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今日学术视野(2019.3.14)

今日学术视野(2019.3.14)

作者: ZQtGe6 | 来源:发表于2019-03-14 05:09 被阅读133次

    astro-ph.SR - 太阳和天体物理学恒星
    cs.AI - 人工智能
    cs.AR - 硬件体系结构
    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.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    cs.NE - 神经与进化计算
    cs.RO - 机器人学
    cs.SD - 声音处理
    cs.SI - 社交网络与信息网络
    cs.SY - 系统与控制
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    math.CO - 组合数学
    math.NA - 数值分析
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    physics.soc-ph - 物理学与社会
    q-bio.GN - 基因组学
    q-fin.PM - 投资组合管理
    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

    • [astro-ph.SR]A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Mission
    • [cs.AI]Generating and Sampling Orbits for Lifted Probabilistic Inference
    • [cs.AI]Interaction Embeddings for Prediction and Explanation in Knowledge Graphs
    • [cs.AI]Iterated two-phase local search for the Set-Union Knapsack Problem
    • [cs.AR]Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect
    • [cs.CL]Character Eyes: Seeing Language through Character-Level Taggers
    • [cs.CL]Context-Aware Learning for Neural Machine Translation
    • [cs.CL]Few-Shot and Zero-Shot Learning for Historical Text Normalization
    • [cs.CL]Partially Shuffling the Training Data to Improve Language Models
    • [cs.CL]Practical Semantic Parsing for Spoken Language Understanding
    • [cs.CL]Syllable-based Neural Named Entity Recognition for Myanmar Language
    • [cs.CL]The Truth and Nothing but the Truth: Multimodal Analysis for Deception Detection
    • [cs.CR]Supervised Machine Learning Techniques for Trojan Detection with Ring Oscillator Network
    • [cs.CV]A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images
    • [cs.CV]An End-to-End Network for Panoptic Segmentation
    • [cs.CV]Cascaded Projection: End-to-End Network Compression and Acceleration
    • [cs.CV]Deep Learning for Automated Medical Image Analysis
    • [cs.CV]Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image
    • [cs.CV]Dense Classification and Implanting for Few-Shot Learning
    • [cs.CV]Discriminative Principal Component Analysis: A REVERSE THINKING
    • [cs.CV]Fast Registration for cross-source point clouds by using weak regional affinity and pixel-wise refinement
    • [cs.CV]GOGGLES: Automatic Training Data Generation with Affinity Coding
    • [cs.CV]Generating superpixels using deep image representations
    • [cs.CV]Image Classification base on PCA of Multi-view Deep Representation
    • [cs.CV]Knowledge Adaptation for Efficient Semantic Segmentation
    • [cs.CV]MTRNet: A Generic Scene Text Eraser
    • [cs.CV]Occlusion-guided compact template learning for ensemble deep network-based pose-invariant face recognition
    • [cs.CV]Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar
    • [cs.CV]Parallel Medical Imaging: A New Data-Knowledge-Driven Evolutionary Framework for Medical Image Analysis
    • [cs.CV]Placental Flattening via Volumetric Parameterization
    • [cs.CV]Quality-Gated Convolutional LSTM for Enhancing compressed video
    • [cs.CV]Semi-Supervised Self-Taught Deep Learning for Finger Bones Segmentation
    • [cs.CV]Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes
    • [cs.CV]Structured Knowledge Distillation for Semantic Segmentation
    • [cs.CV]The Unconstrained Ear Recognition Challenge 2019 - ArXiv version With Appendix
    • [cs.CV]Transfer Adaptation Learning: A Decade Survey
    • [cs.CV]Unsupervised motion saliency map estimation based on optical flow inpainting
    • [cs.CY]Analysis of the use of smart cards on the urban railway
    • [cs.DC]Analyzing the Impact of GDPR on Storage Systems
    • [cs.DC]Decentralized Smart Surveillance through Microservices Platform
    • [cs.DC]Service Capacity Enhanced Task Offloading and Resource Allocation in Multi-Server Edge Computing Environment
    • [cs.IR]Challenges in Search on Streaming Services: Netflix Case Study
    • [cs.IR]Extracting localized information from a Twitter corpus for flood prevention
    • [cs.IR]SPMF: A Social Trust and Preference Segmentation-based Matrix Factorization Recommendation Algorithm
    • [cs.IT]Age of Information in a Multiple Access Channel with Heterogeneous Traffic and an Energy Harvesting Node
    • [cs.IT]Artificial Intelligence-aided Receiver for A CP-Free OFDM System: Design, Simulation, and Experimental Test
    • [cs.IT]Bit-Interleaved Coded Multiple Beamforming in Millimeter-Wave Massive MIMO Systems
    • [cs.IT]Two-Timescale Hybrid Compression and Forward for Massive MIMO Aided C-RAN
    • [cs.LG]Activation Analysis of a Byte-Based Deep Neural Network for Malware Classification
    • [cs.LG]Application of Duration-of-Stay Storage Assignment with Deep Neural Networks under Uncertainty
    • [cs.LG]Communication-efficient distributed SGD with Sketching
    • [cs.LG]Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay
    • [cs.LG]Deep Log-Likelihood Ratio Quantization
    • [cs.LG]Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces
    • [cs.LG]Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures
    • [cs.LG]Embarrassingly parallel MCMC using deep invertible transformations
    • [cs.LG]Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks
    • [cs.LG]Generating Compact Geometric Track-Maps for Train Positioning Applications
    • [cs.LG]Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems
    • [cs.LG]Imitation Learning of Factored Multi-agent Reactive Models
    • [cs.LG]Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning
    • [cs.LG]Learning Condensed and Aligned Features for Unsupervised Domain Adaptation Using Label Propagation
    • [cs.LG]Learning Edge Properties in Graphs from Path Aggregations
    • [cs.LG]Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control
    • [cs.LG]Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
    • [cs.LG]Online Human Activity Recognition Employing Hierarchical Hidden Markov Models
    • [cs.LG]Open-Set Recognition Using Intra-Class Splitting
    • [cs.LG]Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning
    • [cs.LG]Tensor Grid Decomposition with Application to Tensor Completion
    • [cs.LG]Theory III: Dynamics and Generalization in Deep Networks
    • [cs.LO]Probabilistic Temporal Logic over Finite Traces (Technical Report)
    • [cs.NE]Efficient Optimization of Echo State Networks for Time Series Datasets
    • [cs.NE]NeuroCore: Guiding CDCL with Unsat-Core Predictions
    • [cs.RO]An Open-Source 7-Axis, Robotic Platform to Enable Dexterous Procedures within CT Scanners
    • [cs.RO]Blackbox End-to-End Verification of Ground Robot Safety and Liveness
    • [cs.RO]Goal-Directed Behavior under Variational Predictive Coding: Dynamic Organization of Visual Attention and Working Memory
    • [cs.RO]Information correlated Lévy walk exploration and distributed mapping using a swarm of robots
    • [cs.RO]Proceedings of the Fifth International Conference on Cloud and Robotics (ICCR2018)
    • [cs.RO]Recognizing and Tracking High-Level, Human-Meaningful Navigation Features of Occupancy Grid Maps
    • [cs.RO]Resilience by Reconfiguration: Exploiting Heterogeneity in Robot Teams
    • [cs.RO]Siamese Convolutional Neural Network for Sub-millimeter-accurate Camera Pose Estimation and Visual Servoing
    • [cs.RO]Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotors
    • [cs.RO]UAV/UGV Autonomous Cooperation: UAV Assists UGV to Climb a Cliff by Attaching a Tether
    • [cs.SD]Progressive Generative Adversarial Binary Networks for Music Generation
    • [cs.SI]Characterization of Local Attitudes Toward Immigration Using Social Media
    • [cs.SI]What sets Verified Users apart? Insights, Analysis and Prediction of Verified Users on Twitter
    • [cs.SY]Control Barrier Functions for Systems with High Relative Degree
    • [cs.SY]Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs
    • [eess.AS]Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling
    • [eess.IV]AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks
    • [eess.SP]Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks
    • [eess.SP]Satellite Based IoT for MC Applications
    • [math.CO]The Iterated Local Model for Social Networks
    • [math.NA]A total variation based regularizer promoting piecewise-Lipschitz reconstructions
    • [math.OC]Accelerated Learning in the Presence of Time Varying Features with Applications to Machine Learning and Adaptive Control
    • [math.OC]An Efficient Augmented Lagrangian Based Method for Constrained Lasso
    • [math.PR]Calibrating dependence between random elements
    • [math.PR]The Inverse first passage time method for a two compartment model as a tool to relate Inverse Gaussian and Gamma spike distributions
    • [math.ST]ECKO: Ensemble of Clustered Knockoffs for multivariate inference on fMRI data
    • [math.ST]The All-or-Nothing Phenomenon in Sparse Linear Regression
    • [math.ST]The limits of distribution-free conditional predictive inference
    • [physics.soc-ph]A subset selection based approach to finding important structure of complex networks
    • [q-bio.GN]conLSH: Context based Locality Sensitive Hashing for Mapping of noisy SMRT Reads
    • [q-fin.PM]Financial Applications of Gaussian Processes and Bayesian Optimization
    • [stat.AP]Analysis of the AOK Lower Saxony hospitalisation records data (years 2008 -- 2015)
    • [stat.AP]The conditionally autoregressive hidden Markov model (CarHMM): Inferring behavioural states from animal tracking data exhibiting conditional autocorrelation
    • [stat.CO]ROC and AUC with a Binary Predictor: a Potentially Misleading Metric
    • [stat.ME]Causal organic direct and indirect effects: closer to Baron and Kenny
    • [stat.ME]Discrete factor analysis
    • [stat.ME]Flexible Clustering with a Sparse Mixture of Generalized Hyperbolic Distributions
    • [stat.ME]Generalized Sparse Additive Models
    • [stat.ME]Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction
    • [stat.ML]Elements of Sequential Monte Carlo
    • [stat.ML]Imputation estimators for unnormalized models with missing data
    • [stat.ML]Testing Conditional Independence on Discrete Data using Stochastic Complexity
    • [stat.ML]Wavelet regression and additive models for irregularly spaced data

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

    • [astro-ph.SR]A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Mission
    Richard Galvez, David F. Fouhey, Meng Jin, Alexandre Szenicer, Andrés Muñoz-Jaramillo, Mark C. M. Cheung, Paul J. Wright, Monica G. Bobra, Yang Liu, James Mason, Rajat Thomas
    http://arxiv.org/abs/1903.04538v1

    • [cs.AI]Generating and Sampling Orbits for Lifted Probabilistic Inference
    Steven Holtzen, Todd Millstein, Guy Van den Broeck
    http://arxiv.org/abs/1903.04672v1

    • [cs.AI]Interaction Embeddings for Prediction and Explanation in Knowledge Graphs
    Wen Zhang, Bibek Paudel, Wei Zhang, Abraham Bernstein, Huajun Chen
    http://arxiv.org/abs/1903.04750v1

    • [cs.AI]Iterated two-phase local search for the Set-Union Knapsack Problem
    Zequn Wei, Jin-Kao Hao
    http://arxiv.org/abs/1903.04966v1

    • [cs.AR]Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect
    Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan Tallent, Kevin Barker
    http://arxiv.org/abs/1903.04611v1

    • [cs.CL]Character Eyes: Seeing Language through Character-Level Taggers
    Yuval Pinter, Marc Marone, Jacob Eisenstein
    http://arxiv.org/abs/1903.05041v1

    • [cs.CL]Context-Aware Learning for Neural Machine Translation
    Sébastien Jean, Kyunghyun Cho
    http://arxiv.org/abs/1903.04715v1

    • [cs.CL]Few-Shot and Zero-Shot Learning for Historical Text Normalization
    Marcel Bollmann, Natalia Korchagina, Anders Søgaard
    http://arxiv.org/abs/1903.04870v1

    • [cs.CL]Partially Shuffling the Training Data to Improve Language Models
    Ofir Press
    http://arxiv.org/abs/1903.04167v2

    • [cs.CL]Practical Semantic Parsing for Spoken Language Understanding
    Marco Damonte, Rahul Goel, Tagyoung Chung
    http://arxiv.org/abs/1903.04521v1

    • [cs.CL]Syllable-based Neural Named Entity Recognition for Myanmar Language
    Hsu Myat Mo, Khin Mar Soe
    http://arxiv.org/abs/1903.04739v1

    • [cs.CL]The Truth and Nothing but the Truth: Multimodal Analysis for Deception Detection
    Mimansa Jaiswal, Sairam Tabibu, Rajiv Bajpai
    http://arxiv.org/abs/1903.04484v1

    • [cs.CR]Supervised Machine Learning Techniques for Trojan Detection with Ring Oscillator Network
    Kyle Worley, Md Tauhidur Rahman
    http://arxiv.org/abs/1903.04677v1

    • [cs.CV]A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images
    Jiapeng Tang, Xiaoguang Han, Junyi Pan, Kui Jia, Xin Tong
    http://arxiv.org/abs/1903.04704v1

    • [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/1903.05027v1

    • [cs.CV]Cascaded Projection: End-to-End Network Compression and Acceleration
    Breton Minnehan, Andreas Savakis
    http://arxiv.org/abs/1903.04988v1

    • [cs.CV]Deep Learning for Automated Medical Image Analysis
    Wentao Zhu
    http://arxiv.org/abs/1903.04711v1

    • [cs.CV]Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image
    Xiaoguang Han, Zhaoxuan Zhang, Dong Du, Mingdai Yang, Jingming Yu, Pan Pan, Xin Yang, Ligang Liu, Zixiang Xiong, Shuguang Cui
    http://arxiv.org/abs/1903.04019v2

    • [cs.CV]Dense Classification and Implanting for Few-Shot Learning
    Yann Lifchitz, Yannis Avrithis, Sylvaine Picard, Andrei Bursuc
    http://arxiv.org/abs/1903.05050v1

    • [cs.CV]Discriminative Principal Component Analysis: A REVERSE THINKING
    Hanli Qiao
    http://arxiv.org/abs/1903.04963v1

    • [cs.CV]Fast Registration for cross-source point clouds by using weak regional affinity and pixel-wise refinement
    Xiaoshui Huang, Lixin Fan, Qiang Wu, Jian Zhang, Chun Yuan
    http://arxiv.org/abs/1903.04630v1

    • [cs.CV]GOGGLES: Automatic Training Data Generation with Affinity Coding
    Nilaksh Das, Sanya Chaba, Sakshi Gandhi, Duen Horng Chau, Xu Chu
    http://arxiv.org/abs/1903.04552v1

    • [cs.CV]Generating superpixels using deep image representations
    Thomas Verelst, Matthew Blaschko, Maxim Berman
    http://arxiv.org/abs/1903.04586v1

    • [cs.CV]Image Classification base on PCA of Multi-view Deep Representation
    Yaoqi Sun, Liang Li, Liang Zheng, Ji Hu, Yatong Jiang, Chenggang Yan
    http://arxiv.org/abs/1903.04814v1

    • [cs.CV]Knowledge Adaptation for Efficient Semantic Segmentation
    Tong He, Chunhua Shen, Zhi Tian, Dong Gong, Changming Sun, Youliang Yan
    http://arxiv.org/abs/1903.04688v1

    • [cs.CV]MTRNet: A Generic Scene Text Eraser
    Osman Tursun, Rui Zeng, Simon Denman, Sabesan Sivipalan, Sridha Sridharan, Clinton Fookes
    http://arxiv.org/abs/1903.04092v2

    • [cs.CV]Occlusion-guided compact template learning for ensemble deep network-based pose-invariant face recognition
    Yuhang Wu, Ioannis A. Kakadiaris
    http://arxiv.org/abs/1903.04752v1

    • [cs.CV]Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar
    Arash Akbarinia, Karl R. Gegenfurtner
    http://arxiv.org/abs/1903.04772v1

    • [cs.CV]Parallel Medical Imaging: A New Data-Knowledge-Driven Evolutionary Framework for Medical Image Analysis
    Chao Gou, Tianyu Shen, Wenbo Zheng, Oliver Kwan, Fei-Yue Wang
    http://arxiv.org/abs/1903.04855v1

    • [cs.CV]Placental Flattening via Volumetric Parameterization
    S. Mazdak Abulnaga, Esra Abaci Turk, Mikhail Bessmeltsev, P. Ellen Grant, Justin Solomon, Polina Golland
    http://arxiv.org/abs/1903.05044v1

    • [cs.CV]Quality-Gated Convolutional LSTM for Enhancing compressed video
    Ren Yang, Xiaoyan Sun, Mai Xu, Wenjun Zeng
    http://arxiv.org/abs/1903.04596v1

    • [cs.CV]Semi-Supervised Self-Taught Deep Learning for Finger Bones Segmentation
    Ziyuan Zhao, Xiaoman Zhang, Cen Chen, Wei Li, Songyou Peng, Jie Wang, Xulei Yang, Le Zhang, Zeng Zeng
    http://arxiv.org/abs/1903.04778v1

    • [cs.CV]Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes
    Xiaogang Wang, Bin Zhou, Yahao Shi, Xiaowu Chen, Qinping Zhao, Kai Xu
    http://arxiv.org/abs/1903.03911v2

    • [cs.CV]Structured Knowledge Distillation for Semantic Segmentation
    Yifan Liu, Ke Chen, Chris Liu, Zengchang Qin, Zhenbo Luo, Jingdong Wang
    http://arxiv.org/abs/1903.04197v2

    • [cs.CV]The Unconstrained Ear Recognition Challenge 2019 - ArXiv version With Appendix
    Žiga Emeršič, Aruna Kumar S. V., B. S. Harish, Weronika Gutfeter, Jalil Nourmohammadi Khiarak, Andrzej Pacut, Earnest Hansley, Mauricio Pamplona Segundo, Sudeep Sarkar, Hyeonjung Park, Gi Pyo Nam, Ig-Jae Kim, Sagar G. Sangodkar, Ümit Kaçar, Murvet Kirci, Li Yuan, Jishou Yuan, Haonan Zhao, Fei Lu, Junying Mao, Xiaoshuang Zhang, Dogucan Yaman, Fevziye Irem Eyiokur, Kadir Bulut Özler, Hazım Kemal Ekenel, Debbrota Paul Chowdhury, Sambit Bakshi, Banshidhar Majhi, Peter Peer, Vitomir Štruc
    http://arxiv.org/abs/1903.04143v2

    • [cs.CV]Transfer Adaptation Learning: A Decade Survey
    Lei Zhang
    http://arxiv.org/abs/1903.04687v1

    • [cs.CV]Unsupervised motion saliency map estimation based on optical flow inpainting
    L. Maczyta, P. Bouthemy, O. Le Meur
    http://arxiv.org/abs/1903.04842v1

    • [cs.CY]Analysis of the use of smart cards on the urban railway
    Dmitry Namiot, Oleg Pokusaev, Vasily Kupriyanovsky
    http://arxiv.org/abs/1903.03851v1

    • [cs.DC]Analyzing the Impact of GDPR on Storage Systems
    Vinay Banakar, Aashaka Shah, Supreeth Shastri, Melissa Wasserman, Vijay Chidambaram
    http://arxiv.org/abs/1903.04880v1

    • [cs.DC]Decentralized Smart Surveillance through Microservices Platform
    Seyed Yahya Nikouei, Ronghua Xu, Yu Chen, Alex Aved, Erik Blasch
    http://arxiv.org/abs/1903.04563v1

    • [cs.DC]Service Capacity Enhanced Task Offloading and Resource Allocation in Multi-Server Edge Computing Environment
    Wei Du, Tao Lei, Qiang He, Wei Liu, Qiwang Lei, Hailiang Zhao, Wei Wang
    http://arxiv.org/abs/1903.04709v1

    • [cs.IR]Challenges in Search on Streaming Services: Netflix Case Study
    Sudarshan Lamkhede, Sudeep Das
    http://arxiv.org/abs/1903.04638v1

    • [cs.IR]Extracting localized information from a Twitter corpus for flood prevention
    Etienne Brangbour, Pierrick Bruneau, Stéphane Marchand-Maillet, Renaud Hostache, Patrick Matgen, Marco Chini, Thomas Tamisier
    http://arxiv.org/abs/1903.04748v1

    • [cs.IR]SPMF: A Social Trust and Preference Segmentation-based Matrix Factorization Recommendation Algorithm
    Wei Peng, Baogui Xin
    http://arxiv.org/abs/1903.04489v1

    • [cs.IT]Age of Information in a Multiple Access Channel with Heterogeneous Traffic and an Energy Harvesting Node
    Zheng Chen, Nikolaos Pappas, Emil Björnson, Erik G. Larsson
    http://arxiv.org/abs/1903.05066v1

    • [cs.IT]Artificial Intelligence-aided Receiver for A CP-Free OFDM System: Design, Simulation, and Experimental Test
    Jing Zhang, Chao-Kai Wen, Shi Jin, Geoffrey Ye Li
    http://arxiv.org/abs/1903.04766v1

    • [cs.IT]Bit-Interleaved Coded Multiple Beamforming in Millimeter-Wave Massive MIMO Systems
    Sadjad Sedighi, Ender Ayanoglu
    http://arxiv.org/abs/1903.04693v1

    • [cs.IT]Two-Timescale Hybrid Compression and Forward for Massive MIMO Aided C-RAN
    An Liu, Xihan Chen, Wei Yu, Vincent Lau, Min-Jian Zhao
    http://arxiv.org/abs/1903.04692v1

    • [cs.LG]Activation Analysis of a Byte-Based Deep Neural Network for Malware Classification
    Scott E. Coull, Christopher Gardner
    http://arxiv.org/abs/1903.04717v1

    • [cs.LG]Application of Duration-of-Stay Storage Assignment with Deep Neural Networks under Uncertainty
    Michael Lingzhi Li, Elliott Wolf, Daniel Wintz
    http://arxiv.org/abs/1903.05063v1

    • [cs.LG]Communication-efficient distributed SGD with Sketching
    Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora
    http://arxiv.org/abs/1903.04488v1

    • [cs.LG]Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay
    Mohammad Rostami, Soheil Kolouri, Praveen K. Pilly
    http://arxiv.org/abs/1903.04566v1

    • [cs.LG]Deep Log-Likelihood Ratio Quantization
    Marius Arvinte, Ahmed H. Tewfik, Sriram Vishwanath
    http://arxiv.org/abs/1903.04656v1

    • [cs.LG]Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces
    Haotian Fu, Hongyao Tang, Jianye Hao, Zihan Lei, Yingfeng Chen, Changjie Fan
    http://arxiv.org/abs/1903.04959v1

    • [cs.LG]Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures
    Guy Shtar, Lior Rokach, Bracha Shapira
    http://arxiv.org/abs/1903.04571v1

    • [cs.LG]Embarrassingly parallel MCMC using deep invertible transformations
    Diego Mesquita, Paul Blomstedt, Samuel Kaski
    http://arxiv.org/abs/1903.04556v1

    • [cs.LG]Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks
    Omer Berat Sezer, Ahmet Murat Ozbayoglu
    http://arxiv.org/abs/1903.04610v1

    • [cs.LG]Generating Compact Geometric Track-Maps for Train Positioning Applications
    Hanno Winter, Stefan Luthardt, Volker Willert, Jürgen Adamy
    http://arxiv.org/abs/1903.05014v1

    • [cs.LG]Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems
    Henrique Lemos, Marcelo Prates, Pedro Avelar, Luis Lamb
    http://arxiv.org/abs/1903.04598v1

    • [cs.LG]Imitation Learning of Factored Multi-agent Reactive Models
    Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood
    http://arxiv.org/abs/1903.04714v1

    • [cs.LG]Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning
    Xiaobai Ma, Katherine Driggs-Campbell, Mykel J. Kochenderfer
    http://arxiv.org/abs/1903.03642v1

    • [cs.LG]Learning Condensed and Aligned Features for Unsupervised Domain Adaptation Using Label Propagation
    Jaeyoon Yoo, Changhwa Park, Yongjun Hong, Sungroh Yoon
    http://arxiv.org/abs/1903.04860v1

    • [cs.LG]Learning Edge Properties in Graphs from Path Aggregations
    Rakshit Agrawal, Luca de Alfaro
    http://arxiv.org/abs/1903.04613v1

    • [cs.LG]Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control
    Tianshu Chu, Jie Wang, Lara Codecà, Zhaojian Li
    http://arxiv.org/abs/1903.04527v1

    • [cs.LG]Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
    Daniel Borkan, Lucas Dixon, Jeffrey Sorensen, Nithum Thain, Lucy Vasserman
    http://arxiv.org/abs/1903.04561v1

    • [cs.LG]Online Human Activity Recognition Employing Hierarchical Hidden Markov Models
    Parviz Asghari, Elnaz Soelimani, Ehsan Nazerfard
    http://arxiv.org/abs/1903.04820v1

    • [cs.LG]Open-Set Recognition Using Intra-Class Splitting
    Patrick Schlachter, Yiwen Liao, Bin Yang
    http://arxiv.org/abs/1903.04774v1

    • [cs.LG]Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning
    Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier, Andrew Gordon Wilson
    http://arxiv.org/abs/1903.04703v1

    • [cs.LG]Tensor Grid Decomposition with Application to Tensor Completion
    Huyan Huang, Yipeng Liu, Ce Zhu
    http://arxiv.org/abs/1903.04735v1

    • [cs.LG]Theory III: Dynamics and Generalization in Deep Networks
    Andrzej Banburski, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Bob Liang, Jack Hidary, Tomaso Poggio
    http://arxiv.org/abs/1903.04991v1

    • [cs.LO]Probabilistic Temporal Logic over Finite Traces (Technical Report)
    Fabrizio M. Maggi, Marco Montali, Rafael Peñaloza
    http://arxiv.org/abs/1903.04940v1

    • [cs.NE]Efficient Optimization of Echo State Networks for Time Series Datasets
    Jacob Reinier Maat, Nikos Gianniotis, Pavlos Protopapas
    http://arxiv.org/abs/1903.05071v1

    • [cs.NE]NeuroCore: Guiding CDCL with Unsat-Core Predictions
    Daniel Selsam, Nikolaj Bjørner
    http://arxiv.org/abs/1903.04671v1

    • [cs.RO]An Open-Source 7-Axis, Robotic Platform to Enable Dexterous Procedures within CT Scanners
    Dimitri A. Schreiber, Daniel B. Shak, Alexander M. Norbash, Michael C. Yip
    http://arxiv.org/abs/1903.04646v1

    • [cs.RO]Blackbox End-to-End Verification of Ground Robot Safety and Liveness
    Brandon Bohrer, Yong Kiam Tan, Stefan Mitsch, Andrew Sogokon, André Platzer
    http://arxiv.org/abs/1903.05073v1

    • [cs.RO]Goal-Directed Behavior under Variational Predictive Coding: Dynamic Organization of Visual Attention and Working Memory
    Minju Jung, Takazumi Matsumoto, Jun Tani
    http://arxiv.org/abs/1903.04932v1

    • [cs.RO]Information correlated Lévy walk exploration and distributed mapping using a swarm of robots
    Ragesh K. Ramachandran, Zahi Kakish, Spring Berman
    http://arxiv.org/abs/1903.04836v1

    • [cs.RO]Proceedings of the Fifth International Conference on Cloud and Robotics (ICCR2018)
    Huaxi, Zhang, Jacques Malenfant
    http://arxiv.org/abs/1903.04824v1

    • [cs.RO]Recognizing and Tracking High-Level, Human-Meaningful Navigation Features of Occupancy Grid Maps
    Payam Nikdel, Richard Vaughan
    http://arxiv.org/abs/1903.03669v1

    • [cs.RO]Resilience by Reconfiguration: Exploiting Heterogeneity in Robot Teams
    Ragesh K. Ramachandran, James A. Preiss, Gaurav S. Sukhatme
    http://arxiv.org/abs/1903.04856v1

    • [cs.RO]Siamese Convolutional Neural Network for Sub-millimeter-accurate Camera Pose Estimation and Visual Servoing
    Cunjun Yu, Zhongang Cai, Hung Pham, Quang-Cuong Pham
    http://arxiv.org/abs/1903.04713v1

    • [cs.RO]Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotors
    Artem Molchanov, Tao Chen, Wolfgang Hönig, James A. Preiss, Nora Ayanian, Gaurav S. Sukhatme
    http://arxiv.org/abs/1903.04628v1

    • [cs.RO]UAV/UGV Autonomous Cooperation: UAV Assists UGV to Climb a Cliff by Attaching a Tether
    Takahiro Miki, Petr Khrapchenkov, Koichi Hori
    http://arxiv.org/abs/1903.04898v1

    • [cs.SD]Progressive Generative Adversarial Binary Networks for Music Generation
    Manan Oza, Himanshu Vaghela, Kriti Srivastava
    http://arxiv.org/abs/1903.04722v1

    • [cs.SI]Characterization of Local Attitudes Toward Immigration Using Social Media
    Yerka Freire, Eduardo Graells-Garrido
    http://arxiv.org/abs/1903.05072v1

    • [cs.SI]What sets Verified Users apart? Insights, Analysis and Prediction of Verified Users on Twitter
    Indraneil Paul, Abhinav Khattar, Shaan Chopra, Ponnurangam Kumaraguru, Manish Gupta
    http://arxiv.org/abs/1903.04879v1

    • [cs.SY]Control Barrier Functions for Systems with High Relative Degree
    Wei Xiao, Calin Belta
    http://arxiv.org/abs/1903.04706v1

    • [cs.SY]Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs
    Wei Ma, Xidong Pi, Sean Qian
    http://arxiv.org/abs/1903.04681v1

    • [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/1903.04567v1

    • [eess.IV]AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks
    Ian Colbert, Ken Kreutz-Delgado, Srinjoy Das
    http://arxiv.org/abs/1903.04659v1

    • [eess.SP]Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks
    Ian A. D. Williamson, Tyler W. Hughes, Momchil Minkov, Ben Bartlett, Sunil Pai, Shanhui Fan
    http://arxiv.org/abs/1903.04579v1

    • [eess.SP]Satellite Based IoT for MC Applications
    Sudhir Routray, Abhishek Javali, Laxmi Sharma, Richa Tengshe, Sutapa Sarkar, Aritri Ghosh
    http://arxiv.org/abs/1903.04844v1

    • [math.CO]The Iterated Local Model for Social Networks
    Anthony Bonato, Huda Chuangpishit, Sean English, Bill Kay, Erin Meger
    http://arxiv.org/abs/1903.04523v1

    • [math.NA]A total variation based regularizer promoting piecewise-Lipschitz reconstructions
    Martin Burger, Yury Korolev, Carola-Bibiane Schönlieb, Christiane Stollenwerk
    http://arxiv.org/abs/1903.05079v1

    • [math.OC]Accelerated Learning in the Presence of Time Varying Features with Applications to Machine Learning and Adaptive Control
    Joseph E. Gaudio, Travis E. Gibson, Anuradha M. Annaswamy, Michael A. Bolender
    http://arxiv.org/abs/1903.04666v1

    • [math.OC]An Efficient Augmented Lagrangian Based Method for Constrained Lasso
    Zengde Deng, Anthony Man-Cho So
    http://arxiv.org/abs/1903.05006v1

    • [math.PR]Calibrating dependence between random elements
    Abram M. Kagan, Gabor J. Székely
    http://arxiv.org/abs/1903.04663v1

    • [math.PR]The Inverse first passage time method for a two compartment model as a tool to relate Inverse Gaussian and Gamma spike distributions
    Alessia Civallero, Cristina Zucca
    http://arxiv.org/abs/1903.04927v1

    • [math.ST]ECKO: Ensemble of Clustered Knockoffs for multivariate inference on fMRI data
    Tuan-Binh Nguyen, Jérôme-Alexis Chevalier, Bertrand Thirion
    http://arxiv.org/abs/1903.04955v1

    • [math.ST]The All-or-Nothing Phenomenon in Sparse Linear Regression
    Galen Reeves, Jiaming Xu, Ilias Zadik
    http://arxiv.org/abs/1903.05046v1

    • [math.ST]The limits of distribution-free conditional predictive inference
    Rina Foygel Barber, Emmanuel J. Candès, Aaditya Ramdas, Ryan J. Tibshirani
    http://arxiv.org/abs/1903.04684v1

    • [physics.soc-ph]A subset selection based approach to finding important structure of complex networks
    Richa Tripathi, Amit Reza
    http://arxiv.org/abs/1903.04649v1

    • [q-bio.GN]conLSH: Context based Locality Sensitive Hashing for Mapping of noisy SMRT Reads
    Angana Chakraborty, Sanghamitra Bandyopadhyay
    http://arxiv.org/abs/1903.04925v1

    • [q-fin.PM]Financial Applications of Gaussian Processes and Bayesian Optimization
    Joan Gonzalvez, Edmond Lezmi, Thierry Roncalli, Jiali Xu
    http://arxiv.org/abs/1903.04841v1

    • [stat.AP]Analysis of the AOK Lower Saxony hospitalisation records data (years 2008 -- 2015)
    Monika J. Piotrowska, Konrad Sakowski
    http://arxiv.org/abs/1903.04701v1

    • [stat.AP]The conditionally autoregressive hidden Markov model (CarHMM): Inferring behavioural states from animal tracking data exhibiting conditional autocorrelation
    Ethan Lawler, Kim Whoriskey, William H. Aeberhard, Chris Field, Joanna Mills Flemming
    http://arxiv.org/abs/1903.04999v1

    • [stat.CO]ROC and AUC with a Binary Predictor: a Potentially Misleading Metric
    John Muschelli
    http://arxiv.org/abs/1903.04881v1

    • [stat.ME]Causal organic direct and indirect effects: closer to Baron and Kenny
    Judith J. Lok
    http://arxiv.org/abs/1903.04697v1

    • [stat.ME]Discrete factor analysis
    Rolf Larsson
    http://arxiv.org/abs/1903.04919v1

    • [stat.ME]Flexible Clustering with a Sparse Mixture of Generalized Hyperbolic Distributions
    Michael P. B. Gallaugher, Yang Tang, Paul D. McNicholas
    http://arxiv.org/abs/1903.05054v1

    • [stat.ME]Generalized Sparse Additive Models
    Asad Haris, Noah Simon, Ali Shojaie
    http://arxiv.org/abs/1903.04641v1

    • [stat.ME]Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction
    John R. Tipton, Mevin B. Hooten, Connor Nolan, Robert K. Booth, Jason McLachlan
    http://arxiv.org/abs/1903.05036v1

    • [stat.ML]Elements of Sequential Monte Carlo
    Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön
    http://arxiv.org/abs/1903.04797v1

    • [stat.ML]Imputation estimators for unnormalized models with missing data
    Masatoshi Uehara, Takeru Matsuda, Jae Kwang Kim
    http://arxiv.org/abs/1903.03630v1

    • [stat.ML]Testing Conditional Independence on Discrete Data using Stochastic Complexity
    Alexander Marx, Jilles Vreeken
    http://arxiv.org/abs/1903.04829v1

    • [stat.ML]Wavelet regression and additive models for irregularly spaced data
    Asad Haris, Noah Simon, Ali Shojaie
    http://arxiv.org/abs/1903.04631v1

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