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.DS - 数据结构与算法
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.PF - 计算性能
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
math.OC - 优化与控制
math.ST - 统计理论
physics.comp-ph - 计算物理学
q-bio.QM - 定量方法
stat.AP - 应用统计
stat.ME - 统计方法论
stat.ML - (统计)机器学习
stat.OT - 其他统计学
• [cs.AI]An alternative approach to coherent choice functions
• [cs.AI]Evaluation Mechanism of Collective Intelligence for Heterogeneous Agents Group
• [cs.AI]Learning To Follow Directions in Street View
• [cs.AI]Should All Temporal Difference Learning Use Emphasis?
• [cs.AI]To Monitor or to Trust: Observing Robot's Behavior based on a Game-Theoretic Model of Trust
• [cs.CL]Chinese-Japanese Unsupervised Neural Machine Translation Using Sub-character Level Information
• [cs.CL]DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
• [cs.CL]Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data
• [cs.CL]Improving Grounded Natural Language Understanding through Human-Robot Dialog
• [cs.CL]Jointly Optimizing Diversity and Relevance in Neural Response Generation
• [cs.CL]KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos
• [cs.CL]Massively Multilingual Neural Machine Translation
• [cs.CL]Non-Parametric Adaptation for Neural Machine Translation
• [cs.CL]Open Information Extraction from Question-Answer Pairs
• [cs.CL]Reinforcement Learning based Curriculum Optimization for Neural Machine Translation
• [cs.CL]Using natural language processing techniques to extract information on the properties and functionalities of energetic materials from large text corpora
• [cs.CR]TamperNN: Efficient Tampering Detection of Deployed Neural Nets
• [cs.CV]A Behavioral Approach to Visual Navigation with Graph Localization Networks
• [cs.CV]A Deep DUAL-PATH Network for Improved Mammogram Image Processing
• [cs.CV]A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning
• [cs.CV]Adversarial Generation of Handwritten Text Images Conditioned on Sequences
• [cs.CV]Answer Them All! Toward Universal Visual Question Answering Models
• [cs.CV]Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression
• [cs.CV]Broad Neural Network for Change Detection in Aerial Images
• [cs.CV]Deep Learning for Multiple-Image Super-Resolution
• [cs.CV]Deep Neural Network and Data Augmentation Methodology for off-axis iris segmentation in wearable headsets
• [cs.CV]Frequency Domain Transformer Networks for Video Prediction
• [cs.CV]GAN Based Image Deblurring Using Dark Channel Prior
• [cs.CV]Image-Based Geo-Localization Using Satellite Imagery
• [cs.CV]Local Geometric Indexing of High Resolution Data for Facial Reconstruction from Sparse Markers
• [cs.CV]Lung CT Imaging Sign Classification through Deep Learning on Small Data
• [cs.CV]Mask Scoring R-CNN
• [cs.CV]Object Recognition in Deep Convolutional Neural Networks is Fundamentally Different to That in Humans
• [cs.CV]On the Effectiveness of Low Frequency Perturbations
• [cs.CV]Progress Regression RNN for Online Spatial-Temporal Action Localization in Unconstrained Videos
• [cs.CV]Provably scale-covariant networks from oriented quasi quadrature measures in cascade
• [cs.CV]Pyramid Feature Selective Network for Saliency detection
• [cs.CV]ROVO: Robust Omnidirectional Visual Odometry for Wide-baseline Wide-FOV Camera Systems
• [cs.CV]SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation
• [cs.CV]Self-supervised Learning for Single View Depth and Surface Normal Estimation
• [cs.CV]Single Image Deblurring and Camera Motion Estimation with Depth Map
• [cs.CV]Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks
• [cs.CV]Video Extrapolation with an Invertible Linear Embedding
• [cs.CV]Video Summarization via Actionness Ranking
• [cs.CY]Characterizing Activity on the Deep and Dark Web
• [cs.DS]Parallel Weighted Random Sampling
• [cs.IR]Optimal Projection Guided Transfer Hashing for Image Retrieval
• [cs.IR]Ranking in Genealogy: Search Results Fusion at Ancestry
• [cs.IR]Saec: Similarity-Aware Embedding Compression in Recommendation Systems
• [cs.IT]A Method Beyond Channel Capacity in the Low SNR Regime: Theoretical Proof and Numerical Confirmation
• [cs.IT]Bounding and Estimating the Classical Information Rate of Quantum Channels with Memory
• [cs.IT]Covariance-Aided CSI Acquisition with Non-Orthogonal Pilots in Massive MIMO Systems
• [cs.IT]On the Existence of Perfect Splitter Sets
• [cs.IT]Secure Users Oriented Downlink MISO NOMA
• [cs.IT]Uplink Non-Orthogonal Multiple Access over Mixed RF-FSO Systems
• [cs.LG]A block-random algorithm for learning on distributed, heterogeneous data
• [cs.LG]Catalyst.RL: A Distributed Framework for Reproducible RL Research
• [cs.LG]Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment
• [cs.LG]Learning to Plan via Neural Exploration-Exploitation Trees
• [cs.LG]Model-Based Reinforcement Learning for Atari
• [cs.LG]Multi-Object Representation Learning with Iterative Variational Inference
• [cs.LG]Non-linear ICA based on Cramer-Wold metric
• [cs.LG]Optimal Algorithms for Ski Rental with Soft Machine-Learned Predictions
• [cs.PF]Speeding up Deep Learning with Transient Servers
• [cs.RO]Data-Driven Gait Segmentation for Walking Assistance in a Lower-Limb Assistive Device
• [cs.RO]Dynamic Channel: A Planning Framework for Crowd Navigation
• [cs.RO]Generating Grasp Poses for a High-DOF Gripper Using Neural Networks
• [cs.RO]Improving Data Efficiency of Self-supervised Learning for Robotic Grasping
• [cs.RO]Industrial Robot Trajectory Tracking Using Multi-Layer Neural Networks Trained by Iterative Learning Control
• [cs.RO]OpenRoACH: A Durable Open-Source Hexapedal Platform with Onboard Robot Operating System (ROS)
• [cs.RO]RoboCSE: Robot Common Sense Embedding
• [cs.RO]Vine Robots: Design, Teleoperation, and Deployment for Navigation and Exploration
• [cs.RO]Volumetric Instance-Aware Semantic Mapping and 3D Object Discovery
• [cs.SD]A Unified Neural Architecture for Instrumental Audio Tasks
• [cs.SI]A Framework for Detecting Event related Sentiments of a Community
• [cs.SI]Data-driven Approach for Quality Evaluation on Knowledge Sharing Platform
• [cs.SI]High Degree Vertices and Spread of Infections in Spatially Modelled Social Networks
• [cs.SI]Maximizing spreading influence via measuring influence overlap for social networks
• [cs.SI]Transient Dynamics of Epidemic Spreading and its Mitigation on Large Networks
• [cs.SY]Approximate Robust Control of Uncertain Dynamical Systems
• [cs.SY]Distributed Variational Bayesian Algorithms for Extended Object Tracking
• [math.OC]GuSTO: Guaranteed Sequential Trajectory Optimization via Sequential Convex Programming
• [math.OC]Proximal algorithms for constrained composite optimization, with applications to solving low-rank SDPs
• [math.ST]A robust approach for principal component analyisis
• [math.ST]Approximation by finite mixtures of continuous density functions that vanish at infinity
• [math.ST]Are profile likelihoods likelihoods? No, but sometimes they can be
• [math.ST]Improving efficiency in fuzzy regression modeling by Stein-type shrinkage
• [math.ST]Reliability Analysis of Systems Subject To Mutually Dependent Competing Failure Processes With Changing Degradation Rate
• [physics.comp-ph]A massively parallel semi-Lagrangian solver for the six-dimensional Vlasov-Poisson equation
• [q-bio.QM]Deep Learning How to Fit an Intravoxel Incoherent Motion Model to Diffusion-Weighted MRI
• [q-bio.QM]Deep learning in bioinformatics: introduction, application, and perspective in big data era
• [q-bio.QM]Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with Attention
• [stat.AP]A statistical view on a surrogate model for estimating extreme events with an application to wind turbines
• [stat.AP]Contemporary statistical inference for infectious disease models using Stan
• [stat.AP]Detecting changes in the covariance structure of functional time series with application to fMRI data
• [stat.AP]Inter-frequency radio signal quality prediction for handover, evaluated in 3GPP LTE
• [stat.AP]Stabilizing a Queue Subject to Action-Dependent Server Performance
• [stat.ME]A Framework for Covariate Balance using Bregman Distances
• [stat.ME]Distance-Based Independence Screening for Canonical Analysis
• [stat.ME]Metropolized Knockoff Sampling
• [stat.ME]Profile and Globe Tests of Mean Surfaces for Two-Sample Bivariate Functional Data
• [stat.ME]The wrapped xgamma distribution for modeling circular data appearing in geological context
• [stat.ML]A Review of Stochastic Block Models and Extensions for Graph Clustering
• [stat.ML]Machine learning in policy evaluation: new tools for causal inference
• [stat.ML]On the complexity of logistic regression models
• [stat.OT]Bounds on Bayes Factors for Binomial A/B Testing
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• [cs.AI]An alternative approach to coherent choice functions
Jasper De Bock, Gert de Cooman
http://arxiv.org/abs/1903.00336v1
• [cs.AI]Evaluation Mechanism of Collective Intelligence for Heterogeneous Agents Group
Anna Dai, Zhifeng Zhao, Honggang Zhang, Rongpeng Li, Yugeng Zhou
http://arxiv.org/abs/1903.00206v1
• [cs.AI]Learning To Follow Directions in Street View
Karl Moritz Hermann, Mateusz Malinowski, Piotr Mirowski, Andras Banki-Horvath, Keith Anderson, Raia Hadsell
http://arxiv.org/abs/1903.00401v1
• [cs.AI]Should All Temporal Difference Learning Use Emphasis?
Xiang Gu, Sina Ghiassian, Richard S. Sutton
http://arxiv.org/abs/1903.00194v1
• [cs.AI]To Monitor or to Trust: Observing Robot's Behavior based on a Game-Theoretic Model of Trust
Sailik Sengupta, Zahra Zahedi, Subbarao Kambhampati
http://arxiv.org/abs/1903.00111v1
• [cs.CL]Chinese-Japanese Unsupervised Neural Machine Translation Using Sub-character Level Information
Longtu Zhang, Mamoru Komachi
http://arxiv.org/abs/1903.00149v1
• [cs.CL]DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, Matt Gardner
http://arxiv.org/abs/1903.00161v1
• [cs.CL]Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data
Wei Zhao, Liang Wang, Kewei Shen, Ruoyu Jia, Jingming Liu
http://arxiv.org/abs/1903.00138v1
• [cs.CL]Improving Grounded Natural Language Understanding through Human-Robot Dialog
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, Raymond J. Mooney
http://arxiv.org/abs/1903.00122v1
• [cs.CL]Jointly Optimizing Diversity and Relevance in Neural Response Generation
Xiang Gao, Sungjin Lee, Yizhe Zhang, Chris Brockett, Michel Galley, Jianfeng Gao, Bill Dolan
http://arxiv.org/abs/1902.11205v2
• [cs.CL]KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos
Egor Lakomkin, Sven Magg, Cornelius Weber, Stefan Wermter
http://arxiv.org/abs/1903.00216v1
• [cs.CL]Massively Multilingual Neural Machine Translation
Roee Aharoni, Melvin Johnson, Orhan Firat
http://arxiv.org/abs/1903.00089v1
• [cs.CL]Non-Parametric Adaptation for Neural Machine Translation
Ankur Bapna, Orhan Firat
http://arxiv.org/abs/1903.00058v1
• [cs.CL]Open Information Extraction from Question-Answer Pairs
Nikita Bhutani, Yoshihiko Suhara, Wang-Chiew Tan, Alon Halevy, H. V. Jagadish
http://arxiv.org/abs/1903.00172v1
• [cs.CL]Reinforcement Learning based Curriculum Optimization for Neural Machine Translation
Gaurav Kumar, George Foster, Colin Cherry, Maxim Krikun
http://arxiv.org/abs/1903.00041v1
• [cs.CL]Using natural language processing techniques to extract information on the properties and functionalities of energetic materials from large text corpora
Daniel C. Elton, Dhruv Turakhia, Nischal Reddy, Zois Boukouvalas, Mark D. Fuge, Ruth M. Doherty, Peter W. Chung
http://arxiv.org/abs/1903.00415v1
• [cs.CR]TamperNN: Efficient Tampering Detection of Deployed Neural Nets
Erwan Le Merrer, Gilles Trédan
http://arxiv.org/abs/1903.00317v1
• [cs.CV]A Behavioral Approach to Visual Navigation with Graph Localization Networks
Kevin Chen, Juan Pablo de Vicente, Gabriel Sepulveda, Fei Xia, Alvaro Soto, Marynel Vazquez, Silvio Savarese
http://arxiv.org/abs/1903.00445v1
• [cs.CV]A Deep DUAL-PATH Network for Improved Mammogram Image Processing
Heyi Li, Dongdong Chen, William H. Nailon, Mike E. Davies, Dave Laurenson
http://arxiv.org/abs/1903.00001v1
• [cs.CV]A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning
Yinjie Lei, Ziqin Zhou, Pingping Zhang, Yulan Guo, Zijun Ma, Lingqiao Liu
http://arxiv.org/abs/1903.00117v1
• [cs.CV]Adversarial Generation of Handwritten Text Images Conditioned on Sequences
Eloi Alonso, Bastien Moysset, Ronaldo Messina
http://arxiv.org/abs/1903.00277v1
• [cs.CV]Answer Them All! Toward Universal Visual Question Answering Models
Robik Shrestha, Kushal Kafle, Christopher Kanan
http://arxiv.org/abs/1903.00366v1
• [cs.CV]Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression
Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Hua Li, Mark Anastasio
http://arxiv.org/abs/1903.00388v1
• [cs.CV]Broad Neural Network for Change Detection in Aerial Images
Shailesh Shrivastava, Alakh Aggarwal, Pratik Chattopadhyay
http://arxiv.org/abs/1903.00087v1
• [cs.CV]Deep Learning for Multiple-Image Super-Resolution
Michal Kawulok, Pawel Benecki, Szymon Piechaczek, Krzysztof Hrynczenko, Daniel Kostrzewa, Jakub Nalepa
http://arxiv.org/abs/1903.00440v1
• [cs.CV]Deep Neural Network and Data Augmentation Methodology for off-axis iris segmentation in wearable headsets
Viktor Varkarakis, Shabab Bazrafkan, Peter Corcoran
http://arxiv.org/abs/1903.00389v1
• [cs.CV]Frequency Domain Transformer Networks for Video Prediction
Hafez Farazi, Sven Behnke
http://arxiv.org/abs/1903.00271v1
• [cs.CV]GAN Based Image Deblurring Using Dark Channel Prior
Shuang Zhang, Ada Zhen, Robert L. Stevenson
http://arxiv.org/abs/1903.00107v1
• [cs.CV]Image-Based Geo-Localization Using Satellite Imagery
Sixing Hu, Gim Hee Lee
http://arxiv.org/abs/1903.00159v1
• [cs.CV]Local Geometric Indexing of High Resolution Data for Facial Reconstruction from Sparse Markers
Matthew Cong, Lana Lan, Ronald Fedkiw
http://arxiv.org/abs/1903.00119v1
• [cs.CV]Lung CT Imaging Sign Classification through Deep Learning on Small Data
Guocai He
http://arxiv.org/abs/1903.00183v1
• [cs.CV]Mask Scoring R-CNN
Zhaojin Huang, Lichao Huang, Yongchao Gong, Chang Huang, Xinggang Wang
http://arxiv.org/abs/1903.00241v1
• [cs.CV]Object Recognition in Deep Convolutional Neural Networks is Fundamentally Different to That in Humans
Ben Lonnqvist, Alasdair D. F. Clarke, Ramakrishna Chakravarthi
http://arxiv.org/abs/1903.00258v1
• [cs.CV]On the Effectiveness of Low Frequency Perturbations
Yash Sharma, Gavin Weiguang Ding, Marcus Brubaker
http://arxiv.org/abs/1903.00073v1
• [cs.CV]Progress Regression RNN for Online Spatial-Temporal Action Localization in Unconstrained Videos
Bo Hu, Jianfei Cai, Tat-Jen Cham, Junsong Yuan
http://arxiv.org/abs/1903.00304v1
• [cs.CV]Provably scale-covariant networks from oriented quasi quadrature measures in cascade
Tony Lindeberg
http://arxiv.org/abs/1903.00289v1
• [cs.CV]Pyramid Feature Selective Network for Saliency detection
Ting Zhao, Xiangqian Wu
http://arxiv.org/abs/1903.00179v1
• [cs.CV]ROVO: Robust Omnidirectional Visual Odometry for Wide-baseline Wide-FOV Camera Systems
Hochang Seok, Jongwoo Lim
http://arxiv.org/abs/1902.11154v2
• [cs.CV]SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation
Yizhe Zhang, Lin Yang, Hao Zheng, Peixian Liang, Colleen Mangold, Raquel G. Loreto, David P. Hughes, Danny Z. Chen
http://arxiv.org/abs/1903.00035v1
• [cs.CV]Self-supervised Learning for Single View Depth and Surface Normal Estimation
Huangying Zhan, Chamara Saroj Weerasekera, Ravi Garg, Ian Reid
http://arxiv.org/abs/1903.00112v1
• [cs.CV]Single Image Deblurring and Camera Motion Estimation with Depth Map
Liyuan Pan, Yuchao Dai, Miaomiao Liu
http://arxiv.org/abs/1903.00231v1
• [cs.CV]Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks
Joshua Peter Ebenezer, Bijaylaxmi Das, Sudipta Mukhopadhyay
http://arxiv.org/abs/1903.00395v1
• [cs.CV]Video Extrapolation with an Invertible Linear Embedding
Robert Pottorff, Jared Nielsen, David Wingate
http://arxiv.org/abs/1903.00133v1
• [cs.CV]Video Summarization via Actionness Ranking
Mohamed Elfeki, Ali Borji
http://arxiv.org/abs/1903.00110v1
• [cs.CY]Characterizing Activity on the Deep and Dark Web
Nazgol Tavabi, Nathan Bartley, Andrés Abeliuk, Sandeep Soni, Emilio Ferrara, Kristina Lerman
http://arxiv.org/abs/1903.00156v1
• [cs.DS]Parallel Weighted Random Sampling
Lorenz Hübschle-Schneider, Peter Sanders
http://arxiv.org/abs/1903.00227v1
• [cs.IR]Optimal Projection Guided Transfer Hashing for Image Retrieval
Ji Liu, Lei Zhang
http://arxiv.org/abs/1903.00252v1
• [cs.IR]Ranking in Genealogy: Search Results Fusion at Ancestry
Peng Jiang, Yingrui Yang, Gann Bierner, Fengjie Alex Li, Ruhan Wang, Azadeh Moghtaderi
http://arxiv.org/abs/1903.00099v1
• [cs.IR]Saec: Similarity-Aware Embedding Compression in Recommendation Systems
Xiaorui Wu, Hong Xu, Honglin Zhang, Huaming Chen, Jian Wang
http://arxiv.org/abs/1903.00103v1
• [cs.IT]A Method Beyond Channel Capacity in the Low SNR Regime: Theoretical Proof and Numerical Confirmation
Bingli Jiao, Yuli Yang, Mingxi Yin
http://arxiv.org/abs/1903.00136v1
• [cs.IT]Bounding and Estimating the Classical Information Rate of Quantum Channels with Memory
Michael X. Cao, Pascal O. Vontobel
http://arxiv.org/abs/1903.00199v1
• [cs.IT]Covariance-Aided CSI Acquisition with Non-Orthogonal Pilots in Massive MIMO Systems
Alexis Decurninge, Luis G. Ordóñez, Maxime Guillaud
http://arxiv.org/abs/1903.00269v1
• [cs.IT]On the Existence of Perfect Splitter Sets
Pingzhi Yuan, Kevin Zhao
http://arxiv.org/abs/1903.00118v1
• [cs.IT]Secure Users Oriented Downlink MISO NOMA
Hui-Ming Wang, Xu Zhang, Qian Yang, Theodoros A. Tsiftsis
http://arxiv.org/abs/1903.00205v1
• [cs.IT]Uplink Non-Orthogonal Multiple Access over Mixed RF-FSO Systems
Mohammad Vahid Jamali, Hessam Mahdavifar
http://arxiv.org/abs/1903.00326v1
• [cs.LG]A block-random algorithm for learning on distributed, heterogeneous data
Prakash Mohan, Marc T. Henry de Frahan, Ryan King, Ray W. Grout
http://arxiv.org/abs/1903.00091v1
• [cs.LG]Catalyst.RL: A Distributed Framework for Reproducible RL Research
Sergey Kolesnikov, Oleksii Hrinchuk
http://arxiv.org/abs/1903.00027v1
• [cs.LG]Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment
Cedric Renggli, Bojan Karlaš, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang
http://arxiv.org/abs/1903.00278v1
• [cs.LG]Learning to Plan via Neural Exploration-Exploitation Trees
Binghong Chen, Bo Dai, Le Song
http://arxiv.org/abs/1903.00070v1
• [cs.LG]Model-Based Reinforcement Learning for Atari
Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Ryan Sepassi, George Tucker, Henryk Michalewski
http://arxiv.org/abs/1903.00374v1
• [cs.LG]Multi-Object Representation Learning with Iterative Variational Inference
Klaus Greff, Raphaël Lopez Kaufmann, Rishab Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew Botvinick, Alexander Lerchner
http://arxiv.org/abs/1903.00450v1
• [cs.LG]Non-linear ICA based on Cramer-Wold metric
Przemysław Spurek, Aleksandra Nowak, Jacek Tabor, Łukasz Maziarka, Stanisław Jastrzębski
http://arxiv.org/abs/1903.00201v1
• [cs.LG]Optimal Algorithms for Ski Rental with Soft Machine-Learned Predictions
Rohan Kodialam
http://arxiv.org/abs/1903.00092v1
• [cs.PF]Speeding up Deep Learning with Transient Servers
Shijian Li, Robert J. Walls, Lijie Xu, Tian Guo
http://arxiv.org/abs/1903.00045v1
• [cs.RO]Data-Driven Gait Segmentation for Walking Assistance in a Lower-Limb Assistive Device
Aleksandra Kalinowska, Thomas A. Berrueta, Adam Zoss, Todd Murphey
http://arxiv.org/abs/1903.00036v1
• [cs.RO]Dynamic Channel: A Planning Framework for Crowd Navigation
Chao Cao, Pete Trautman, Soshi Iba
http://arxiv.org/abs/1903.00143v1
• [cs.RO]Generating Grasp Poses for a High-DOF Gripper Using Neural Networks
Min Liu, Zherong Pan, Kai Xu, Kanishka Ganguly, Dinesh Manocha
http://arxiv.org/abs/1903.00425v1
• [cs.RO]Improving Data Efficiency of Self-supervised Learning for Robotic Grasping
Lars Berscheid, Thomas Rühr, Torsten Kröger
http://arxiv.org/abs/1903.00228v1
• [cs.RO]Industrial Robot Trajectory Tracking Using Multi-Layer Neural Networks Trained by Iterative Learning Control
Shuyang Chen, John T. Wen
http://arxiv.org/abs/1903.00082v1
• [cs.RO]OpenRoACH: A Durable Open-Source Hexapedal Platform with Onboard Robot Operating System (ROS)
Liyu Wang, Yuxiang Yang, Gustavo Correa, Konstantinos Karydis, Ronald S. Fearing
http://arxiv.org/abs/1903.00131v1
• [cs.RO]RoboCSE: Robot Common Sense Embedding
Angel Daruna, Weiyu Liu, Zsolt Kira, Sonia Chernova
http://arxiv.org/abs/1903.00412v1
• [cs.RO]Vine Robots: Design, Teleoperation, and Deployment for Navigation and Exploration
Margaret M. Coad, Laura H. Blumenschein, Sadie Cutler, Javier A. Reyna Zepeda, Nicholas D. Naclerio, Haitham El-Hussieny, Usman Mehmood, Jee-Hwan Ryu, Elliot W. Hawkes, Allison M. Okamura
http://arxiv.org/abs/1903.00069v1
• [cs.RO]Volumetric Instance-Aware Semantic Mapping and 3D Object Discovery
Margarita Grinvald, Fadri Furrer, Tonci Novkovic, Jen Jen Chung, Cesar Cadena, Roland Siegwart, Juan Nieto
http://arxiv.org/abs/1903.00268v1
• [cs.SD]A Unified Neural Architecture for Instrumental Audio Tasks
Steven Spratley, Daniel Beck, Trevor Cohn
http://arxiv.org/abs/1903.00142v1
• [cs.SI]A Framework for Detecting Event related Sentiments of a Community
Muhammad Aslam Jarwar
http://arxiv.org/abs/1903.00232v1
• [cs.SI]Data-driven Approach for Quality Evaluation on Knowledge Sharing Platform
Lu Xu, Jinhai Xiang, Yating Wang, Fuchuan Ni
http://arxiv.org/abs/1903.00384v1
• [cs.SI]High Degree Vertices and Spread of Infections in Spatially Modelled Social Networks
Joshua Feldman, Jeannette Janssen
http://arxiv.org/abs/1903.00077v1
• [cs.SI]Maximizing spreading influence via measuring influence overlap for social networks
Ning Wang, Zi-Yi Wang, Jian-Guo Liu, Jing-Ti Han
http://arxiv.org/abs/1903.00248v1
• [cs.SI]Transient Dynamics of Epidemic Spreading and its Mitigation on Large Networks
Chul-Ho Lee, Srinivas Tenneti, Do Young Eun
http://arxiv.org/abs/1903.00167v1
• [cs.SY]Approximate Robust Control of Uncertain Dynamical Systems
Edouard Leurent, Yann Blanco, Denis Efimov, Odalric-Ambrym Maillard
http://arxiv.org/abs/1903.00220v1
• [cs.SY]Distributed Variational Bayesian Algorithms for Extended Object Tracking
Junhao Hua, Chunguang Li
http://arxiv.org/abs/1903.00182v1
• [math.OC]GuSTO: Guaranteed Sequential Trajectory Optimization via Sequential Convex Programming
Riccardo Bonalli, Abhishek Cauligi, Andrew Bylard, Marco Pavone
http://arxiv.org/abs/1903.00155v1
• [math.OC]Proximal algorithms for constrained composite optimization, with applications to solving low-rank SDPs
Yu Bai, John Duchi, Song Mei
http://arxiv.org/abs/1903.00184v1
• [math.ST]A robust approach for principal component analyisis
María Camila Vásquez-Correa, Henry Laniado Rodas
http://arxiv.org/abs/1903.00093v1
• [math.ST]Approximation by finite mixtures of continuous density functions that vanish at infinity
T Tin Nguyen, Hien D Nguyen, Faicel Chamroukhi, Geoffrey J McLachlan
http://arxiv.org/abs/1903.00147v1
• [math.ST]Are profile likelihoods likelihoods? No, but sometimes they can be
Alan Huang, Andy Sangil Kim
http://arxiv.org/abs/1903.00162v1
• [math.ST]Improving efficiency in fuzzy regression modeling by Stein-type shrinkage
M. Kashani, M. Arashi, M. R. Rabiei
http://arxiv.org/abs/1903.00351v1
• [math.ST]Reliability Analysis of Systems Subject To Mutually Dependent Competing Failure Processes With Changing Degradation Rate
Nooshin Yousefi, David W. Coit
http://arxiv.org/abs/1903.00076v1
• [physics.comp-ph]A massively parallel semi-Lagrangian solver for the six-dimensional Vlasov-Poisson equation
Katharina Kormann, Klaus Reuter, Markus Rampp
http://arxiv.org/abs/1903.00308v1
• [q-bio.QM]Deep Learning How to Fit an Intravoxel Incoherent Motion Model to Diffusion-Weighted MRI
Sebastiano Barbieri, Oliver J. Gurney-Champion, Remy Klaassen, Harriet C. Thoeny
http://arxiv.org/abs/1903.00095v1
• [q-bio.QM]Deep learning in bioinformatics: introduction, application, and perspective in big data era
Yu Li, Chao Huang, Lizhong Ding, Zhongxiao Li, Yijie Pan, Xin Gao
http://arxiv.org/abs/1903.00342v1
• [q-bio.QM]Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with Attention
Eryu Xia, Xin Du, Jing Mei, Wen Sun, Suijun Tong, Zhiqing Kang, Jian Sheng, Jian Li, Changsheng Ma, Jianzeng Dong, Shaochun Li
http://arxiv.org/abs/1903.00197v1
• [stat.AP]A statistical view on a surrogate model for estimating extreme events with an application to wind turbines
Mikkel Slot Nielsen, Victor Rohde
http://arxiv.org/abs/1903.00251v1
• [stat.AP]Contemporary statistical inference for infectious disease models using Stan
Anastasia Chatzilena, Edwin van Leeuwen, Oliver Ratmann, Marc Baguelin, Nikolaos Demiris
http://arxiv.org/abs/1903.00423v1
• [stat.AP]Detecting changes in the covariance structure of functional time series with application to fMRI data
Christina Stoehr, John A D Aston, Claudia Kirch
http://arxiv.org/abs/1903.00288v1
• [stat.AP]Inter-frequency radio signal quality prediction for handover, evaluated in 3GPP LTE
Caroline Svahn, Oleg Sysoev, Mirsad Čirkić, Fredrik Gunnarsson, Joel Berglund
http://arxiv.org/abs/1903.00196v1
• [stat.AP]Stabilizing a Queue Subject to Action-Dependent Server Performance
Michael Lin, Richard J. La, Nuno C. Martins
http://arxiv.org/abs/1903.00135v1
• [stat.ME]A Framework for Covariate Balance using Bregman Distances
Kevin P. Josey, Elizabeth Juarez-Colunga, Debashis Ghosh
http://arxiv.org/abs/1903.00390v1
• [stat.ME]Distance-Based Independence Screening for Canonical Analysis
Chuanping Yu, Xiaoming Huo
http://arxiv.org/abs/1903.00037v1
• [stat.ME]Metropolized Knockoff Sampling
Stephen Bates, Emmanuel Candès, Lucas Janson, Wenshuo Wang
http://arxiv.org/abs/1903.00434v1
• [stat.ME]Profile and Globe Tests of Mean Surfaces for Two-Sample Bivariate Functional Data
Jin Yang, Chunling Liu, Tao Zhang, Kam Chuen Yuen, Aiyi Liu
http://arxiv.org/abs/1902.10570v2
• [stat.ME]The wrapped xgamma distribution for modeling circular data appearing in geological context
Hazem Al-Mofleh, Subhradev Sen
http://arxiv.org/abs/1903.00177v1
• [stat.ML]A Review of Stochastic Block Models and Extensions for Graph Clustering
Clement Lee, Darren J Wilkinson
http://arxiv.org/abs/1903.00114v1
• [stat.ML]Machine learning in policy evaluation: new tools for causal inference
Noemi Kreif, Karla DiazOrdaz
http://arxiv.org/abs/1903.00402v1
• [stat.ML]On the complexity of logistic regression models
Nicola Bulso, Matteo Marsili, Yasser Roudi
http://arxiv.org/abs/1903.00386v1
• [stat.OT]Bounds on Bayes Factors for Binomial A/B Testing
Maciej Skorski
http://arxiv.org/abs/1903.00049v1
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