astro-ph.IM - 仪器仪表和天体物理学方法
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.DC - 分布式、并行与集群计算
cs.HC - 人机接口
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.SE - 软件工程
cs.SI - 社交网络与信息网络
eess.AS - 语音处理
eess.IV - 图像与视频处理
eess.SP - 信号处理
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.data-an - 数据分析、 统计和概率
physics.soc-ph - 物理学与社会
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
• [astro-ph.IM]Attitude Control of an Inflatable Sailplane for Mars Exploration
• [cs.AI]Agent-Based Adaptive Level Generation for Dynamic Difficulty Adjustment in Angry Birds
• [cs.AI]Augmenting Learning Components for Safety in Resource Constrained Autonomous Robots
• [cs.AI]Distributed Synthesis of Surveillance Strategies for Mobile Sensors
• [cs.AI]The Actor-Advisor: Policy Gradient With Off-Policy Advice
• [cs.AI]Toward A Neuro-inspired Creative Decoder
• [cs.CL]Aspect Specific Opinion Expression Extraction using Attention based LSTM-CRF Network
• [cs.CL]Compression of Recurrent Neural Networks for Efficient Language Modeling
• [cs.CL]End-to-end Anchored Speech Recognition
• [cs.CL]Towards Autoencoding Variational Inference for Aspect-based Opinion Summary
• [cs.CL]Understanding Chat Messages for Sticker Recommendation in Hike Messenger
• [cs.CV]Advances on CNN-based super-resolution of Sentinel-2 images
• [cs.CV]Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level
• [cs.CV]CHIP: Channel-wise Disentangled Interpretation of Deep Convolutional Neural Networks
• [cs.CV]FDDB-360: Face Detection in 360-degree Fisheye Images
• [cs.CV]Matrix Cofactorization for Joint Representation Learning and Supervised Classification -- Application to Hyperspectral Image Analysis
• [cs.CV]Neural Inverse Knitting: From Images to Manufacturing Instructions
• [cs.CV]Real-time 3D Traffic Cone Detection for Autonomous Driving
• [cs.CV]Reversible GANs for Memory-efficient Image-to-Image Translation
• [cs.CV]Single Network Panoptic Segmentation for Street Scene Understanding
• [cs.CV]StampNet: unsupervised multi-class object discovery
• [cs.CV]Theoretical analysis on Noise2Noise using Stein's Unbiased Risk Estimator for Gaussian denoising: Towards unsupervised training with clipped noisy images
• [cs.CV]Unsupervised Data Uncertainty Learning in Visual Retrieval Systems
• [cs.CV]Virtual Training for a Real Application: Accurate Object-Robot Relative Localization without Calibration
• [cs.DC]Hop: Heterogeneity-Aware Decentralized Training
• [cs.DC]PAI Data, Summary of the Project PAI Data Protocol
• [cs.DC]Prospective Hybrid Consensus for Project PAI
• [cs.DC]Random Gossip Processes in Smartphone Peer-to-Peer Networks
• [cs.DC]Storm: a fast transactional dataplane for remote data structures
• [cs.HC]Are Children Fully Aware of Online Privacy Risks and How Can We Improve Their Coping Ability?
• [cs.IR]A Comparison of Information Retrieval Techniques for Detecting Source Code Plagiarism
• [cs.IR]A Network-centric Framework for Auditing Recommendation Systems
• [cs.IR]The few-get-richer: a surprising consequence of popularity-based rankings
• [cs.IT]A Random Access G-Network: Stability, Stable Throughput, and Queueing Analysis
• [cs.IT]Asymmetric Construction of Low-Latency and Length-Flexible Polar Codes
• [cs.IT]Eigenvalue Based Detection of a Signal in Colored Noise: Finite and Asymptotic Analyses
• [cs.IT]Massive MIMO Multicast Beamforming Via Accelerated Random Coordinate Descent
• [cs.IT]Rank-metric codes
• [cs.IT]Safeguarding Wireless Network with UAVs: A Physical Layer Security Perspective
• [cs.LG]A Simple Baseline for Bayesian Uncertainty in Deep Learning
• [cs.LG]Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
• [cs.LG]Adversarial Domain Adaptation for Stance Detection
• [cs.LG]Artificial Intelligence for Prosthetics - challenge solutions
• [cs.LG]BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
• [cs.LG]Bounds for the VC Dimension of 1NN Prototype Sets
• [cs.LG]Centroid-based deep metric learning for speaker recognition
• [cs.LG]Deeper & Sparser Exploration
• [cs.LG]DiffEqFlux.jl - A Julia Library for Neural Differential Equations
• [cs.LG]Effectiveness of LSTMs in Predicting Congestive Heart Failure Onset
• [cs.LG]Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives
• [cs.LG]Global Explanations of Neural Networks: Mapping the Landscape of Predictions
• [cs.LG]Graph Classification with Recurrent Variational Neural Networks
• [cs.LG]Hybrid Models with Deep and Invertible Features
• [cs.LG]KLUCB Approach to Copeland Bandits
• [cs.LG]Metaoptimization on a Distributed System for Deep Reinforcement Learning
• [cs.LG]Negative eigenvalues of the Hessian in deep neural networks
• [cs.LG]Neural Network Attributions: A Causal Perspective
• [cs.LG]On the Variance of Unbiased Online Recurrent Optimization
• [cs.LG]Online Clustering by Penalized Weighted GMM
• [cs.LG]Principal Model Analysis Based on Partial Least Squares
• [cs.LG]Sparse Regression and Adaptive Feature Generation for the Discovery of Dynamical Systems
• [cs.LG]Spatial Mixture Models with Learnable Deep Priors for Perceptual Grouping
• [cs.LG]Speeding up scaled gradient projection methods using deep neural networks for inverse problems in image processing
• [cs.LG]Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis
• [cs.LG]The role of a layer in deep neural networks: a Gaussian Process perspective
• [cs.MA]CESMA: Centralized Expert Supervises Multi-Agents
• [cs.NE]Investigating RNN Memory using Neuro-Evolution: Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution
• [cs.NE]Self-Adjusting Mutation Rates with Provably Optimal Success Rules
• [cs.RO]Commodifying Pointing in HRI: Simple and Fast Pointing Gesture Detection from RGB-D Images
• [cs.RO]Integer Programming as a General Solution Methodology for Path-Based Optimization in Robotics: Principles and Best Practices
• [cs.SE]A Manually-Curated Dataset of Fixes to Vulnerabilities of Open-Source Software
• [cs.SI]Modeling and Analysis of Tagging Networks in Stack Exchange Communities
• [cs.SI]Red Bots Do It Better Comparative Analysis of Social Bot Partisan Behavior
• [eess.AS]Conv-codes: Audio Hashing For Bird Species Classification
• [eess.AS]End-to-end losses based on speaker basis vectors and all-speaker hard negative mining for speaker verification
• [eess.IV]DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling
• [eess.IV]SAPSAM - Sparsely Annotated Pathological Sign Activation Maps - A novel approach to train Convolutional Neural Networks on lung CT scans using binary labels only
• [eess.SP]Wireless Networks Design in the Era of Deep Learning: Model-Based, AI-Based, or Both?
• [math.OC]Momentum Schemes with Stochastic Variance Reduction for Nonconvex Composite Optimization
• [math.OC]Predict Globally, Correct Locally: Parallel-in-Time Optimal Control of Neural Networks
• [math.PR]On the asymptotic optimality of the comb strategy for prediction with expert advice
• [math.PR]Subadditivity Beyond Trees and the Chi-Squared Mutual Information
• [math.ST]Consistent Risk Estimation in High-Dimensional Linear Regression
• [math.ST]Cramér Type Moderate Deviations for Random Fields
• [math.ST]Estimation of smooth densities in Wasserstein distance
• [math.ST]Tail behavior of dependent V-statistics and its applications
• [math.ST]Weak consistency of the 1-nearest neighbor measure with applications to missing data and covariate shift
• [physics.data-an]Field dynamics inference for local and causal interactions
• [physics.soc-ph]Anti-modular nature of partially bipartite networks makes them infra small-world
• [quant-ph]Entropy Bound for the Classical Capacity of a Quantum Channel Assisted by Classical Feedback
• [stat.AP]Ensemble Prediction of Time to Event Outcomes with Competing Risks: A Case Study of Surgical Complications in Crohn's Disease
• [stat.AP]Winning Is Not Everything: A contextual analysis of hockey face-offs
• [stat.ME]Bias-Aware Confidence Intervals for Empirical Bayes Analysis
• [stat.ME]Modeling microbial abundances and dysbiosis with beta-binomial regression
• [stat.ML]A Bayesian Approach for Accurate Classification-Based Aggregates
• [stat.ML]A Scale Invariant Flatness Measure for Deep Network Minima
• [stat.ML]Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise
• [stat.ML]Cost-Effective Incentive Allocation via Structured Counterfactual Inference
• [stat.ML]Model Selection for Simulator-based Statistical Models: A Kernel Approach
• [stat.ML]Radial and Directional Posteriors for Bayesian Neural Networks
• [stat.ML]Random Matrix Improved Covariance Estimation for a Large Class of Metrics
·····································
• [astro-ph.IM]Attitude Control of an Inflatable Sailplane for Mars Exploration
Adrien Bouskela, Aman Chandra, Jekan Thangavelautham, Sergey Shkarayev
http://arxiv.org/abs/1902.02083v2
• [cs.AI]Agent-Based Adaptive Level Generation for Dynamic Difficulty Adjustment in Angry Birds
Matthew Stephenson, Jochen Renz
http://arxiv.org/abs/1902.02518v1
• [cs.AI]Augmenting Learning Components for Safety in Resource Constrained Autonomous Robots
Shreyas Ramakrishna, Abhishek Dubey, Matthew P Burruss, Charles Hartsell, Nagabhushan Mahadevan, Saideep Nannapaneni, Aron Laszka, Gabor Karsai
http://arxiv.org/abs/1902.02432v1
• [cs.AI]Distributed Synthesis of Surveillance Strategies for Mobile Sensors
Suda Bharadwaj, Rayna Dimitrova, Ufuk Topcu
http://arxiv.org/abs/1902.02393v1
• [cs.AI]The Actor-Advisor: Policy Gradient With Off-Policy Advice
Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé
http://arxiv.org/abs/1902.02556v1
• [cs.AI]Toward A Neuro-inspired Creative Decoder
Payel Das, Brian Quanz, Pin-Yu Chen, Jaw-wook Ahn
http://arxiv.org/abs/1902.02399v1
• [cs.CL]Aspect Specific Opinion Expression Extraction using Attention based LSTM-CRF Network
Abhishek Laddha, Arjun Mukherjee
http://arxiv.org/abs/1902.02709v1
• [cs.CL]Compression of Recurrent Neural Networks for Efficient Language Modeling
Artem M. Grachev, Dmitry I. Ignatov, Andrey V. Savchenko
http://arxiv.org/abs/1902.02380v1
• [cs.CL]End-to-end Anchored Speech Recognition
Yiming Wang, Xing Fan, I-Fan Chen, Yuzong Liu, Tongfei Chen, Björn Hoffmeister
http://arxiv.org/abs/1902.02383v1
• [cs.CL]Towards Autoencoding Variational Inference for Aspect-based Opinion Summary
Tai Hoang, Huy Le, Tho Quan
http://arxiv.org/abs/1902.02507v1
• [cs.CL]Understanding Chat Messages for Sticker Recommendation in Hike Messenger
Abhishek Laddha, Mohamed Hanoosh, Debdoot Mukherjee
http://arxiv.org/abs/1902.02704v1
• [cs.CV]Advances on CNN-based super-resolution of Sentinel-2 images
Massimiliano Gargiulo
http://arxiv.org/abs/1902.02513v1
• [cs.CV]Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level
Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alex M. Bronstein
http://arxiv.org/abs/1902.02593v1
• [cs.CV]CHIP: Channel-wise Disentangled Interpretation of Deep Convolutional Neural Networks
Xinrui Cui, Dan Wang, Z. Jane Wang
http://arxiv.org/abs/1902.02497v1
• [cs.CV]FDDB-360: Face Detection in 360-degree Fisheye Images
Jianglin Fu, Saeed Ranjbar Alvar, Ivan V. Bajic, Rodney G. Vaughan
http://arxiv.org/abs/1902.02777v1
• [cs.CV]Matrix Cofactorization for Joint Representation Learning and Supervised Classification -- Application to Hyperspectral Image Analysis
Adrien Lagrange, Mathieu Fauvel, Stéphane May, José Bioucas-Dias, Nicolas Dobigeon
http://arxiv.org/abs/1902.02597v1
• [cs.CV]Neural Inverse Knitting: From Images to Manufacturing Instructions
Alexandre Kaspar, Tae-Hyun Oh, Liane Makatura, Petr Kellnhofer, Jacqueline Aslarus, Wojciech Matusik
http://arxiv.org/abs/1902.02752v1
• [cs.CV]Real-time 3D Traffic Cone Detection for Autonomous Driving
Ankit Dhall, Dengxin Dai, Luc Van Gool
http://arxiv.org/abs/1902.02394v1
• [cs.CV]Reversible GANs for Memory-efficient Image-to-Image Translation
Tycho F. A. van der Ouderaa, Daniel E. Worrall
http://arxiv.org/abs/1902.02729v1
• [cs.CV]Single Network Panoptic Segmentation for Street Scene Understanding
Daan de Geus, Panagiotis Meletis, Gijs Dubbelman
http://arxiv.org/abs/1902.02678v1
• [cs.CV]StampNet: unsupervised multi-class object discovery
Joost Visser, Alessandro Corbetta, Vlado Menkovski, Federico Toschi
http://arxiv.org/abs/1902.02693v1
• [cs.CV]Theoretical analysis on Noise2Noise using Stein's Unbiased Risk Estimator for Gaussian denoising: Towards unsupervised training with clipped noisy images
Magauiya Zhussip, Shakarim Soltanayev, Se Young Chun
http://arxiv.org/abs/1902.02452v1
• [cs.CV]Unsupervised Data Uncertainty Learning in Visual Retrieval Systems
Ahmed Taha, Yi-Ting Chen, Teruhisa Misu, Abhinav Shrivastava, Larry Davis
http://arxiv.org/abs/1902.02586v1
• [cs.CV]Virtual Training for a Real Application: Accurate Object-Robot Relative Localization without Calibration
Vianney Loing, Renaud Marlet, Mathieu Aubry
http://arxiv.org/abs/1902.02711v1
• [cs.DC]Hop: Heterogeneity-Aware Decentralized Training
Qinyi Luo, Jinkun Lin, Youwei Zhuo, Xuehai Qian
http://arxiv.org/abs/1902.01064v2
• [cs.DC]PAI Data, Summary of the Project PAI Data Protocol
Jincheng Du, Dan Fang, Mark Harvilla
http://arxiv.org/abs/1902.02470v1
• [cs.DC]Prospective Hybrid Consensus for Project PAI
Mark Harvilla, Jincheng Du
http://arxiv.org/abs/1902.02469v1
• [cs.DC]Random Gossip Processes in Smartphone Peer-to-Peer Networks
Calvin Newport, Alex Weaver
http://arxiv.org/abs/1902.02763v1
• [cs.DC]Storm: a fast transactional dataplane for remote data structures
Stanko Novakovic, Yizhou Shan, Aasheesh Kolli, Michael Cui, Yiying Zhang, Haggai Eran, Liran Liss, Michael Wei, Dan Tsafrir, Marcos Aguilera
http://arxiv.org/abs/1902.02411v1
• [cs.HC]Are Children Fully Aware of Online Privacy Risks and How Can We Improve Their Coping Ability?
Ge Wang, Jun Zhao, Nigel Shadbolt
http://arxiv.org/abs/1902.02635v1
• [cs.IR]A Comparison of Information Retrieval Techniques for Detecting Source Code Plagiarism
Vasishtha Sriram Jayapati, Ajay Venkitaraman
http://arxiv.org/abs/1902.02407v1
• [cs.IR]A Network-centric Framework for Auditing Recommendation Systems
Abhisek Dash, Animesh Mukherjee, Saptarshi Ghosh
http://arxiv.org/abs/1902.02710v1
• [cs.IR]The few-get-richer: a surprising consequence of popularity-based rankings
Fabrizio Germano, Vicenç Gómez, Gaël Le Mens
http://arxiv.org/abs/1902.02580v1
• [cs.IT]A Random Access G-Network: Stability, Stable Throughput, and Queueing Analysis
Ioannis Dimitriou, Nikolaos Pappas
http://arxiv.org/abs/1902.02697v1
• [cs.IT]Asymmetric Construction of Low-Latency and Length-Flexible Polar Codes
Adam Cavatassi, Thibaud Tonnellier, Warren J. Gross
http://arxiv.org/abs/1902.02402v1
• [cs.IT]Eigenvalue Based Detection of a Signal in Colored Noise: Finite and Asymptotic Analyses
Lahiru D. Chamain, Prathapasinghe Dharmawansa, Saman Atapattu, Chintha Tellambura
http://arxiv.org/abs/1902.02483v1
• [cs.IT]Massive MIMO Multicast Beamforming Via Accelerated Random Coordinate Descent
Shuai Wang, Lei Cheng, Minghua Xia, Yik-Chung Wu
http://arxiv.org/abs/1902.02447v1
• [cs.IT]Rank-metric codes
Elisa Gorla
http://arxiv.org/abs/1902.02650v1
• [cs.IT]Safeguarding Wireless Network with UAVs: A Physical Layer Security Perspective
Qingqing Wu, Weidong Mei, Rui Zhang
http://arxiv.org/abs/1902.02472v1
• [cs.LG]A Simple Baseline for Bayesian Uncertainty in Deep Learning
Wesley Maddox, Timur Garipov, Pavel Izmailov, Dmitry Vetrov, Andrew Gordon Wilson
http://arxiv.org/abs/1902.02476v1
• [cs.LG]Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
Tiago Ramalho, Marta Garnelo
http://arxiv.org/abs/1902.02527v1
• [cs.LG]Adversarial Domain Adaptation for Stance Detection
Brian Xu, Mitra Mohtarami, James Glass
http://arxiv.org/abs/1902.02401v1
• [cs.LG]Artificial Intelligence for Prosthetics - challenge solutions
Łukasz Kidziński, Carmichael Ong, Sharada Prasanna Mohanty, Jennifer Hicks, Sean F. Carroll, Bo Zhou, Hongsheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaśkowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy Watson, Marcel Salathé, Sergey Levine, Scott Delp
http://arxiv.org/abs/1902.02441v1
• [cs.LG]BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
Asa Cooper Stickland, Iain Murray
http://arxiv.org/abs/1902.02671v1
• [cs.LG]Bounds for the VC Dimension of 1NN Prototype Sets
Iain A. D. Gunn, Ludmila I. Kuncheva
http://arxiv.org/abs/1902.02660v1
• [cs.LG]Centroid-based deep metric learning for speaker recognition
Jixuan Wang, Kuan-Chieh Wang, Marc Law, Frank Rudzicz, Michael Brudno
http://arxiv.org/abs/1902.02375v1
• [cs.LG]Deeper & Sparser Exploration
Divya Grover, Christos Dimitrakakis
http://arxiv.org/abs/1902.02661v1
• [cs.LG]DiffEqFlux.jl - A Julia Library for Neural Differential Equations
Chris Rackauckas, Mike Innes, Yingbo Ma, Jesse Bettencourt, Lyndon White, Vaibhav Dixit
http://arxiv.org/abs/1902.02376v1
• [cs.LG]Effectiveness of LSTMs in Predicting Congestive Heart Failure Onset
Sunil Mallya, Marc Overhage, Navneet Srivastava, Tatsuya Arai, Cole Erdman
http://arxiv.org/abs/1902.02443v1
• [cs.LG]Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives
Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh
http://arxiv.org/abs/1902.02416v1
• [cs.LG]Global Explanations of Neural Networks: Mapping the Landscape of Predictions
Mark Ibrahim, Melissa Louie, Ceena Modarres, John Paisley
http://arxiv.org/abs/1902.02384v1
• [cs.LG]Graph Classification with Recurrent Variational Neural Networks
Edouard Pineau, Nathan de Lara
http://arxiv.org/abs/1902.02721v1
• [cs.LG]Hybrid Models with Deep and Invertible Features
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Gorur, Balaji Lakshminarayanan
http://arxiv.org/abs/1902.02767v1
• [cs.LG]KLUCB Approach to Copeland Bandits
Nischal Agrawal, Prasanna Chaporkar
http://arxiv.org/abs/1902.02778v1
• [cs.LG]Metaoptimization on a Distributed System for Deep Reinforcement Learning
Greg Heinrich, Iuri Frosio
http://arxiv.org/abs/1902.02725v1
• [cs.LG]Negative eigenvalues of the Hessian in deep neural networks
Guillaume Alain, Nicolas Le Roux, Pierre-Antoine Manzagol
http://arxiv.org/abs/1902.02366v1
• [cs.LG]Neural Network Attributions: A Causal Perspective
Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar, Vineeth N Balasubramanian
http://arxiv.org/abs/1902.02302v2
• [cs.LG]On the Variance of Unbiased Online Recurrent Optimization
Tim Cooijmans, James Martens
http://arxiv.org/abs/1902.02405v1
• [cs.LG]Online Clustering by Penalized Weighted GMM
Shlomo Bugdary, Shay Maymon
http://arxiv.org/abs/1902.02544v1
• [cs.LG]Principal Model Analysis Based on Partial Least Squares
Qiwei Xie, Liang Tang, Weifu Li, Vijay John, Yong Hu
http://arxiv.org/abs/1902.02422v1
• [cs.LG]Sparse Regression and Adaptive Feature Generation for the Discovery of Dynamical Systems
Chinmay S. Kulkarni
http://arxiv.org/abs/1902.02719v1
• [cs.LG]Spatial Mixture Models with Learnable Deep Priors for Perceptual Grouping
Jinyang Yuan, Bin Li, Xiangyang Xue
http://arxiv.org/abs/1902.02502v1
• [cs.LG]Speeding up scaled gradient projection methods using deep neural networks for inverse problems in image processing
Byung Hyun Lee, Se Young Chun
http://arxiv.org/abs/1902.02449v1
• [cs.LG]Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis
Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten Borgwardt
http://arxiv.org/abs/1902.01659v2
• [cs.LG]The role of a layer in deep neural networks: a Gaussian Process perspective
Oded Ben-David, Zohar Ringel
http://arxiv.org/abs/1902.02354v1
• [cs.MA]CESMA: Centralized Expert Supervises Multi-Agents
Alex Tong Lin, Mark J. Debord, Katia Estabridis, Gary Hewer, Stanley Osher
http://arxiv.org/abs/1902.02311v2
• [cs.NE]Investigating RNN Memory using Neuro-Evolution: Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution
Alexander Ororbia, Ahmed Ahmed Elsaid, Travis Desell
http://arxiv.org/abs/1902.02390v1
• [cs.NE]Self-Adjusting Mutation Rates with Provably Optimal Success Rules
Benjamin Doerr, Carola Doerr, Johannes Lengler
http://arxiv.org/abs/1902.02588v1
• [cs.RO]Commodifying Pointing in HRI: Simple and Fast Pointing Gesture Detection from RGB-D Images
Bita Azari, Angelica Lim, Richard T. Vaughan
http://arxiv.org/abs/1902.02636v1
• [cs.RO]Integer Programming as a General Solution Methodology for Path-Based Optimization in Robotics: Principles and Best Practices
Shuai D. Han, Jingjin Yu
http://arxiv.org/abs/1902.02652v1
• [cs.SE]A Manually-Curated Dataset of Fixes to Vulnerabilities of Open-Source Software
Serena E. Ponta, Henrik Plate, Antonino Sabetta, Michele Bezzi, Cédric Dangremont
http://arxiv.org/abs/1902.02595v1
• [cs.SI]Modeling and Analysis of Tagging Networks in Stack Exchange Communities
Xiang Fu, Shangdi Yu, Austin R. Benson
http://arxiv.org/abs/1902.02372v1
• [cs.SI]Red Bots Do It Better Comparative Analysis of Social Bot Partisan Behavior
Luca Luceri, Ashok Deb, Adam Badawy, Emilio Ferrara
http://arxiv.org/abs/1902.02765v1
• [eess.AS]Conv-codes: Audio Hashing For Bird Species Classification
Anshul Thakur, Pulkit Sharma, Vinayak Abrol, Padmanabhan Rajan
http://arxiv.org/abs/1902.02498v1
• [eess.AS]End-to-end losses based on speaker basis vectors and all-speaker hard negative mining for speaker verification
Hee-Soo Heo, Jee-weon Jung, IL-Ho Yang, Sung-Hyun Yoon, Hye-jin Shim, Ha-Jin Yu
http://arxiv.org/abs/1902.02455v1
• [eess.IV]DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling
Sunghwan Joo, Sungmin Cha, Taesup Moon
http://arxiv.org/abs/1902.02530v1
• [eess.IV]SAPSAM - Sparsely Annotated Pathological Sign Activation Maps - A novel approach to train Convolutional Neural Networks on lung CT scans using binary labels only
Mario Zusag, Sujal Desai, Marcello Di Paolo, Thomas Semple, Anand Shah, Elsa Angelini
http://arxiv.org/abs/1902.02629v1
• [eess.SP]Wireless Networks Design in the Era of Deep Learning: Model-Based, AI-Based, or Both?
Alessio Zappone, Marco Di Renzo, Mérouane Debbah
http://arxiv.org/abs/1902.02647v1
• [math.OC]Momentum Schemes with Stochastic Variance Reduction for Nonconvex Composite Optimization
Yi Zhou, Zhe Wang, Kaiyi Ji, Yingbin Liang, Vahid Tarokh
http://arxiv.org/abs/1902.02715v1
• [math.OC]Predict Globally, Correct Locally: Parallel-in-Time Optimal Control of Neural Networks
Panos Parpas, Corey Muir
http://arxiv.org/abs/1902.02542v1
• [math.PR]On the asymptotic optimality of the comb strategy for prediction with expert advice
Erhan Bayraktar, Ibrahim Ekren, Yili Zhang
http://arxiv.org/abs/1902.02368v1
• [math.PR]Subadditivity Beyond Trees and the Chi-Squared Mutual Information
Emmanuel Abbe, Enric Boix-Adserà
http://arxiv.org/abs/1902.02431v1
• [math.ST]Consistent Risk Estimation in High-Dimensional Linear Regression
Ji Xu, Arian Maleki, Kamiar Rahnama Rad
http://arxiv.org/abs/1902.01753v2
• [math.ST]Cramér Type Moderate Deviations for Random Fields
Aleksandr Beknazaryan, Hailin Sang, Yimin Xiao
http://arxiv.org/abs/1902.02723v1
• [math.ST]Estimation of smooth densities in Wasserstein distance
Jonathan Weed, Quentin Berthet
http://arxiv.org/abs/1902.01778v2
• [math.ST]Tail behavior of dependent V-statistics and its applications
Yandi Shen, Fang Han, Daniela Witten
http://arxiv.org/abs/1902.02761v1
• [math.ST]Weak consistency of the 1-nearest neighbor measure with applications to missing data and covariate shift
James Sharpnack
http://arxiv.org/abs/1902.02408v1
• [physics.data-an]Field dynamics inference for local and causal interactions
Philipp Frank, Reimar Leike, Torsten A. Enßlin
http://arxiv.org/abs/1902.02624v1
• [physics.soc-ph]Anti-modular nature of partially bipartite networks makes them infra small-world
Aradhana Singh, Md. Izhar Ashraf, Sitabhra Sinha
http://arxiv.org/abs/1902.02668v1
• [quant-ph]Entropy Bound for the Classical Capacity of a Quantum Channel Assisted by Classical Feedback
Dawei Ding, Yihui Quek, Peter W. Shor, Mark M. Wilde
http://arxiv.org/abs/1902.02490v1
• [stat.AP]Ensemble Prediction of Time to Event Outcomes with Competing Risks: A Case Study of Surgical Complications in Crohn's Disease
Michael C Sachs, Andrea Discacciati, Åsa Everhov, Ola Olén, Erin E Gabriel
http://arxiv.org/abs/1902.02533v1
• [stat.AP]Winning Is Not Everything: A contextual analysis of hockey face-offs
Nick Czuzoj-Shulman, David Yu, Christopher Boucher, Luke Bornn, Mehrsan Javan
http://arxiv.org/abs/1902.02397v1
• [stat.ME]Bias-Aware Confidence Intervals for Empirical Bayes Analysis
Nikolaos Ignatiadis, Stefan Wager
http://arxiv.org/abs/1902.02774v1
• [stat.ME]Modeling microbial abundances and dysbiosis with beta-binomial regression
Bryan D. Martin, Daniela Witten, Amy D. Willis
http://arxiv.org/abs/1902.02776v1
• [stat.ML]A Bayesian Approach for Accurate Classification-Based Aggregates
Q. A. Meertens, C. G. H. Diks, H. J. van den Herik, F W Takes
http://arxiv.org/abs/1902.02412v1
• [stat.ML]A Scale Invariant Flatness Measure for Deep Network Minima
Akshay Rangamani, Nam H. Nguyen, Abhishek Kumar, Dzung Phan, Sang H. Chin, Trac D. Tran
http://arxiv.org/abs/1902.02434v1
• [stat.ML]Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise
Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon
http://arxiv.org/abs/1902.02509v1
• [stat.ML]Cost-Effective Incentive Allocation via Structured Counterfactual Inference
Romain Lopez, Chenchen Li, Xiang Yan, Junwu Xiong, Michael I. Jordan, Yuan Qi, Le Song
http://arxiv.org/abs/1902.02495v1
• [stat.ML]Model Selection for Simulator-based Statistical Models: A Kernel Approach
Takafumi Kajihara, Motonobu Kanagawa, Yuuki Nakaguchi, Kanishka Khandelwal, Kenji Fukumiziu
http://arxiv.org/abs/1902.02517v1
• [stat.ML]Radial and Directional Posteriors for Bayesian Neural Networks
Changyong Oh, Kamil Adamczewski, Mijung Park
http://arxiv.org/abs/1902.02603v1
• [stat.ML]Random Matrix Improved Covariance Estimation for a Large Class of Metrics
Malik Tiomoko, Florent Bouchard, Guillaume Ginholac, Romain Couillet
http://arxiv.org/abs/1902.02554v1
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