/1901.05233v1

    • [cs.AI]Robot Sequential Decision Making using LSTM-based Learning and Logical-probabilistic Reasoning
    Saeid Amiri, Mohammad Shokrolah Shirazi, Shiqi Zhang
    http://arxiv.org/abs/1901.05322v1

    • [cs.AI]Soft Constraints for Inference with Declarative Knowledge
    Zenna Tavares, Javier Burroni, Edgar Minaysan, Armando Solar Lezama, Rajesh Ranganath
    http://arxiv.org/abs/1901.05437v1

    • [cs.CL]A Tweet Dataset Annotated for Named Entity Recognition and Stance Detection
    Dilek Küçük, Fazli Can
    http://arxiv.org/abs/1901.04787v2

    • [cs.CL]Answering Comparative Questions: Better than Ten-Blue-Links?
    Matthias Schildwächter, Alexander Bondarenko, Julian Zenker, Matthias Hagen, Chris Biemann, Alexander Panchenko
    http://arxiv.org/abs/1901.05041v1

    • [cs.CL]Assessing BERT's Syntactic Abilities
    Yoav Goldberg
    http://arxiv.org/abs/1901.05287v1

    • [cs.CL]Dependency or Span, End-to-End Uniform Semantic Role Labeling
    Zuchao Li, Shexia He, Hai Zhao, Yiqing Zhang, Zhuosheng Zhang, Xi Zhou, Xiang Zhou
    http://arxiv.org/abs/1901.05280v1

    • [cs.CL]Formal models of Structure Building in Music, Language and Animal Songs
    Willem Zuidema, Dieuwke Hupkes, Geraint Wiggins, Constance Scharff, Martin Rohrmeier
    http://arxiv.org/abs/1901.05180v1

    • [cs.CL]Investigating Antigram Behaviour using Distributional Semantics
    Saptarshi Sengupta
    http://arxiv.org/abs/1901.05066v1

    • [cs.CL]Learning from Dialogue after Deployment: Feed Yourself, Chatbot!
    Braden Hancock, Antoine Bordes, Pierre-Emmanuel Mazare, Jason Weston
    http://arxiv.org/abs/1901.05415v1

    • [cs.CL]Sentence transition matrix: An efficient approach that preserves sentence semantics
    Myeongjun Jang, Pilsung Kang
    http://arxiv.org/abs/1901.05219v1

    • [cs.CL]Variable-sized input, character-level recurrent neural networks in lead generation: predicting close rates from raw user inputs
    Giulio Giorcelli
    http://arxiv.org/abs/1901.05115v1

    • [cs.CV]A Comprehensive Performance Evaluation for 3D Transformation Estimation Techniques
    Bao Zhao, Xiaobo Chen, Xinyi Le, Juntong Xi
    http://arxiv.org/abs/1901.05104v1

    • [cs.CV]A Functional Representation for Graph Matching
    Fu-Dong Wang, Gui-Song Xia, Nan Xue, Yipeng Zhang, Marcello Pelillo
    http://arxiv.org/abs/1901.05179v1

    • [cs.CV]Actions Speak Louder Than (Pass)words: Passive Authentication of Smartphone Users via Deep Temporal Features
    Debayan Deb, Arun Ross, Anil K. Jain, Kwaku Prakah-Asante, K. Venkatesh Prasad
    http://arxiv.org/abs/1901.05107v1

    • [cs.CV]Attention-aware Multi-stroke Style Transfer
    Yuan Yao, Jianqiang Ren, Xuansong Xie, Weidong Liu, Yong-Jin Liu, Jun Wang
    http://arxiv.org/abs/1901.05127v1

    • [cs.CV]DAFE-FD: Density Aware Feature Enrichment for Face Detection
    Vishwanath A. Sindagi, Vishal M. Patel
    http://arxiv.org/abs/1901.05375v1

    • [cs.CV]Deep Grid Net (DGN): A Deep Learning System for Real-Time Driving Context Understanding
    Liviu Marina, Bogdan Trasnea, Cocias Tiberiu, Andrei Vasilcoi, Florin Moldoveanu, Sorin Grigorescu
    http://arxiv.org/abs/1901.05203v1

    • [cs.CV]Deep Supervised Hashing leveraging Quadratic Spherical Mutual Information for Content-based Image Retrieval
    Nikolaos Passalis, Anastasios Tefas
    http://arxiv.org/abs/1901.05135v1

    • [cs.CV]DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
    Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, Steven Lovegrove
    http://arxiv.org/abs/1901.05103v1

    • [cs.CV]Domain Adaptation for Structured Output via Discriminative Representations
    Yi-Hsuan Tsai, Kihyuk Sohn, Samuel Schulter, Manmohan Chandraker
    http://arxiv.org/abs/1901.05427v1

    • [cs.CV]Light-weighted Saliency Detection with Distinctively Lower Memory Cost and Model Size
    Shanghua Xiao
    http://arxiv.org/abs/1901.05002v1

    • [cs.CV]Lightweight Markerless Monocular Face Capture with 3D Spatial Priors
    Shridhar Ravikumar
    http://arxiv.org/abs/1901.05355v1

    • [cs.CV]MRI to CT Translation with GANs
    Bodo Kaiser, Shadi Albarqouni
    http://arxiv.org/abs/1901.05259v1

    • [cs.CV]Nonrigid reconstruction of 3D breast surfaces with a low-cost RGBD camera for surgical planning and aesthetic evaluation
    Rene Lacher, Francisco Vasconcelos, Norman Williams, Gerrit Rindermann, John Hipwell, David Hawkes, Danail Stoyanov
    http://arxiv.org/abs/1901.05377v1

    • [cs.CV]Real-world Underwater Enhancement: Challenging, Benchmark and Efficient Solutions
    Risheng Liu, Minjun Hou, Xin Fan, Zhongxuan Luo
    http://arxiv.org/abs/1901.05320v1

    • [cs.CV]Technical Report on Visual Quality Assessment for Frame Interpolation
    Hui Men, Hanhe Lin, Vlad Hosu, Daniel Maurer, Andres Bruhn, Dietmar Saupe
    http://arxiv.org/abs/1901.05362v1

    • [cs.CV]UAN: Unified Attention Network for Convolutional Neural Networks
    Tony Joseph, Konstantinos G. Derpanis, Faisal Z. Qureshi
    http://arxiv.org/abs/1901.05376v1

    • [cs.CY]Artificial Intelligence for Social Good
    Gregory D. Hager, Ann Drobnis, Fei Fang, Rayid Ghani, Amy Greenwald, Terah Lyons, David C. Parkes, Jason Schultz, Suchi Saria, Stephen F. Smith, Milind Tambe
    http://arxiv.org/abs/1901.05406v1

    • [cs.CY]Teaching Electronics and Programming in Norwegian Schools Using the air:bit Sensor Kit
    Bjørn Fjukstad, Nina Angelvik, Morten Grønnesby, Maria Wulff Hauglann, Hedinn Gunhildrud, Fredrik Høisæther Rasch, Julianne Iversen, Margaret Dalseng, Lars Ailo Bongo
    http://arxiv.org/abs/1901.05240v1

    • [cs.CY]Tracking the Digital Traces of Russian Trolls: Distinguishing the Roles and Strategy of Trolls On Twitter
    Dongwoo Kim, Timothy Graham, Zimin Wan, Marian-Andrei Rizoiu
    http://arxiv.org/abs/1901.05228v1

    • [cs.DC]Achlys : Towards a framework for distributed storage and generic computing applications for wireless IoT edge networks with Lasp on GRiSP
    Kopestenski Igor, Peter Van Roy
    http://arxiv.org/abs/1901.05030v1

    • [cs.DS]The Bayesian Prophet: A Low-Regret Framework for Online Decision Making
    Alberto Vera, Siddhartha Banerjee
    http://arxiv.org/abs/1901.05028v1

    • [cs.ET]On complexity of branching droplets in electrical field
    Mohammad Mahdi Dehshibi, Jitka Cejkova, Dominik Svara, Andrew Adamatzky
    http://arxiv.org/abs/1901.05043v1

    • [cs.IR]It's Only Words And Words Are All I Have
    Manash Pratim Barman, Kavish Dahekar, Abhinav Anshuman, Amit Awekar
    http://arxiv.org/abs/1901.05227v1

    • [cs.IR]Large-Scale Joint Topic, Sentiment & User Preference Analysis for Online Reviews
    Xinli Yu, Zheng Chen, Wei-Shih Yang, Xiaohua Hu, Erjia Yan
    http://arxiv.org/abs/1901.04993v1

    • [cs.IT]Adaptive Learning-Based Task Offloading for Vehicular Edge Computing Systems
    Yuxuan Sun, Xueying Guo, Jinhui Song, Sheng Zhou, Zhiyuan Jiang, Xin Liu, Zhisheng Niu
    http://arxiv.org/abs/1901.05205v1

    • [cs.IT]An Exponential Lower Bound on the Sub-Packetization of MSR Codes
    Omar Alrabiah, Venkatesan Guruswami
    http://arxiv.org/abs/1901.05112v1

    • [cs.IT]Asymptotic Analysis on LDPC-BICM Scheme for Compute-and-Forward Relaying
    Satoshi Takabe, Tadashi Wadayama, Masahito Hayashi
    http://arxiv.org/abs/1901.05262v1

    • [cs.IT]Channel Conditions for the Optimality of Interference Decoding Schemes for K-user Gaussian Interference Channels
    Ragini Chaluvadi, Bolli Madhuri, Srikrishna Bhashyam
    http://arxiv.org/abs/1901.05153v1

    • [cs.IT]Coded Federated Computing in Wireless Networks with Straggling Devices and Imperfect CSI
    Sukjong Ha, Jingjing Zhang, Osvaldo Simeone, Joonhyuk Kang
    http://arxiv.org/abs/1901.05239v1

    • [cs.IT]Coded Matrix Multiplication on a Group-Based Model
    Muah Kim, Jy-yong Sohn, Jaekyun Moon
    http://arxiv.org/abs/1901.05162v1

    • [cs.IT]Hybrid Beamformer Design for High Dynamic Range Ambient Backscatter Receivers
    Ruifeng Duan, Estifanos Menta, Hüseyin Yiğitler, Riku Jäntti
    http://arxiv.org/abs/1901.05323v1

    • [cs.IT]Linear complementary dual, maximum distance separable codes
    Ted Hurley
    http://arxiv.org/abs/1901.04241v2

    • [cs.IT]Low-Complexity Joint Channel Estimation and List Decoding of Short Codes
    Mustafa Cemil Coşkun, Gianluigi Liva, Johan Östman, Giuseppe Durisi
    http://arxiv.org/abs/1901.05409v1

    • [cs.IT]Relative Age of Information: A New Metric for Status Update Systems
    Peng Zou, Omur Ozel, Suresh Subramaniam
    http://arxiv.org/abs/1901.05428v1

    • [cs.IT]STORNS: Stochastic Radio Access Network Slicing
    Vincenzo Sciancalepore, Marco Di Renzo, Xavier Costa-Perez
    http://arxiv.org/abs/1901.05336v1

    • [cs.IT]Status from a Random Field: How Densely Should One Update?
    Zhiyuan Jiang, Sheng Zhou
    http://arxiv.org/abs/1901.05096v1

    • [cs.IT]Using auto-encoders for solving ill-posed linear inverse problems
    Shirin Jalali, Xin Yuan
    http://arxiv.org/abs/1901.05045v1

    • [cs.IT]Utility Regions for DF Relay in OFDMA-based Secure Communication with Untrusted Users
    Ravikant Saini, Deepak Mishra, Swades De
    http://arxiv.org/abs/1901.05177v1

    • [cs.LG]A review of single-source unsupervised domain adaptation
    Wouter M. Kouw, Marco Loog
    http://arxiv.org/abs/1901.05335v1

    • [cs.LG]AI Pipeline - bringing AI to you. End-to-end integration of data, algorithms and deployment tools
    Miguel de Prado, Jing Su, Rozenn Dahyot, Rabia Saeed, Lorenzo Keller, Noelia Vallez
    http://arxiv.org/abs/1901.05049v1

    • [cs.LG]CFOF: A Concentration Free Measure for Anomaly Detection
    Fabrizio Angiulli
    http://arxiv.org/abs/1901.04992v1

    • [cs.LG]MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks
    Dan Li, Dacheng Chen, Lei Shi, Baihong Jin, Jonathan Goh, See-Kiong Ng
    http://arxiv.org/abs/1901.04997v1

    • [cs.LG]Memory Augmented Deep Generative models for Forecasting the Next Shot Location in Tennis
    Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes
    http://arxiv.org/abs/1901.05123v1

    • [cs.LG]ReNeg and Backseat Driver: Learning from Demonstration with Continuous Human Feedback
    Jacob Beck, Zoe Papakipos, Michael Littman
    http://arxiv.org/abs/1901.05101v1

    • [cs.LG]Representation Learning on Graphs: A Reinforcement Learning Application
    Sephora Madjiheurem, Laura Toni
    http://arxiv.org/abs/1901.05351v1

    • [cs.LG]TensorFlow.js: Machine Learning for the Web and Beyond
    Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viegas, Martin Wattenberg
    http://arxiv.org/abs/1901.05350v1

    • [cs.NE]The Discrete Langevin Machine: Bridging the Gap Between Thermodynamic and Neuromorphic Systems
    Lukas Kades, Jan M. Pawlowski
    http://arxiv.org/abs/1901.05214v1

    • [cs.PL]Predicting Variable Types in Dynamically Typed Programming Languages
    Abhinav Jangda, Gaurav Anand
    http://arxiv.org/abs/1901.05138v1

    • [cs.RO]GridSim: A Vehicle Kinematics Engine for Deep Neuroevolutionary Control in Autonomous Driving
    Bogdan Trasnea, Andrei Vasilcoi, Claudiu Pozna, Sorin Grigorescu
    http://arxiv.org/abs/1901.05195v1

    • [cs.RO]Timely Negotiation and Correction of Shared Intentions With Body Motion
    Raphael Deimel
    http://arxiv.org/abs/1901.05256v1

    • [cs.RO]Uncertainty-Aware Driver Trajectory Prediction at Urban Intersections
    Xin Huang, Stephen McGill, Brian C. Williams, Luke Fletcher, Guy Rosman
    http://arxiv.org/abs/1901.05105v1

    • [cs.SD]Spectrogram Feature Losses for Music Source Separation
    Abhimanyu Sahai, Romann Weber, Brian McWilliams
    http://arxiv.org/abs/1901.05061v1

    • [cs.SI]Beyond Uniform Reverse Sampling: A Hybrid Sampling Technique for Misinformation Prevention
    Gunagmo Tong, Ding-Zhu Du
    http://arxiv.org/abs/1901.05149v1

    • [cs.SI]Location, Occupation, and Semantics based Socioeconomic Status Inference on Twitter
    Jacobo Levy Abitbol, Márton Karsai, Eric Fleury
    http://arxiv.org/abs/1901.05389v1

    • [cs.SI]Weighted Label Propagation Algorithm based on Local Edge Betweenness
    Hamid Shahrivari Joghan, Alireza Bagheri, Meysam Azad
    http://arxiv.org/abs/1901.05359v1

    • [eess.SP]Seizure Detection using Least EEG Channels by Deep Convolutional Neural Network
    Mustafa Talha Avcu, Zhuo Zhang, Derrick Wei Shih Chan
    http://arxiv.org/abs/1901.05305v1

    • [hep-ex]LHC analysis-specific datasets with Generative Adversarial Networks
    Bobak Hashemi, Nick Amin, Kaustuv Datta, Dominick Olivito, Maurizio Pierini
    http://arxiv.org/abs/1901.05282v1

    • [math.NA]Algorithms for \ell_p-based semi-supervised learning on graphs
    Mauricio Flores Rios, Jeff Calder, Gilad Lerman
    http://arxiv.org/abs/1901.05031v1

    • [math.OC]DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
    Rixon Crane, Fred Roosta
    http://arxiv.org/abs/1901.05134v1

    • [math.OC]Optimization Models for Machine Learning: A Survey
    Claudio Gambella, Bissan Ghaddar, Joe Naoum-Sawaya
    http://arxiv.org/abs/1901.05331v1

    • [math.ST]Bayesian sequential least-squares estimation for the drift of a Wiener process
    Erik Ekström, Ioannis Karatzas, Juozas Vaicenavicius
    http://arxiv.org/abs/1901.05410v1

    • [math.ST]Joint temporal and contemporaneous aggregation of random-coefficient AR(1) processes with infinite variance
    Vytautė Pilipauskaitė, Viktor Skorniakov, Donatas Surgailis
    http://arxiv.org/abs/1901.05380v1

    • [math.ST]On posterior contraction of parameters and interpretability in Bayesian mixture modeling
    Aritra Guha, Nhat Ho, XuanLong Nguyen
    http://arxiv.org/abs/1901.05078v1

    • [math.ST]The median of a jittered Poisson distribution
    Jean-François Coeurjolly, Joëlle Rousseau-Trépanier
    http://arxiv.org/abs/1901.05367v1

    • [math.ST]Tracy-Widom limit for the largest eigenvalue of high-dimensional covariance matrices in elliptical distributions
    Jun Wen, Wang Zhou
    http://arxiv.org/abs/1901.05166v1

    • [physics.ed-ph]Using CoCalc as a Training Tool for Mathematics Teachers Pre-Service Training
    Maiia Popel
    http://arxiv.org/abs/1901.05139v1

    • [physics.soc-ph]On the frequency and severity of interstate wars
    Aaron Clauset
    http://arxiv.org/abs/1901.05086v1

    • [q-bio.GN]Determining Multifunctional Genes and Diseases in Human Using Gene Ontology
    Hisham Al-Mubaid, Sasikanth Potu, M. Shenify
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    • [q-bio.PE]On a family of stochastic SVIR influenza epidemic models and maximum likelihood estimation
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    • [stat.AP]Improving linear quantile regression for replicated data
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    • [stat.AP]Novel metrics for quantifying the capacity of subgroup-defining variables to yield efficient treatment rules
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    • [stat.ME]A Note on the Estimation Method of Intervention Effects based on Statistical Decision Theory
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    • [stat.ME]A nonparametric super-efficient estimator of the average treatment effect
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    • [stat.ME]Learning Temporal Evolution of Spatial Dependence with Generalized Spatiotemporal Gaussian Process Models
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    • [stat.ME]On the Estimation of Population Size from a Dependent Triple Record System
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    • [stat.ME]Smooth Adjustment for Correlated Effects
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    • [stat.ME]Two-stage Circular-circular Regression with Rounding Error: An Application to Cataract Surgery Data
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    • [stat.ML]A Primer on PAC-Bayesian Learning
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    • [stat.ML]Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques
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    • [stat.ML]The Winning Solution to the IEEE CIG 2017 Game Data Mining Competition
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          本文标题:今日学术视野(2019.1.18)

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