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今日学术视野(2019.1.30)

今日学术视野(2019.1.30)

作者: ZQtGe6 | 来源:发表于2019-01-30 05:45 被阅读110次

    cs.AI - 人工智能
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DC - 分布式、并行与集群计算
    cs.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.NI - 网络和互联网体系结构
    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
    econ.GN - 一般经济学
    eess.IV - 图像与视频处理
    eess.SP - 信号处理
    math-ph - 数学物理
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    physics.comp-ph - 计算物理学
    q-bio.QM - 定量方法
    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
    stat.OT - 其他统计学

    • [cs.AI]It could be worse, it could be raining: reliable automatic meteorological forecasting
    • [cs.AI]Multi-Agent Generalized Recursive Reasoning
    • [cs.AI]Strong Equivalence and Program's Structure in Arguing Essential Equivalence between Logic Programs
    • [cs.CL]A new evaluation framework for topic modeling algorithms based on synthetic corpora
    • [cs.CL]Analogies Explained: Towards Understanding Word Embeddings
    • [cs.CL]Dual Co-Matching Network for Multi-choice Reading Comprehension
    • [cs.CL]Evaluating Word Embedding Models: Methods and Experimental Results
    • [cs.CL]Implicit Dimension Identification in User-Generated Text with LSTM Networks
    • [cs.CL]Language Independent Sequence Labelling for Opinion Target Extraction
    • [cs.CL]Language Model Pre-training for Hierarchical Document Representations
    • [cs.CL]Neural Related Work Summarization with a Joint Context-driven Attention Mechanism
    • [cs.CL]Personalized Dialogue Generation with Diversified Traits
    • [cs.CL]Promoting Diversity for End-to-End Conversation Response Generation
    • [cs.CL]Toward Unsupervised Text Content Manipulation
    • [cs.CL]Variational Smoothing in Recurrent Neural Network Language Models
    • [cs.CR]The CATS Hackathon: Creating and Refining Test Items for Cybersecurity Concept Inventories
    • [cs.CV]3D Contouring for Breast Tumor in Sonography
    • [cs.CV]4D Generic Video Object Proposals
    • [cs.CV]6D Object Pose Estimation Based on 2D Bounding Box
    • [cs.CV]Attribute-Guided Sketch Generation
    • [cs.CV]Audio-Visual Scene-Aware Dialog
    • [cs.CV]Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study
    • [cs.CV]Bridging the Gap Between Computational Photography and Visual Recognition
    • [cs.CV]CURE: Curvature Regularization For Missing Data Recovery
    • [cs.CV]Challenges in Designing Datasets and Validation for Autonomous Driving
    • [cs.CV]CoCoNet: A Collaborative Convolutional Network
    • [cs.CV]CollaGAN : Collaborative GAN for Missing Image Data Imputation
    • [cs.CV]Convolutional Neural Networks with Layer Reuse
    • [cs.CV]Deep Convolutional Encoder-Decoders with Aggregated Multi-Resolution Skip Connections for Skin Lesion Segmentation
    • [cs.CV]DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression
    • [cs.CV]Degraded Historical Documents Images Binarization Using a Combination of Enhanced Techniques
    • [cs.CV]DistInit: Learning Video Representations without a Single Labeled Video
    • [cs.CV]Edge, Ridge, and Blob Detection with Symmetric Molecules
    • [cs.CV]End-to-End Discriminative Deep Network for Liver Lesion Classification
    • [cs.CV]Enhancing Quality for VVC Compressed Videos by Jointly Exploiting Spatial Details and Temporal Structure
    • [cs.CV]Fast Hierarchical Depth Map Computation from Stereo
    • [cs.CV]Generalization of feature embeddings transferred from different video anomaly detection domains
    • [cs.CV]Human Pose Estimation using Motion Priors and Ensemble Models
    • [cs.CV]Learning Transformation Synchronization
    • [cs.CV]Leveraging Outdoor Webcams for Local Descriptor Learning
    • [cs.CV]Monocular Depth Estimation: A Survey
    • [cs.CV]Multi-modal dialog for browsing large visual catalogs using exploration-exploitation paradigm in a joint embedding space
    • [cs.CV]NeuralSampler: Euclidean Point Cloud Auto-Encoder and Sampler
    • [cs.CV]On Detecting GANs and Retouching based Synthetic Alterations
    • [cs.CV]Open Source Face Recognition Performance Evaluation Package
    • [cs.CV]Points2Pix: 3D Point-Cloud to Image Translation using conditional Generative Adversarial Networks
    • [cs.CV]Progressive Image Deraining Networks: A Better and Simpler Baseline
    • [cs.CV]Real-time Video Summarization on Commodity Hardware
    • [cs.CV]Resultant Based Incremental Recovery of Camera Pose from Pairwise Matches
    • [cs.CV]Scene Text Synthesis for Efficient and Effective Deep Network Training
    • [cs.CV]Soft labeling by Distilling Anatomical knowledge for Improved MS Lesion Segmentation
    • [cs.CV]Spatio-temporal Action Recognition: A Survey
    • [cs.CV]Watermark Signal Detection and Its Application in Image Retrieval
    • [cs.CY]"And We Will Fight For Our Race!'" A Measurement Study of Genetic Testing Conversations on Reddit and 4chan
    • [cs.CY]Is Privacy Controllable?
    • [cs.CY]Leveraging Data Driven Approaches to Quantify the Impact of Construction Projects on Urban Quality of Life
    • [cs.CY]On the mapping of Points of Interest through StreetView imagery and paid crowdsourcing
    • [cs.DC]A Comprehensive Survey on Parallelization and Elasticity in Stream Processing
    • [cs.DC]Heterogeneity-aware Gradient Coding for Straggler Tolerance
    • [cs.DC]Optimal and Automated Deployment for Microservices
    • [cs.DC]Robust Dynamic Resource Allocation via Probabilistic Task Pruning in Heterogeneous Computing Systems
    • [cs.DC]SimBlock: A Blockchain Network Simulator
    • [cs.IR]Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
    • [cs.IT]An Information-Theoretic Explanation for the Adversarial Fragility of AI Classifiers
    • [cs.IT]Capacity Optimality of AMP in Coded Systems
    • [cs.IT]Capacity of Single-Server Single-Message Private Information Retrieval with Private Coded Side Information
    • [cs.IT]Closed-form performance analysis of linear MIMO receivers in general fading scenarios
    • [cs.IT]Communication Complexity of Estimating Correlations
    • [cs.IT]Concurrent Coding: A Reason to Think Differently About Encoding Against Noise, Burst Errors and Jamming
    • [cs.IT]Coverage and Rate Analysis of Downlink Cellular Vehicle-to-Everything (C-V2X) Communication
    • [cs.IT]Detection of a Signal in Colored Noise: A Random Matrix Theory Based Analysis
    • [cs.IT]Energy-Efficient Resource Allocation for Secure UAV Communication Systems
    • [cs.IT]Generalized Alignment Chain: Improved Converse Results for Index Coding
    • [cs.IT]On Peak Age of Information in Data Preprocessing enabled IoT Networks
    • [cs.IT]Optimal Online Transmission Policy in Wireless Powered Networks with Urgency-aware Age of Information
    • [cs.IT]Orthogonal Time Frequency Space (OTFS) Modulation Based Radar System
    • [cs.IT]Secrecy Outage Analysis of Non-Orthogonal Spectrum Sharing for Heterogeneous Cellular Networks
    • [cs.IT]Secrecy Throughput Maximization for Full-Duplex Wireless Powered IoT Networks under Fairness Constraints
    • [cs.IT]Steiner systems S(2, 4, \frac{3^m-1}{2}) and 2-designs from ternary linear codes of length \frac{3^m-1}{2}
    • [cs.IT]Techniques for System Information Broadcast in Cell-Free Massive MIMO
    • [cs.IT]Towards an Extremal Network Theory -- Robust GDoF Gain of Transmitter Cooperation over TIN
    • [cs.IT]Tradeoff Between Delay and High SNR Capacity in Quantized MIMO Systems
    • [cs.LG]99% of Parallel Optimization is Inevitably a Waste of Time
    • [cs.LG]A general model for plane-based clustering with loss function
    • [cs.LG]Action Robust Reinforcement Learning and Applications in Continuous Control
    • [cs.LG]Activation Adaptation in Neural Networks
    • [cs.LG]Adversarial Examples Target Topological Holes in Deep Networks
    • [cs.LG]Anomaly detecting and ranking of the cloud computing platform by multi-view learning
    • [cs.LG]Atrous Convolutional Neural Network (ACNN) for Biomedical Semantic Segmentation with Dimensionally Lossless Feature Maps
    • [cs.LG]Augment your batch: better training with larger batches
    • [cs.LG]Black Box Submodular Maximization: Discrete and Continuous Settings
    • [cs.LG]CLIC: Curriculum Learning and Imitation for feature Control in non-rewarding environments
    • [cs.LG]CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks
    • [cs.LG]Complex-Valued Neural Networks for Privacy Protection
    • [cs.LG]Concrete Autoencoders for Differentiable Feature Selection and Reconstruction
    • [cs.LG]DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks
    • [cs.LG]Deconstructing Generative Adversarial Networks
    • [cs.LG]Depth creates no more spurious local minima
    • [cs.LG]Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour Algorithm
    • [cs.LG]Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals
    • [cs.LG]Distributed Learning with Compressed Gradient Differences
    • [cs.LG]Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees
    • [cs.LG]ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding
    • [cs.LG]Error Feedback Fixes SignSGD and other Gradient Compression Schemes
    • [cs.LG]Escaping Saddle Points with Adaptive Gradient Methods
    • [cs.LG]Fairness in representation: quantifying stereotyping as a representational harm
    • [cs.LG]Fairwashing: the risk of rationalization
    • [cs.LG]Fixup Initialization: Residual Learning Without Normalization
    • [cs.LG]From-Below Boolean Matrix Factorization Algorithm Based on MDL
    • [cs.LG]Graphical-model based estimation and inference for differential privacy
    • [cs.LG]How Sensitive are Sensitivity-Based Explanations?
    • [cs.LG]Hybrid Machine Learning Approach to Popularity Prediction of Newly Released Contents for Online Video Streaming Service
    • [cs.LG]ICLR Reproducibility Challenge Report (Padam : Closing The Generalization Gap Of Adaptive Gradient Methods in Training Deep Neural Networks)
    • [cs.LG]Imitation Learning from Imperfect Demonstration
    • [cs.LG]Improved Accounting for Differentially Private Learning
    • [cs.LG]Improving Neural Network Quantization using Outlier Channel Splitting
    • [cs.LG]Ising Models with Latent Conditional Gaussian Variables
    • [cs.LG]Large-Scale Classification using Multinomial Regression and ADMM
    • [cs.LG]ML for Flood Forecasting at Scale
    • [cs.LG]Making Deep Q-learning methods robust to time discretization
    • [cs.LG]Money on the Table: Statistical information ignored by Softmax can improve classifier accuracy
    • [cs.LG]Neural eliminators and classifiers
    • [cs.LG]Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift
    • [cs.LG]On Learning Invariant Representation for Domain Adaptation
    • [cs.LG]On the Universality of Invariant Networks
    • [cs.LG]Out-of-Sample Testing for GANs
    • [cs.LG]Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
    • [cs.LG]PruneTrain: Gradual Structured Pruning from Scratch for Faster Neural Network Training
    • [cs.LG]Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
    • [cs.LG]Reward Shaping via Meta-Learning
    • [cs.LG]SGD: General Analysis and Improved Rates
    • [cs.LG]Secure multi-party linear regression at plaintext speed
    • [cs.LG]SelectiveNet: A Deep Neural Network with an Integrated Reject Option
    • [cs.LG]Semi-supervised Learning in Network-Structured Data via Total Variation Minimization
    • [cs.LG]Squeezed Very Deep Convolutional Neural Networks for Text Classification
    • [cs.LG]Stacking and stability
    • [cs.LG]Stiffness: A New Perspective on Generalization in Neural Networks
    • [cs.LG]Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the O(1/T) Convergence Rate
    • [cs.LG]Stochastic Linear Bandits with Hidden Low Rank Structure
    • [cs.LG]Stopping Active Learning based on Predicted Change of F Measure for Text Classification
    • [cs.LG]Strong Black-box Adversarial Attacks on Unsupervised Machine Learning Models
    • [cs.LG]Support Feature Machines
    • [cs.LG]Target Tracking for Contextual Bandits: Application to Demand Side Management
    • [cs.LG]The Use of Unlabeled Data versus Labeled Data for Stopping Active Learning for Text Classification
    • [cs.LG]TuckER: Tensor Factorization for Knowledge Graph Completion
    • [cs.LG]Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
    • [cs.LG]Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces
    • [cs.NE]A Simple Method to Reduce Off-chip Memory Accesses on Convolutional Neural Networks
    • [cs.NE]Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets
    • [cs.NE]Intrinsically Sparse Long Short-Term Memory Networks
    • [cs.NE]Multi Objective Particle Swarm Optimization based Cooperative Agents with Automated Negotiation
    • [cs.NE]Progressive Label Distillation: Learning Input-Efficient Deep Neural Networks
    • [cs.NE]Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware
    • [cs.NI]Spectrum Data Poisoning with Adversarial Deep Learning
    • [cs.RO]Active Localization of Gas Leaks using Fluid Simulation
    • [cs.RO]Bayesian Active Learning for Collaborative Task Specification Using Equivalence Regions
    • [cs.RO]Contact-Implicit Optimization of Locomotion Trajectories for a Quadrupedal Microrobot
    • [cs.RO]Context-aware Monitoring in Robotic Surgery
    • [cs.RO]Globally Optimal Registration based on Fast Branch and Bound
    • [cs.RO]Modeling and Simulation of Robotic Finger Powered by Nylon Artificial Muscles- Equations with Simulink model
    • [cs.RO]Online Estimation of Ocean Current from Sparse GPS Data for Underwater Vehicles
    • [cs.RO]Streamlines for Motion Planning in Underwater Currents
    • [cs.SD]End-to-End Multi-Task Denoising for joint SDR and PESQ Optimization
    • [cs.SI]GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks
    • [cs.SI]Predicting Tomorrow's Headline using Today's Twitter Deliberations
    • [cs.SI]User Donations in a Crowdsourced Video System
    • [cs.SY]Estimating multi-year 24/7 origin-destination demand using high-granular multi-source traffic data
    • [cs.SY]Physical Access Control Management System Based on Permissioned Blockchain
    • [econ.GN]Intensity estimation of transaction arrivals on the intraday electricity market
    • [eess.IV]A deep learning-based method for prostate segmentation in T2-weighted magnetic resonance imaging
    • [eess.SP]A Two-staged Adaptive Successive Cancellation List Decoding for Polar Codes
    • [math-ph]Bures-Hall Ensemble: Spectral Densities and Average Entropies
    • [math.OC]A Privacy Preserving Randomized Gossip Algorithm via Controlled Noise Insertion
    • [math.OC]Asynchronous Accelerated Proximal Stochastic Gradient for Strongly Convex Distributed Finite Sums
    • [math.PR]On strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables
    • [math.ST]Asymptotics of maximum likelihood estimation for stable law with (M) parameterization
    • [math.ST]Change-point detection in a linear model by adaptive fused quantile method
    • [math.ST]Exact Good-Turing characterization of the two-parameter Poisson-Dirichlet superpopulation model
    • [math.ST]Nonparametric relative error estimation of the regression function for censored data
    • [math.ST]On the unified zero-inflated cure-rate survival models
    • [math.ST]Reconciling the Bayes Factor and Likelihood Ratio for Two Non-Nested Model Selection Problems
    • [physics.comp-ph]Acceleration of the NVT-flash calculation for multicomponent mixtures using deep neural network models
    • [q-bio.QM]Tumor Connectomics: Mapping the intra-tumoral complex interaction network
    • [quant-ph]Coherence Optimization in Neutron Interferometry through Defocussing
    • [quant-ph]Supervised Learning Enhanced by an Entangled Sensor Network
    • [stat.AP]A Structured Approach to the Analysis of Remote Sensing Images
    • [stat.AP]A computational method for estimating Burr XII parameters with complete and multiple censored data
    • [stat.AP]Galton-Watson process and bayesian inference: A turnkey method for the viability study of small populations
    • [stat.AP]RefCurv: A Software for the Construction of Pediatric Reference Curves
    • [stat.AP]Volatility Models Applied to Geophysics and High Frequency Financial Market Data
    • [stat.ME]A Multi-parameter regression model for interval censored survival data
    • [stat.ME]A Spatially Discrete Approximation to Log-Gaussian Cox Processes for Modelling Aggregated Disease Count Data
    • [stat.ME]A dynamic stochastic blockmodel for interaction lengths
    • [stat.ME]Clustering Discrete Valued Time Series
    • [stat.ME]Effect sizes of the differences between means without assuming the variance equality and between a mean and a constant
    • [stat.ME]Eficient Monte Carlo Simulation of the Left Tail of Positive Gaussian Quadratic Forms
    • [stat.ME]Joint models as latent Gaussian models - not reinventing the wheel
    • [stat.ME]Markov-Modulated Linear Regression
    • [stat.ME]On doubly robust estimation for logistic partially linear models
    • [stat.ME]Propensity Score Matching underestimates Treatment Effect, in a simulated theoretical multivariate model
    • [stat.ME]Separable Effects for Causal Inference in the Presence of Competing Risks
    • [stat.ME]The Robust Kernel Association Test
    • [stat.ML]A Practical Bandit Method with Advantages in Neural Network Tuning
    • [stat.ML]An analytic formulation for positive-unlabeled learning via weighted integral probability metric
    • [stat.ML]Disentangling in Variational Autoencoders with Natural Clustering
    • [stat.ML]Improved Causal Discovery from Longitudinal Data Using a Mixture of DAGs
    • [stat.ML]Information-Theoretic Understanding of Population Risk Improvement with Model Compression
    • [stat.ML]Interpreting Deep Neural Networks Through Variable Importance
    • [stat.ML]On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
    • [stat.ML]On Symmetric Losses for Learning from Corrupted Labels
    • [stat.ML]Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets
    • [stat.OT]Shannon's entropy and its Generalizations towards Statistics, Reliability and Information Science during 1948-2018

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

    • [cs.AI]It could be worse, it could be raining: reliable automatic meteorological forecasting
    Matteo Cristani, Francesco Domenichini, Claudio Tomazzoli1, Luca Viganò, Margherita Zorzi
    http://arxiv.org/abs/1901.09867v1

    • [cs.AI]Multi-Agent Generalized Recursive Reasoning
    Ying Wen, Yaodong Yang, Rui Lu, Jun Wang
    http://arxiv.org/abs/1901.09216v1

    • [cs.AI]Strong Equivalence and Program's Structure in Arguing Essential Equivalence between Logic Programs
    Yuliya Lierler
    http://arxiv.org/abs/1901.09127v1

    • [cs.CL]A new evaluation framework for topic modeling algorithms based on synthetic corpora
    Hanyu Shi, Martin Gerlach, Isabel Diersen, Doug Downey, Luis A. N. Amaral
    http://arxiv.org/abs/1901.09848v1

    • [cs.CL]Analogies Explained: Towards Understanding Word Embeddings
    Carl Allen, Timothy Hospedales
    http://arxiv.org/abs/1901.09813v1

    • [cs.CL]Dual Co-Matching Network for Multi-choice Reading Comprehension
    Shuailiang Zhang, Hai Zhao, Yuwei Wu, Zhuosheng Zhang, Xi Zhou, Xiang Zhou
    http://arxiv.org/abs/1901.09381v1

    • [cs.CL]Evaluating Word Embedding Models: Methods and Experimental Results
    Bin Wang, Angela Wang, Fenxiao Chen, Yunchen Wang, C. -C. Jay Kuo
    http://arxiv.org/abs/1901.09785v1

    • [cs.CL]Implicit Dimension Identification in User-Generated Text with LSTM Networks
    Victor Makarenkov, Ido Guy, Niva Hatzen, Tamar Meisels, Bracha Shapira, Lior Rokach
    http://arxiv.org/abs/1901.09219v1

    • [cs.CL]Language Independent Sequence Labelling for Opinion Target Extraction
    Rodrigo Agerri, German Rigau
    http://arxiv.org/abs/1901.09755v1

    • [cs.CL]Language Model Pre-training for Hierarchical Document Representations
    Ming-Wei Chang, Kristina Toutanova, Kenton Lee, Jacob Devlin
    http://arxiv.org/abs/1901.09128v1

    • [cs.CL]Neural Related Work Summarization with a Joint Context-driven Attention Mechanism
    Yongzhen Wang, Xiaozhong Liu, Zheng Gao
    http://arxiv.org/abs/1901.09492v1

    • [cs.CL]Personalized Dialogue Generation with Diversified Traits
    Yinhe Zheng, Guanyi Chen, Minlie Huang, Song Liu, Xuan Zhu
    http://arxiv.org/abs/1901.09672v1

    • [cs.CL]Promoting Diversity for End-to-End Conversation Response Generation
    Yu-Ping Ruan, Zhen-Hua Ling, Quan Liu, Jia-Chen Gu, Xiaodan Zhu
    http://arxiv.org/abs/1901.09444v1

    • [cs.CL]Toward Unsupervised Text Content Manipulation
    Wentao Wang, Zhiting Hu, Zichao Yang, Haoran Shi, Frank Xu, Eric Xing
    http://arxiv.org/abs/1901.09501v1

    • [cs.CL]Variational Smoothing in Recurrent Neural Network Language Models
    Lingpeng Kong, Gabor Melis, Wang Ling, Lei Yu, Dani Yogatama
    http://arxiv.org/abs/1901.09296v1

    • [cs.CR]The CATS Hackathon: Creating and Refining Test Items for Cybersecurity Concept Inventories
    Alan T. Sherman, Linda Oliva, Enis Golaszewski, Dhananjay Phatak, Travis Scheponik, Geoffrey L. Herman, Dong San Choi, Spencer E. Offenberger, Peter Peterson, Josiah Dykstra, Gregory V. Bard, Ankur Chattopadhyay, Filipo Sharevski, Rakesh Verma, Ryan Vrecenar
    http://arxiv.org/abs/1901.09286v1

    • [cs.CV]3D Contouring for Breast Tumor in Sonography
    Yu-Len Huang, PhD, Dar-Ren Chen, MD, Yu-Chih Lin
    http://arxiv.org/abs/1901.09407v1

    • [cs.CV]4D Generic Video Object Proposals
    Aljosa Osep, Paul Voigtlaender, Mark Weber, Jonathon Luiten, Bastian Leibe
    http://arxiv.org/abs/1901.09260v1

    • [cs.CV]6D Object Pose Estimation Based on 2D Bounding Box
    Jin Liu, Sheng He
    http://arxiv.org/abs/1901.09366v1

    • [cs.CV]Attribute-Guided Sketch Generation
    Hao Tang, Xinya Chen, Wei Wang, Dan Xu, Jason J. Corso, Nicu Sebe, Yan Yan
    http://arxiv.org/abs/1901.09774v1

    • [cs.CV]Audio-Visual Scene-Aware Dialog
    Huda Alamri, Vincent Cartillier, Abhishek Das, Jue Wang, Stefan Lee, Peter Anderson, Irfan Essa, Devi Parikh, Dhruv Batra, Anoop Cherian, Tim K. Marks, Chiori Hori
    http://arxiv.org/abs/1901.09107v1

    • [cs.CV]Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study
    Robert Robinson, Vanya V. Valindria, Wenjia Bai, Ozan Oktay, Bernhard Kainz, Hideaki Suzuki, Mihir M. Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kim, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Paul M. Matthews, Daniel Rueckert, Ben Glocker
    http://arxiv.org/abs/1901.09351v1

    • [cs.CV]Bridging the Gap Between Computational Photography and Visual Recognition
    Rosaura G. VidalMata, Sreya Banerjee, Brandon RichardWebster, Michael Albright, Pedro Davalos, Scott McCloskey, Ben Miller, Asong Tambo, Sushobhan Ghosh, Sudarshan Nagesh, Ye Yuan, Yueyu Hu, Junru Wu, Wenhan Yang, Xiaoshuai Zhang, Jiaying Liu, Zhangyang Wang, Hwann-Tzong Chen, Tzu-Wei Huang, Wen-Chi Chin, Yi-Chun Li, Mahmoud Lababidi, Charles Otto, Walter J. Scheirer
    http://arxiv.org/abs/1901.09482v1

    • [cs.CV]CURE: Curvature Regularization For Missing Data Recovery
    Bin Dong, Haocheng Ju, Yiping Lu, Zuoqiang Shi
    http://arxiv.org/abs/1901.09548v1

    • [cs.CV]Challenges in Designing Datasets and Validation for Autonomous Driving
    Michal Uricar, David Hurych, Pavel Krizek, Senthil Yogamani
    http://arxiv.org/abs/1901.09270v1

    • [cs.CV]CoCoNet: A Collaborative Convolutional Network
    Tapabrata Chakraborti, Brendan McCane, Steven Mills, Umapada Pal
    http://arxiv.org/abs/1901.09886v1

    • [cs.CV]CollaGAN : Collaborative GAN for Missing Image Data Imputation
    Dongwook Lee, Junyoung Kim, Won-Jin Moon, Jong Chul Ye
    http://arxiv.org/abs/1901.09764v1

    • [cs.CV]Convolutional Neural Networks with Layer Reuse
    Okan Köpüklü, Maryam Babaee, Gerhard Rigoll
    http://arxiv.org/abs/1901.09615v1

    • [cs.CV]Deep Convolutional Encoder-Decoders with Aggregated Multi-Resolution Skip Connections for Skin Lesion Segmentation
    Ahmed H. Shahin, Karim Amer, Mustafa A. Elattar
    http://arxiv.org/abs/1901.09197v1

    • [cs.CV]DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression
    Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao, Franck Cappello
    http://arxiv.org/abs/1901.09124v1

    • [cs.CV]Degraded Historical Documents Images Binarization Using a Combination of Enhanced Techniques
    Omar Boudraa, Walid Khaled Hidouci, Dominique Michelucci
    http://arxiv.org/abs/1901.09425v1

    • [cs.CV]DistInit: Learning Video Representations without a Single Labeled Video
    Rohit Girdhar, Du Tran, Lorenzo Torresani, Deva Ramanan
    http://arxiv.org/abs/1901.09244v1

    • [cs.CV]Edge, Ridge, and Blob Detection with Symmetric Molecules
    Rafael Reisenhofer, Emily J. King
    http://arxiv.org/abs/1901.09723v1

    • [cs.CV]End-to-End Discriminative Deep Network for Liver Lesion Classification
    Francisco Perdigon Romero, Andre Diler, Gabriel Bisson-Gregoire, Simon Turcotte, Real Lapointe, Franck Vandenbroucke-Menu, An Tang, Samuel Kadoury
    http://arxiv.org/abs/1901.09483v1

    • [cs.CV]Enhancing Quality for VVC Compressed Videos by Jointly Exploiting Spatial Details and Temporal Structure
    Xiandong Meng, Xuan Deng, Shuyuan Zhu, Bing Zeng
    http://arxiv.org/abs/1901.09575v1

    • [cs.CV]Fast Hierarchical Depth Map Computation from Stereo
    Vinay Kaushik, Brejesh Lall
    http://arxiv.org/abs/1901.09593v1

    • [cs.CV]Generalization of feature embeddings transferred from different video anomaly detection domains
    Fernando Pereira dos Santos, Leonardo Sampaio Ferraz Ribeiro, Moacir Antonelli Ponti
    http://arxiv.org/abs/1901.09819v1

    • [cs.CV]Human Pose Estimation using Motion Priors and Ensemble Models
    Norimichi Ukita
    http://arxiv.org/abs/1901.09156v1

    • [cs.CV]Learning Transformation Synchronization
    Xiangru Huang, Zhenxiao Liang, Xiaowei Zhou, Yao Xie, Leonidas Guibas, Qixing Huang
    http://arxiv.org/abs/1901.09458v1

    • [cs.CV]Leveraging Outdoor Webcams for Local Descriptor Learning
    Milan Pultar, Dmytro Mishkin, Jiří Matas
    http://arxiv.org/abs/1901.09780v1

    • [cs.CV]Monocular Depth Estimation: A Survey
    Amlaan Bhoi
    http://arxiv.org/abs/1901.09402v1

    • [cs.CV]Multi-modal dialog for browsing large visual catalogs using exploration-exploitation paradigm in a joint embedding space
    Arkabandhu Chowdhury, Indrani Bhattacharya, Vikas Raykar
    http://arxiv.org/abs/1901.09854v1

    • [cs.CV]NeuralSampler: Euclidean Point Cloud Auto-Encoder and Sampler
    Edoardo Remelli, Pierre Baque, Pascal Fua
    http://arxiv.org/abs/1901.09394v1

    • [cs.CV]On Detecting GANs and Retouching based Synthetic Alterations
    Anubhav Jain, Richa Singh, Mayank Vatsa
    http://arxiv.org/abs/1901.09237v1

    • [cs.CV]Open Source Face Recognition Performance Evaluation Package
    Xiang Xu, Ioannis A. Kakadiaris
    http://arxiv.org/abs/1901.09447v1

    • [cs.CV]Points2Pix: 3D Point-Cloud to Image Translation using conditional Generative Adversarial Networks
    Stefan Milz, Martin Simon, Kai Fischer, Maximillian Pöpperl
    http://arxiv.org/abs/1901.09280v1

    • [cs.CV]Progressive Image Deraining Networks: A Better and Simpler Baseline
    Dongwei Ren, Wangmeng Zuo, Qinghua Hu, Pengfei Zhu, Deyu Meng
    http://arxiv.org/abs/1901.09221v1

    • [cs.CV]Real-time Video Summarization on Commodity Hardware
    Wesley Taylor, Faisal Z. Qureshi
    http://arxiv.org/abs/1901.09287v1

    • [cs.CV]Resultant Based Incremental Recovery of Camera Pose from Pairwise Matches
    Yoni Kasten, Meirav Galun, Ronen Basri
    http://arxiv.org/abs/1901.09364v1

    • [cs.CV]Scene Text Synthesis for Efficient and Effective Deep Network Training
    Fangneng Zhan, Hongyuan Zhu, Shijian Lu
    http://arxiv.org/abs/1901.09193v1

    • [cs.CV]Soft labeling by Distilling Anatomical knowledge for Improved MS Lesion Segmentation
    Eytan Kats, Jacob Goldberger, Hayit Greenspan
    http://arxiv.org/abs/1901.09263v1

    • [cs.CV]Spatio-temporal Action Recognition: A Survey
    Amlaan Bhoi
    http://arxiv.org/abs/1901.09403v1

    • [cs.CV]Watermark Signal Detection and Its Application in Image Retrieval
    Ning Ma, Josh Zhao, Mark Bolin
    http://arxiv.org/abs/1901.09473v1

    • [cs.CY]"And We Will Fight For Our Race!'" A Measurement Study of Genetic Testing Conversations on Reddit and 4chan
    Alexandros Mittos, Savvas Zannettou, Jeremy Blackburn, Emiliano De Cristofaro
    http://arxiv.org/abs/1901.09735v1

    • [cs.CY]Is Privacy Controllable?
    Yefim Shulman, Joachim Meyer
    http://arxiv.org/abs/1901.09804v1

    • [cs.CY]Leveraging Data Driven Approaches to Quantify the Impact of Construction Projects on Urban Quality of Life
    Zhengbo Zou, Semiha Ergan
    http://arxiv.org/abs/1901.09084v1

    • [cs.CY]On the mapping of Points of Interest through StreetView imagery and paid crowdsourcing
    Eddy Maddalena, Luis-Daniel Ibáñez, Elena Simperl
    http://arxiv.org/abs/1901.09264v1

    • [cs.DC]A Comprehensive Survey on Parallelization and Elasticity in Stream Processing
    Henriette Röger, Ruben Mayer
    http://arxiv.org/abs/1901.09716v1

    • [cs.DC]Heterogeneity-aware Gradient Coding for Straggler Tolerance
    Haozhao Wang, Song Guo, Bin Tang, Ruixuan Li, Chengjie Li
    http://arxiv.org/abs/1901.09339v1

    • [cs.DC]Optimal and Automated Deployment for Microservices
    Mario Bravetti, Saverio Giallorenzo, Jacopo Mauro, Iacopo Talevi, Gianluigi Zavattaro
    http://arxiv.org/abs/1901.09782v1

    • [cs.DC]Robust Dynamic Resource Allocation via Probabilistic Task Pruning in Heterogeneous Computing Systems
    James Gentry, Chavit Denninnart, Mohsen Amini Salehi
    http://arxiv.org/abs/1901.09312v1

    • [cs.DC]SimBlock: A Blockchain Network Simulator
    Yusuke Aoki, Kai Otsuki, Takeshi Kaneko, Ryohei Banno, Kazuyuki Shudo
    http://arxiv.org/abs/1901.09777v1

    • [cs.IR]Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
    Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
    http://arxiv.org/abs/1901.09451v1

    • [cs.IT]An Information-Theoretic Explanation for the Adversarial Fragility of AI Classifiers
    Hui Xie, Jirong Yi, Weiyu Xu, Raghu Mudumbai
    http://arxiv.org/abs/1901.09413v1

    • [cs.IT]Capacity Optimality of AMP in Coded Systems
    Lei Liu, Chulong Liang, Junjie Ma, Li Ping
    http://arxiv.org/abs/1901.09559v1

    • [cs.IT]Capacity of Single-Server Single-Message Private Information Retrieval with Private Coded Side Information
    Anoosheh Heidarzadeh, Fatemeh Kazemi, Alex Sprintson
    http://arxiv.org/abs/1901.09248v1

    • [cs.IT]Closed-form performance analysis of linear MIMO receivers in general fading scenarios
    M. Kieburg, G. Akemann, G. Alfano, G. Caire
    http://arxiv.org/abs/1901.09740v1

    • [cs.IT]Communication Complexity of Estimating Correlations
    Uri Hadar, Jingbo Liu, Yury Polyanskiy, Ofer Shayevitz
    http://arxiv.org/abs/1901.09100v1

    • [cs.IT]Concurrent Coding: A Reason to Think Differently About Encoding Against Noise, Burst Errors and Jamming
    David M Benton
    http://arxiv.org/abs/1901.09646v1

    • [cs.IT]Coverage and Rate Analysis of Downlink Cellular Vehicle-to-Everything (C-V2X) Communication
    Vishnu Vardhan Chetlur, Harpreet S. Dhillon
    http://arxiv.org/abs/1901.09236v1

    • [cs.IT]Detection of a Signal in Colored Noise: A Random Matrix Theory Based Analysis
    Lahiru D. Chamain, Prathapasinghe Dharmawansa, Saman Atapattu, Chintha Tellambura
    http://arxiv.org/abs/1901.09568v1

    • [cs.IT]Energy-Efficient Resource Allocation for Secure UAV Communication Systems
    Yuanxin Cai, Zhiqiang Wei, Ruide Li, Derrick Wing Kwan Ng, Jinhong Yuan
    http://arxiv.org/abs/1901.09308v1

    • [cs.IT]Generalized Alignment Chain: Improved Converse Results for Index Coding
    Yucheng Liu, Parastoo Sadeghi
    http://arxiv.org/abs/1901.09183v1

    • [cs.IT]On Peak Age of Information in Data Preprocessing enabled IoT Networks
    Chao Xu, Howard H. Yang, Xijun Wang, Tony Q. S. Quek
    http://arxiv.org/abs/1901.09376v1

    • [cs.IT]Optimal Online Transmission Policy in Wireless Powered Networks with Urgency-aware Age of Information
    Yang Lu, Ke Xiong, Pingyi Fan, Zhangdui Zhong, Khaled Ben Letaief
    http://arxiv.org/abs/1901.09232v1

    • [cs.IT]Orthogonal Time Frequency Space (OTFS) Modulation Based Radar System
    P. Raviteja, Khoa T. Phan, Yi Hong, Emanuele Viterbo
    http://arxiv.org/abs/1901.09300v1

    • [cs.IT]Secrecy Outage Analysis of Non-Orthogonal Spectrum Sharing for Heterogeneous Cellular Networks
    Yulong~Zou, Tong Wu, Ming~Sun, Jia~Zhu, Mujun~Qian, Chen Liu
    http://arxiv.org/abs/1901.09417v1

    • [cs.IT]Secrecy Throughput Maximization for Full-Duplex Wireless Powered IoT Networks under Fairness Constraints
    Roohollah Rezaei, Sumei Sun, Fellow, IEEE, Xin Kang, Member, IEEE, Yong Liang Guan, Senior Member, IEEE, Mohammad Reza Pakravan, Member, IEEE
    http://arxiv.org/abs/1901.09631v1

    • [cs.IT]Steiner systems S(2, 4, \frac{3^m-1}{2}) and 2-designs from ternary linear codes of length \frac{3^m-1}{2}
    Chunming Tang, Cunsheng Ding, Maosheng Xiong
    http://arxiv.org/abs/1901.09228v1

    • [cs.IT]Techniques for System Information Broadcast in Cell-Free Massive MIMO
    Marcus Karlsson, Emil Björnson, Erik G. Larsson
    http://arxiv.org/abs/1901.09554v1

    • [cs.IT]Towards an Extremal Network Theory -- Robust GDoF Gain of Transmitter Cooperation over TIN
    Yao-Chia Chan, Junge Wang, Syed A. Jafar
    http://arxiv.org/abs/1901.09885v1

    • [cs.IT]Tradeoff Between Delay and High SNR Capacity in Quantized MIMO Systems
    Abbas Khalili, Farhad Shirani, Elza Erkip, Yonina C. Eldar
    http://arxiv.org/abs/1901.09844v1

    • [cs.LG]99% of Parallel Optimization is Inevitably a Waste of Time
    Konstantin Mishchenko, Filip Hanzely, Peter Richtárik
    http://arxiv.org/abs/1901.09437v1

    • [cs.LG]A general model for plane-based clustering with loss function
    Zhen Wang, Yuan-Hai Shao, Lan Bai, Chun-Na Li, Li-Ming Liu
    http://arxiv.org/abs/1901.09178v1

    • [cs.LG]Action Robust Reinforcement Learning and Applications in Continuous Control
    Chen Tessler, Yonathan Efroni, Shie Mannor
    http://arxiv.org/abs/1901.09184v1

    • [cs.LG]Activation Adaptation in Neural Networks
    Farnoush Farhadi, Vahid Partovi Nia, Andrea Lodi
    http://arxiv.org/abs/1901.09849v1

    • [cs.LG]Adversarial Examples Target Topological Holes in Deep Networks
    Thomas Gebhart, Paul Schrater
    http://arxiv.org/abs/1901.09496v1

    • [cs.LG]Anomaly detecting and ranking of the cloud computing platform by multi-view learning
    Jing Zhang
    http://arxiv.org/abs/1901.09294v1

    • [cs.LG]Atrous Convolutional Neural Network (ACNN) for Biomedical Semantic Segmentation with Dimensionally Lossless Feature Maps
    Xiao-Yun Zhou, Jian-Qing Zheng, Guang-Zhong Yang
    http://arxiv.org/abs/1901.09203v1

    • [cs.LG]Augment your batch: better training with larger batches
    Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry
    http://arxiv.org/abs/1901.09335v1

    • [cs.LG]Black Box Submodular Maximization: Discrete and Continuous Settings
    Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi
    http://arxiv.org/abs/1901.09515v1

    • [cs.LG]CLIC: Curriculum Learning and Imitation for feature Control in non-rewarding environments
    Pierre Fournier, Olivier Sigaud, Mohamed Chetouani, Cédric Colas
    http://arxiv.org/abs/1901.09720v1

    • [cs.LG]CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks
    Alberto Marchisio, Giorgio Nanfa, Faiq Khalid, Muhammad Abdullah Hanif, Maurizio Martina, Muhammad Shafique
    http://arxiv.org/abs/1901.09878v1

    • [cs.LG]Complex-Valued Neural Networks for Privacy Protection
    Liyao Xiang, Haotian Ma, Hao Zhang, Yifan Zhang, Quanshi Zhang
    http://arxiv.org/abs/1901.09546v1

    • [cs.LG]Concrete Autoencoders for Differentiable Feature Selection and Reconstruction
    Abubakar Abid, Muhammad Fatih Balin, James Zou
    http://arxiv.org/abs/1901.09346v1

    • [cs.LG]DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks
    Xingjian Li, Haoyi Xiong, Hanchao Wang, Yuxuan Rao, Liping Liu, Jun Huan
    http://arxiv.org/abs/1901.09229v1

    • [cs.LG]Deconstructing Generative Adversarial Networks
    Banghua Zhu, Jiantao Jiao, David Tse
    http://arxiv.org/abs/1901.09465v1

    • [cs.LG]Depth creates no more spurious local minima
    Li Zhang
    http://arxiv.org/abs/1901.09827v1

    • [cs.LG]Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour Algorithm
    Ricards Marcinkevics, Steven Kelk, Carlo Galuzzi, Berthold Stegemann
    http://arxiv.org/abs/1901.09187v1

    • [cs.LG]Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals
    Thomas Moreau, Alexandre Gramfort
    http://arxiv.org/abs/1901.09235v1

    • [cs.LG]Distributed Learning with Compressed Gradient Differences
    Konstantin Mishchenko, Eduard Gorbunov, Martin Takáč, Peter Richtárik
    http://arxiv.org/abs/1901.09269v1

    • [cs.LG]Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees
    Abdul Karim, Avinash Mishra, M A Hakim Newton, Abdul Sattar
    http://arxiv.org/abs/1901.09240v1

    • [cs.LG]ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding
    Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos
    http://arxiv.org/abs/1901.09671v1

    • [cs.LG]Error Feedback Fixes SignSGD and other Gradient Compression Schemes
    Sai Praneeth Karimireddy, Quentin Rebjock, Sebastian U. Stich, Martin Jaggi
    http://arxiv.org/abs/1901.09847v1

    • [cs.LG]Escaping Saddle Points with Adaptive Gradient Methods
    Matthew Staib, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar, Suvrit Sra
    http://arxiv.org/abs/1901.09149v1

    • [cs.LG]Fairness in representation: quantifying stereotyping as a representational harm
    Mohsen Abbasi, Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian
    http://arxiv.org/abs/1901.09565v1

    • [cs.LG]Fairwashing: the risk of rationalization
    Ulrich Aïvodji, Hiromi Arai, Olivier Fortineau, Sébastien Gambs, Satoshi Hara, Alain Tapp
    http://arxiv.org/abs/1901.09749v1

    • [cs.LG]Fixup Initialization: Residual Learning Without Normalization
    Hongyi Zhang, Yann N. Dauphin, Tengyu Ma
    http://arxiv.org/abs/1901.09321v1

    • [cs.LG]From-Below Boolean Matrix Factorization Algorithm Based on MDL
    Tatiana Makhalova, Martin Trnecka
    http://arxiv.org/abs/1901.09567v1

    • [cs.LG]Graphical-model based estimation and inference for differential privacy
    Ryan McKenna, Daniel Sheldon, Gerome Miklau
    http://arxiv.org/abs/1901.09136v1

    • [cs.LG]How Sensitive are Sensitivity-Based Explanations?
    Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David Inouye, Pradeep Ravikumar
    http://arxiv.org/abs/1901.09392v1

    • [cs.LG]Hybrid Machine Learning Approach to Popularity Prediction of Newly Released Contents for Online Video Streaming Service
    Hongjun Jeon, Wonchul Seo, Eunjeong Lucy Park, Sungchul Choi
    http://arxiv.org/abs/1901.09613v1

    • [cs.LG]ICLR Reproducibility Challenge Report (Padam : Closing The Generalization Gap Of Adaptive Gradient Methods in Training Deep Neural Networks)
    Harshal Mittal, Kartikey Pandey, Yash Kant
    http://arxiv.org/abs/1901.09517v1

    • [cs.LG]Imitation Learning from Imperfect Demonstration
    Yueh-Hua Wu, Nontawat Charoenphakdee, Han Bao, Voot Tangkaratt, Masashi Sugiyama
    http://arxiv.org/abs/1901.09387v1

    • [cs.LG]Improved Accounting for Differentially Private Learning
    Aleksei Triastcyn, Boi Faltings
    http://arxiv.org/abs/1901.09697v1

    • [cs.LG]Improving Neural Network Quantization using Outlier Channel Splitting
    Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang
    http://arxiv.org/abs/1901.09504v1

    • [cs.LG]Ising Models with Latent Conditional Gaussian Variables
    Frank Nussbaum, Joachim Giesen
    http://arxiv.org/abs/1901.09712v1

    • [cs.LG]Large-Scale Classification using Multinomial Regression and ADMM
    Samy Wu Fung, Sanna Tyrväinen, Lars Ruthotto, Eldad Haber
    http://arxiv.org/abs/1901.09450v1

    • [cs.LG]ML for Flood Forecasting at Scale
    Sella Nevo, Vova Anisimov, Gal Elidan, Ran El-Yaniv, Pete Giencke, Yotam Gigi, Avinatan Hassidim, Zach Moshe, Mor Schlesinger, Guy Shalev, Ajai Tirumali, Ami Wiesel, Oleg Zlydenko, Yossi Matias
    http://arxiv.org/abs/1901.09583v1

    • [cs.LG]Making Deep Q-learning methods robust to time discretization
    Corentin Tallec, Léonard Blier, Yann Ollivier
    http://arxiv.org/abs/1901.09732v1

    • [cs.LG]Money on the Table: Statistical information ignored by Softmax can improve classifier accuracy
    Charles B. Delahunt, Courosh Mehanian, J. Nathan Kutz
    http://arxiv.org/abs/1901.09283v1

    • [cs.LG]Neural eliminators and classifiers
    Włodzisław Duch, Rafał Adamczak, Yoichi Hayashi
    http://arxiv.org/abs/1901.09632v1

    • [cs.LG]Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift
    Carles Gelada, Marc G. Bellemare
    http://arxiv.org/abs/1901.09455v1

    • [cs.LG]On Learning Invariant Representation for Domain Adaptation
    Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoffrey J. Gordon
    http://arxiv.org/abs/1901.09453v1

    • [cs.LG]On the Universality of Invariant Networks
    Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman
    http://arxiv.org/abs/1901.09342v1

    • [cs.LG]Out-of-Sample Testing for GANs
    Pablo Sánchez-Martín, Pablo M. Olmos, Fernando Pérez-Cruz
    http://arxiv.org/abs/1901.09557v1

    • [cs.LG]Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
    Ying Wen, Yaodong Yang, Rui Luo, Jun Wang, Wei Pan
    http://arxiv.org/abs/1901.09207v1

    • [cs.LG]PruneTrain: Gradual Structured Pruning from Scratch for Faster Neural Network Training
    Sangkug Lym, Esha Choukse, Siavash Zangeneh, Wei Wen, Mattan Erez, Sujay Shanghavi
    http://arxiv.org/abs/1901.09290v1

    • [cs.LG]Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
    Kefan Dong, Yuanhao Wang, Xiaoyu Chen, Liwei Wang
    http://arxiv.org/abs/1901.09311v1

    • [cs.LG]Reward Shaping via Meta-Learning
    Haosheng Zou, Tongzheng Ren, Dong Yan, Hang Su, Jun Zhu
    http://arxiv.org/abs/1901.09330v1

    • [cs.LG]SGD: General Analysis and Improved Rates
    Robert Mansel Gower, Nicolas Loizou, Xun Qian, Alibek Sailanbayev, Egor Shulgin, Peter Richtarik
    http://arxiv.org/abs/1901.09401v1

    • [cs.LG]Secure multi-party linear regression at plaintext speed
    Jonathan M. Bloom
    http://arxiv.org/abs/1901.09531v1

    • [cs.LG]SelectiveNet: A Deep Neural Network with an Integrated Reject Option
    Yonatan Geifman, Ran El-Yaniv
    http://arxiv.org/abs/1901.09192v1

    • [cs.LG]Semi-supervised Learning in Network-Structured Data via Total Variation Minimization
    Alexander Jung, Alfred O. Hero III, Alexandru Mara, Saeed Jahromi, Ayelet Heimowitz, Yonina C. Eldar
    http://arxiv.org/abs/1901.09838v1

    • [cs.LG]Squeezed Very Deep Convolutional Neural Networks for Text Classification
    Andréa B. Duque, Luã Lázaro J. Santos, David Macêdo, Cleber Zanchettin
    http://arxiv.org/abs/1901.09821v1

    • [cs.LG]Stacking and stability
    Nino Arsov, Martin Pavlovski, Ljupco Kocarev
    http://arxiv.org/abs/1901.09134v1

    • [cs.LG]Stiffness: A New Perspective on Generalization in Neural Networks
    Stanislav Fort, Paweł Krzysztof Nowak, Srini Narayanan
    http://arxiv.org/abs/1901.09491v1

    • [cs.LG]Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the O(1/T) Convergence Rate
    Lijun Zhang, Zhi-Hua Zhou
    http://arxiv.org/abs/1901.09344v1

    • [cs.LG]Stochastic Linear Bandits with Hidden Low Rank Structure
    Sahin Lale, Kamyar Azizzadenesheli, Anima Anandkumar, Babak Hassibi
    http://arxiv.org/abs/1901.09490v1

    • [cs.LG]Stopping Active Learning based on Predicted Change of F Measure for Text Classification
    Michael Altschuler, Michael Bloodgood
    http://arxiv.org/abs/1901.09118v1

    • [cs.LG]Strong Black-box Adversarial Attacks on Unsupervised Machine Learning Models
    Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra
    http://arxiv.org/abs/1901.09493v1

    • [cs.LG]Support Feature Machines
    Tomasz Maszczyk, Włodzisław Duch
    http://arxiv.org/abs/1901.09643v1

    • [cs.LG]Target Tracking for Contextual Bandits: Application to Demand Side Management
    Margaux Brégère, Pierre Gaillard, Yannig Goude, Gilles Stoltz
    http://arxiv.org/abs/1901.09532v1

    • [cs.LG]The Use of Unlabeled Data versus Labeled Data for Stopping Active Learning for Text Classification
    Garrett Beatty, Ethan Kochis, Michael Bloodgood
    http://arxiv.org/abs/1901.09126v1

    • [cs.LG]TuckER: Tensor Factorization for Knowledge Graph Completion
    Ivana Balažević, Carl Allen, Timothy M. Hospedales
    http://arxiv.org/abs/1901.09590v1

    • [cs.LG]Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
    Chao Qu, Shie Mannor, Huan Xu, Yuan Qi, Le Song, Junwu Xiong
    http://arxiv.org/abs/1901.09326v1

    • [cs.LG]Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces
    Arash Mehrjou, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
    http://arxiv.org/abs/1901.09206v1

    • [cs.NE]A Simple Method to Reduce Off-chip Memory Accesses on Convolutional Neural Networks
    Doyun Kim, Kyoung-Young Kim, Sangsoo Ko, Sanghyuck Ha
    http://arxiv.org/abs/1901.09614v1

    • [cs.NE]Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets
    Guillaume Bellec, Franz Scherr, Elias Hajek, Darjan Salaj, Robert Legenstein, Wolfgang Maass
    http://arxiv.org/abs/1901.09049v1

    • [cs.NE]Intrinsically Sparse Long Short-Term Memory Networks
    Shiwei Liu, Decebal Constantin Mocanu, Mykola Pechenizkiy
    http://arxiv.org/abs/1901.09208v1

    • [cs.NE]Multi Objective Particle Swarm Optimization based Cooperative Agents with Automated Negotiation
    Najwa Kouka, Raja Fdhila, Adel M. Alimi
    http://arxiv.org/abs/1901.09292v1

    • [cs.NE]Progressive Label Distillation: Learning Input-Efficient Deep Neural Networks
    Zhong Qiu Lin, Alexander Wong
    http://arxiv.org/abs/1901.09135v1

    • [cs.NE]Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware
    Shiwei Liu, Decebal Constantin Mocanu, Amarsagar Reddy Ramapuram Matavalam, Yulong Pei, Mykola Pechenizkiy
    http://arxiv.org/abs/1901.09181v1

    • [cs.NI]Spectrum Data Poisoning with Adversarial Deep Learning
    Yi Shi, Tugba Erpek, Yalin E. Sagduyu, Jason H. Li
    http://arxiv.org/abs/1901.09247v1

    • [cs.RO]Active Localization of Gas Leaks using Fluid Simulation
    Martin Asenov, Marius Rutkauskas, Derryck Reid, Kartic Subr, Subramanian Ramamoorthy
    http://arxiv.org/abs/1901.09608v1

    • [cs.RO]Bayesian Active Learning for Collaborative Task Specification Using Equivalence Regions
    Nils Wilde, Dana Kulic, Stephen L. Smith
    http://arxiv.org/abs/1901.09470v1

    • [cs.RO]Contact-Implicit Optimization of Locomotion Trajectories for a Quadrupedal Microrobot
    Neel Doshi, Kaushik Jayaram, Benjamin Goldberg, Zachary Manchester, Robert J. Wood, Scott Kuindersma
    http://arxiv.org/abs/1901.09065v1

    • [cs.RO]Context-aware Monitoring in Robotic Surgery
    Mohammad Samin Yasar, David Evans, Homa Alemzadeh
    http://arxiv.org/abs/1901.09802v1

    • [cs.RO]Globally Optimal Registration based on Fast Branch and Bound
    Luca Consolini, Mattia Laurini, Marco Locatelli, Dario Lodi Rizzini
    http://arxiv.org/abs/1901.09641v1

    • [cs.RO]Modeling and Simulation of Robotic Finger Powered by Nylon Artificial Muscles- Equations with Simulink model
    Lokesh Saharan, Lianjun Wu, Yonas Tadesse
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