cs.AI - 人工智能
cs.CL - 计算与语言
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DC - 分布式、并行与集群计算
cs.DS - 数据结构与算法
cs.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.NI - 网络和互联网体系结构
cs.RO - 机器人学
cs.SD - 声音处理
cs.SE - 软件工程
cs.SI - 社交网络与信息网络
cs.SY - 系统与控制
econ.EM - 计量经济学
eess.SP - 信号处理
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
q-bio.GN - 基因组学
q-bio.NC - 神经元与认知
stat.AP - 应用统计
stat.CO - 统计计算
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [cs.AI]Constraint Satisfaction Propagation: Non-stationary Policy Synthesis for Temporal Logic Planning
• [cs.AI]Human-Centered Artificial Intelligence and Machine Learning
• [cs.AI]Visual Hindsight Experience Replay
• [cs.CL]A Generalized Language Model in Tensor Space
• [cs.CL]Adding Interpretable Attention to Neural Translation Models Improves Word Alignment
• [cs.CL]Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements
• [cs.CL]EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
• [cs.CL]Exploring the context of recurrent neural network based conversational agents
• [cs.CL]Learning Efficient Lexically-Constrained Neural Machine Translation with External Memory
• [cs.CL]Multi-Task Deep Neural Networks for Natural Language Understanding
• [cs.CL]Towards Controlled Transformation of Sentiment in Sentences
• [cs.CL]Unsupervised Text Style Transfer via Iterative Matching and Translation
• [cs.CV]A Convolutional Neural Network for the Automatic Diagnosis of Collagen VI related Muscular Dystrophies
• [cs.CV]A lossless data hiding scheme in JPEG images with segment coding
• [cs.CV]Automated brain extraction of multi-sequence MRI using artificial neural networks
• [cs.CV]Automated detection of celiac disease on duodenal biopsy slides: a deep learning approach
• [cs.CV]Chester: A Web Delivered Locally Computed Chest X-Ray Disease Prediction System
• [cs.CV]Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets
• [cs.CV]DDSL: Deep Differentiable Simplex Layer for Learning Geometric Signals
• [cs.CV]Efficient Relative Pose Estimation for Cameras and Generalized Cameras in Case of Known Relative Rotation Angle
• [cs.CV]GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
• [cs.CV]Human Face Expressions from Images - 2D Face Geometry and 3D Face Local Motion versus Deep Neural Features
• [cs.CV]Improving Model Robustness with Transformation-Invariant Attacks
• [cs.CV]Is Image Memorability Prediction Solved?
• [cs.CV]Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework
• [cs.CV]New insights on Multi-Solution Distribution of the P3P Problem
• [cs.CV]Noise2Self: Blind Denoising by Self-Supervision
• [cs.CV]On Intra-Class Variance for Deep Learning of Classifiers
• [cs.CV]Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks
• [cs.CV]Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images
• [cs.CV]Real-world Mapping of Gaze Fixations Using Instance Segmentation for Road Construction Safety Applications
• [cs.CV]Resolution enhancement in scanning electron microscopy using deep learning
• [cs.CV]Saliency detection for seismic applications using multi-dimensional spectral projections and directional comparisons
• [cs.CV]Semantic Hierarchy Preserving Deep Hashing for Large-scale Image Retrieval
• [cs.CV]Similar Image Search for Histopathology: SMILY
• [cs.CV]Texture-Aware Superpixel Segmentation
• [cs.CV]Three-dimensional propagation and time-reversal of fluorescence images
• [cs.CV]VAE-GANs for Probabilistic Compressive Image Recovery: Uncertainty Analysis
• [cs.CY]Building Knowledge Graphs About Political Agents in the Age of Misinformation
• [cs.CY]Software solutions for form-based collection of data and the semantic enrichment of form data
• [cs.DC]Accuracy vs. Efficiency: Achieving Both through FPGA-Implementation Aware Neural Architecture Search
• [cs.DC]Design and Evaluation of Smart-Contract-based System Operations for Permissioned Blockchain-based Systems
• [cs.DC]High Performance Algorithms for Counting Collisions and Pairwise Interactions
• [cs.DC]The OoO VLIW JIT Compiler for GPU Inference
• [cs.DS]A Pseudo-Deterministic RNC Algorithm for General Graph Perfect Matching
• [cs.HC]Shaping the Narrative Arc: An Information-Theoretic Approach to Collaborative Dialogue
• [cs.IR]An InfoVis Tool for Interactive Component-Based Evaluation
• [cs.IR]Comparing of Term Clustering Frameworks for Modular Ontology Learning
• [cs.IR]Conversational Networks for Automatic Online Moderation
• [cs.IT]A New Proof of Nonsignalling Multiprover Parallel Repetition Theorem
• [cs.IT]A Tractable Framework for Coverage Analysis of Cellular-Connected UAV Networks
• [cs.IT]Caching or No Caching in Dense HetNets?
• [cs.IT]Delay Analysis of Spatially-Coded MIMO-ZFBF with Retransmissions in Random Networks
• [cs.IT]Determining the Dimension and Structure of the Subspace Correlated Across Multiple Data Sets
• [cs.IT]Reed-Muller codes polarize
• [cs.IT]Spatial Soft-Core Caching
• [cs.IT]Statistics of the Nonlinear Discrete Spectrum of a Noisy Pulse
• [cs.IT]The Interference Channel Revisited: Eliminating Interference with a Two Antenna Receiver
• [cs.IT]Transportation Proof of an inequality by Anantharam, Jog and Nair
• [cs.LG]A Bad Arm Existence Checking Problem
• [cs.LG]A Comparative Analysis of Expected and Distributional Reinforcement Learning
• [cs.LG]A Geometric Perspective on Optimal Representations for Reinforcement Learning
• [cs.LG]A Theory of Regularized Markov Decision Processes
• [cs.LG]An Optimization Framework for Task Sequencing in Curriculum Learning
• [cs.LG]Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective
• [cs.LG]Deep Learning for Inverse Problems: Bounds and Regularizers
• [cs.LG]Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
• [cs.LG]Distributed Correlation-Based Feature Selection in Spark
• [cs.LG]Distributionally Robust Removal of Malicious Nodes from Networks
• [cs.LG]Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization
• [cs.LG]Effect of Various Regularizers on Model Complexities of Neural Networks in Presence of Input Noise
• [cs.LG]Emerging Convolutions for Generative Normalizing Flows
• [cs.LG]Feature-Critic Networks for Heterogeneous Domain Generalization
• [cs.LG]Funnelling: A New Ensemble Method for Heterogeneous Transfer Learning and its Application to Polylingual Text Classification
• [cs.LG]Generalized Dirichlet-process-means for f-separable distortion measures
• [cs.LG]High-dimensional Metric Combining for Non-coherent Molecular Signal Detection
• [cs.LG]HyperGAN: A Generative Model for Diverse, Performant Neural Networks
• [cs.LG]Hyperbox based machine learning algorithms: A comprehensive survey
• [cs.LG]Improving SGD convergence by tracing multiple promising directions and estimating distance to minimum
• [cs.LG]Learning and Evaluating General Linguistic Intelligence
• [cs.LG]Memory-Efficient Adaptive Optimization for Large-Scale Learning
• [cs.LG]Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty
• [cs.LG]Natural Analysts in Adaptive Data Analysis
• [cs.LG]New Tricks for Estimating Gradients of Expectations
• [cs.LG]On the Consistency of Top-k Surrogate Losses
• [cs.LG]Peer-to-peer Federated Learning on Graphs
• [cs.LG]ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization
• [cs.LG]Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization
• [cs.LG]Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition
• [cs.LG]Successor Features Support Model-based and Model-free Reinforcement Learning
• [cs.LG]The Evolved Transformer
• [cs.LG]The Value Function Polytope in Reinforcement Learning
• [cs.LG]The Wilderness Area Data Set: Adapting the Covertype data set for unsupervised learning
• [cs.LG]Toward Sensor-based Sleep Monitoring with Electrodermal Activity Measures
• [cs.LG]Unsupervised Prediction of Negative Health Events Ahead of Time
• [cs.MA]Priority Inheritance with Backtracking for Iterative Multi-agent Path Finding
• [cs.NE]Code Farming: A Process for Creating Generic Computational Building Blocks
• [cs.NE]Improving Evolutionary Strategies with Generative Neural Networks
• [cs.NE]Neuroevolution with Perceptron Turing Machines
• [cs.NE]Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution
• [cs.NI]Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications
• [cs.RO]A Data Driven Method of Optimizing Feedforward Compensator for Autonomous Vehicle
• [cs.RO]A test bed for measuring UAV servo reliability
• [cs.RO]Capturing Object Detection Uncertainty in Multi-Layer Grid Maps
• [cs.SD]Optimization of the Area Under the ROC Curve using Neural Network Supervectors for Text-Dependent Speaker Verification
• [cs.SE]Formal methods and software engineering for DL. Security, safety and productivity for DL systems development
• [cs.SI]Still out there: Modeling and Identifying Russian Troll Accounts on Twitter
• [cs.SY]Geometric fluid approximation for general continuous-time Markov chains
• [econ.EM]A dynamic factor model approach to incorporate Big Data in state space models for official statistics
• [eess.SP]Decomposition of Higher-Order Spectra for Blind Multiple-Input Deconvolution, Pattern Identification and Separation
• [math.OC]Lower Bounds for Smooth Nonconvex Finite-Sum Optimization
• [math.OC]Stochastic Recursive Variance-Reduced Cubic Regularization Methods
• [math.PR]Tight bounds on the convergence rate of generalized ratio consensus algorithms
• [math.ST]Improved mathematical models of statistical regularities in precipitation
• [q-bio.GN]GeNet: Deep Representations for Metagenomics
• [q-bio.NC]Sequential Bayesian Detection of Spike Activities from Fluorescence Observations
• [stat.AP]Bayesian nonparametric multiway regression for clustered binomial data
• [stat.CO]Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage
• [stat.ME]Causal Proportional Hazards Estimation with a Binary Instrumental Variable
• [stat.ME]Logistic Box-Cox Regression to Assess the Shape and Median Effect under Uncertainty about Model Specification
• [stat.ME]Propensity Score Matching underestimates Real Treatment Effect, in a simulated theoretical multivariate model
• [stat.ME]Random forests for high-dimensional longitudinal data
• [stat.ML]Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model
• [stat.ML]End-to-End Probabilistic Inference for Nonstationary Audio Analysis
• [stat.ML]Functional Regularisation for Continual Learning using Gaussian Processes
• [stat.ML]Metric Gaussian Variational Inference
• [stat.ML]Minimizing Negative Transfer of Knowledge in Multivariate Gaussian Processes: A Scalable and Regularized Approach
• [stat.ML]Multi-dimensional Tensor Sketch
• [stat.ML]Robust Inference via Generative Classifiers for Handling Noisy Labels
• [stat.ML]Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee
·····································
• [cs.AI]Constraint Satisfaction Propagation: Non-stationary Policy Synthesis for Temporal Logic Planning
Thomas J. Ringstrom, Paul R. Schrater
http://arxiv.org/abs/1901.10405v2
• [cs.AI]Human-Centered Artificial Intelligence and Machine Learning
Mark O. Riedl
http://arxiv.org/abs/1901.11184v1
• [cs.AI]Visual Hindsight Experience Replay
Himanshu Sahni, Toby Buckley, Pieter Abbeel, Ilya Kuzovkin
http://arxiv.org/abs/1901.11529v1
• [cs.CL]A Generalized Language Model in Tensor Space
Lipeng Zhang, Peng Zhang, Xindian Ma, Shuqin Gu, Zhan Su, Dawei Song
http://arxiv.org/abs/1901.11167v1
• [cs.CL]Adding Interpretable Attention to Neural Translation Models Improves Word Alignment
Thomas Zenkel, Joern Wuebker, John DeNero
http://arxiv.org/abs/1901.11359v1
• [cs.CL]Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements
Venkata Subrahmanyan Govindarajan, Benjamin Van Durme, Aaron Steven White
http://arxiv.org/abs/1901.11429v1
• [cs.CL]EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
Jason W. Wei, Kai Zou
http://arxiv.org/abs/1901.11196v1
• [cs.CL]Exploring the context of recurrent neural network based conversational agents
Raffaele Piccini, Gerasimos Spanakis
http://arxiv.org/abs/1901.11462v1
• [cs.CL]Learning Efficient Lexically-Constrained Neural Machine Translation with External Memory
Ya Li, Xinyu Liu, Dan Liu, Xueqiang Zhang, Junhua Liu
http://arxiv.org/abs/1901.11344v1
• [cs.CL]Multi-Task Deep Neural Networks for Natural Language Understanding
Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao
http://arxiv.org/abs/1901.11504v1
• [cs.CL]Towards Controlled Transformation of Sentiment in Sentences
Wouter Leeftink, Gerasimos Spanakis
http://arxiv.org/abs/1901.11467v1
• [cs.CL]Unsupervised Text Style Transfer via Iterative Matching and Translation
Zhijing Jin, Di Jin, Jonas Mueller, Nicholas Matthews, Enrico Santus
http://arxiv.org/abs/1901.11333v1
• [cs.CV]A Convolutional Neural Network for the Automatic Diagnosis of Collagen VI related Muscular Dystrophies
Adrián Bazaga, Mònica Roldán, Carmen Badosa, Cecilia Jiménez-Mallebrera, Josep M. Porta
http://arxiv.org/abs/1901.11074v1
• [cs.CV]A lossless data hiding scheme in JPEG images with segment coding
Mingming Zhang, Quan Zhou, Yanlang Hu
http://arxiv.org/abs/1901.11203v1
• [cs.CV]Automated brain extraction of multi-sequence MRI using artificial neural networks
Fabian Isensee, Marianne Schell, Irada Tursunova, Gianluca Brugnara, David Bonekamp, Ulf Neuberger, Antje Wick, Heinz-Peter Schlemmer, Sabine Heiland, Wolfgang Wick, Martin Bendszus, Klaus Hermann Maier-Hein, Philipp Kickingereder
http://arxiv.org/abs/1901.11341v1
• [cs.CV]Automated detection of celiac disease on duodenal biopsy slides: a deep learning approach
Jason W. Wei, Jerry W. Wei, Christopher R. Jackson, Bing Ren, Arief A. Suriawinata, Saeed Hassanpour
http://arxiv.org/abs/1901.11447v1
• [cs.CV]Chester: A Web Delivered Locally Computed Chest X-Ray Disease Prediction System
Joseph Paul Cohen, Paul Bertin, Vincent Frappier
http://arxiv.org/abs/1901.11210v1
• [cs.CV]Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets
Jue Jiang, Yu-Chi Hu, Neelam Tyagi, Pengpeng Zhang, Andreas Rimner, Joseph O. Deasy, Harini Veeraraghavan
http://arxiv.org/abs/1901.11369v1
• [cs.CV]DDSL: Deep Differentiable Simplex Layer for Learning Geometric Signals
Chiyu "Max" Jiang, Dana Lynn Ona Lansigan, Philip Marcus, Matthias Nießner
http://arxiv.org/abs/1901.11082v1
• [cs.CV]Efficient Relative Pose Estimation for Cameras and Generalized Cameras in Case of Known Relative Rotation Angle
Evgeniy Martyushev, Bo Li
http://arxiv.org/abs/1901.11357v1
• [cs.CV]GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger
http://arxiv.org/abs/1901.11461v1
• [cs.CV]Human Face Expressions from Images - 2D Face Geometry and 3D Face Local Motion versus Deep Neural Features
Rafal Pilarczyk, Xin Chang, Wladyslaw Skarbek
http://arxiv.org/abs/1901.11179v1
• [cs.CV]Improving Model Robustness with Transformation-Invariant Attacks
Houpu Yao, Zhe Wang, Guangyu Nie, Yassine Mazboudi, Yezhou Yang, Yi Ren
http://arxiv.org/abs/1901.11188v1
• [cs.CV]Is Image Memorability Prediction Solved?
Shay Perera, Ayellet Tal, Lihi Zelnik-Manor
http://arxiv.org/abs/1901.11420v1
• [cs.CV]Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework
Caiyong Wang, Yuhao Zhu, Yunfan Liu, Ran He, Zhenan Sun
http://arxiv.org/abs/1901.11195v1
• [cs.CV]New insights on Multi-Solution Distribution of the P3P Problem
Bo Wang, Hao Hu, Caixia Zhang
http://arxiv.org/abs/1901.11464v1
• [cs.CV]Noise2Self: Blind Denoising by Self-Supervision
Joshua Batson, Loic Royer
http://arxiv.org/abs/1901.11365v1
• [cs.CV]On Intra-Class Variance for Deep Learning of Classifiers
Rafal Pilarczyk, Wladyslaw Skarbek
http://arxiv.org/abs/1901.11186v1
• [cs.CV]Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks
Jason W. Wei, Laura J. Tafe, Yevgeniy A. Linnik, Louis J. Vaickus, Naofumi Tomita, Saeed Hassanpour
http://arxiv.org/abs/1901.11489v1
• [cs.CV]Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images
Haozhe Xie, Hongxun Yao, Xiaoshuai Sun, Shangchen Zhou, Shengping Zhang, Xiaojun Tong
http://arxiv.org/abs/1901.11153v1
• [cs.CV]Real-world Mapping of Gaze Fixations Using Instance Segmentation for Road Construction Safety Applications
Idris Jeelani, Khashayar Asadi, Hariharan Ramshankar, Kevin Han, Alex Albert
http://arxiv.org/abs/1901.11078v1
• [cs.CV]Resolution enhancement in scanning electron microscopy using deep learning
Kevin de Haan, Zachary S. Ballard, Yair Rivenson, Yichen Wu, Aydogan Ozcan
http://arxiv.org/abs/1901.11094v1
• [cs.CV]Saliency detection for seismic applications using multi-dimensional spectral projections and directional comparisons
Muhammad Amir Shafiq, Zhiling Long, Tariq Alshawi, Ghassan AlRegib
http://arxiv.org/abs/1901.11095v1
• [cs.CV]Semantic Hierarchy Preserving Deep Hashing for Large-scale Image Retrieval
Xuefei Zhe, Le Ou-Yang, Shifeng Chen, Hong Yan
http://arxiv.org/abs/1901.11259v1
• [cs.CV]Similar Image Search for Histopathology: SMILY
Narayan Hegde, Jason D. Hipp, Yun Liu, Michael E. Buck, Emily Reif, Daniel Smilkov, Michael Terry, Carrie J. Cai, Mahul B. Amin, Craig H. Mermel, Phil Q. Nelson, Lily H. Peng, Greg S. Corrado, Martin C. Stumpe
http://arxiv.org/abs/1901.11112v1
• [cs.CV]Texture-Aware Superpixel Segmentation
Remi Giraud, Vinh-Thong Ta, Nicolas Papadakis, Yannick Berthoumieu
http://arxiv.org/abs/1901.11111v1
• [cs.CV]Three-dimensional propagation and time-reversal of fluorescence images
Yichen Wu, Yair Rivenson, Hongda Wang, Yilin Luo, Eyal Ben-David, Aydogan Ozcan
http://arxiv.org/abs/1901.11252v1
• [cs.CV]VAE-GANs for Probabilistic Compressive Image Recovery: Uncertainty Analysis
Vineet Edupuganti, Morteza Mardani, Joseph Cheng, Shreyas Vasanawala, John Pauly
http://arxiv.org/abs/1901.11228v1
• [cs.CY]Building Knowledge Graphs About Political Agents in the Age of Misinformation
Daniel Schwabe, Carlos Laufer, Antonio Busson
http://arxiv.org/abs/1901.11408v1
• [cs.CY]Software solutions for form-based collection of data and the semantic enrichment of form data
Markus D. Steinberg
http://arxiv.org/abs/1901.11053v1
• [cs.DC]Accuracy vs. Efficiency: Achieving Both through FPGA-Implementation Aware Neural Architecture Search
Weiwen Jiang, Xinyi Zhang, Edwin H. -M. Sha, Lei Yang, Qingfeng Zhuge, Yiyu Shi, Jingtong Hu
http://arxiv.org/abs/1901.11211v1
• [cs.DC]Design and Evaluation of Smart-Contract-based System Operations for Permissioned Blockchain-based Systems
Tatsuya Sato, Yosuke Himura, Jun Nemoto
http://arxiv.org/abs/1901.11249v1
• [cs.DC]High Performance Algorithms for Counting Collisions and Pairwise Interactions
Matheus Henrique Junqueira Saldanha, Paulo Sérgio Lopes de Souza
http://arxiv.org/abs/1901.11204v1
• [cs.DC]The OoO VLIW JIT Compiler for GPU Inference
Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica
http://arxiv.org/abs/1901.10008v2
• [cs.DS]A Pseudo-Deterministic RNC Algorithm for General Graph Perfect Matching
Nima Anari, Vijay V. Vazirani
http://arxiv.org/abs/1901.10387v2
• [cs.HC]Shaping the Narrative Arc: An Information-Theoretic Approach to Collaborative Dialogue
Kory W. Mathewson, Pablo Samuel Castro, Colin Cherry, George Foster, Marc G. Bellemare
http://arxiv.org/abs/1901.11528v1
• [cs.IR]An InfoVis Tool for Interactive Component-Based Evaluation
Giacomo Rocco, Gianmaria Silvello
http://arxiv.org/abs/1901.11372v1
• [cs.IR]Comparing of Term Clustering Frameworks for Modular Ontology Learning
Ziwei Xu, Mounira Harzallah, Fabrice Guillet
http://arxiv.org/abs/1901.09037v1
• [cs.IR]Conversational Networks for Automatic Online Moderation
Etienne Papegnies, Vincent Labatut, Richard Dufour, Georges Linares
http://arxiv.org/abs/1901.11281v1
• [cs.IT]A New Proof of Nonsignalling Multiprover Parallel Repetition Theorem
Himanshu Tyagi, Shun Watanabe
http://arxiv.org/abs/1901.11105v1
• [cs.IT]A Tractable Framework for Coverage Analysis of Cellular-Connected UAV Networks
Xianghao Yu, Jun Zhang, Robert Schober, Khaled B. Letaief
http://arxiv.org/abs/1901.11326v1
• [cs.IT]Caching or No Caching in Dense HetNets?
M. G. Khoshkholgh, Keivan Navaie, Kang G. Shin, V. C. M. Leung, Halim Yanikomeroglu
http://arxiv.org/abs/1901.11068v1
• [cs.IT]Delay Analysis of Spatially-Coded MIMO-ZFBF with Retransmissions in Random Networks
Mohammad G. Khoshkholgh, Victor C. M. Leung
http://arxiv.org/abs/1901.11067v1
• [cs.IT]Determining the Dimension and Structure of the Subspace Correlated Across Multiple Data Sets
Tanuj Hasija, Christian Lameiro, Timothy Marrinan, Peter J. Schreier
http://arxiv.org/abs/1901.11366v1
• [cs.IT]Reed-Muller codes polarize
Emmanuel Abbe, Min Ye
http://arxiv.org/abs/1901.11533v1
• [cs.IT]Spatial Soft-Core Caching
Derya Malak, Muriel Médard, Edmund Yeh
http://arxiv.org/abs/1901.11102v1
• [cs.IT]Statistics of the Nonlinear Discrete Spectrum of a Noisy Pulse
Francisco Javier Garcia-Gomez, Vahid Aref
http://arxiv.org/abs/1901.11419v1
• [cs.IT]The Interference Channel Revisited: Eliminating Interference with a Two Antenna Receiver
Amir Leshem, Uri Erez
http://arxiv.org/abs/1901.11452v1
• [cs.IT]Transportation Proof of an inequality by Anantharam, Jog and Nair
Thomas A. Courtade
http://arxiv.org/abs/1901.10893v2
• [cs.LG]A Bad Arm Existence Checking Problem
Koji Tabata, Atsuyoshi Nakamura, Junya Honda, Tamiki Komatsuzaki
http://arxiv.org/abs/1901.11200v1
• [cs.LG]A Comparative Analysis of Expected and Distributional Reinforcement Learning
Clare Lyle, Pablo Samuel Castro, Marc G. Bellemare
http://arxiv.org/abs/1901.11084v1
• [cs.LG]A Geometric Perspective on Optimal Representations for Reinforcement Learning
Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taiga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle
http://arxiv.org/abs/1901.11530v1
• [cs.LG]A Theory of Regularized Markov Decision Processes
Matthieu Geist, Bruno Scherrer, Olivier Pietquin
http://arxiv.org/abs/1901.11275v1
• [cs.LG]An Optimization Framework for Task Sequencing in Curriculum Learning
Francesco Foglino, Matteo Leonetti
http://arxiv.org/abs/1901.11478v1
• [cs.LG]Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective
Anirudh Vemula, Wen Sun, J. Andrew Bagnell
http://arxiv.org/abs/1901.11503v1
• [cs.LG]Deep Learning for Inverse Problems: Bounds and Regularizers
Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues
http://arxiv.org/abs/1901.11352v1
• [cs.LG]Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
Ya Ju Fan, Jonathan E. Allen, Sam Ade Jacobs, Brian C. Van Essen
http://arxiv.org/abs/1901.11152v1
• [cs.LG]Distributed Correlation-Based Feature Selection in Spark
Raul-Jose Palma-Mendoza, Luis de-Marcos, Daniel Rodriguez, Amparo Alonso-Betanzos
http://arxiv.org/abs/1901.11286v1
• [cs.LG]Distributionally Robust Removal of Malicious Nodes from Networks
Sixie Yu, Yevgeniy Vorobeychik
http://arxiv.org/abs/1901.11463v1
• [cs.LG]Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization
Nicolas Gillis, Le Thi Khanh Hien, Valentin Leplat, Vincent Y. F. Tan
http://arxiv.org/abs/1901.10757v2
• [cs.LG]Effect of Various Regularizers on Model Complexities of Neural Networks in Presence of Input Noise
Mayank Sharma, Aayush Yadav, Sumit Soman, Jayadeva
http://arxiv.org/abs/1901.11458v1
• [cs.LG]Emerging Convolutions for Generative Normalizing Flows
Emiel Hoogeboom, Rianne van den Berg, Max Welling
http://arxiv.org/abs/1901.11137v1
• [cs.LG]Feature-Critic Networks for Heterogeneous Domain Generalization
Yiying Li, Yongxin Yang, Wei Zhou, Timothy M. Hospedales
http://arxiv.org/abs/1901.11448v1
• [cs.LG]Funnelling: A New Ensemble Method for Heterogeneous Transfer Learning and its Application to Polylingual Text Classification
Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani
http://arxiv.org/abs/1901.11459v1
• [cs.LG]Generalized Dirichlet-process-means for f-separable distortion measures
Masahiro Kobayashi, Kazuho Watanabe
http://arxiv.org/abs/1901.11331v1
• [cs.LG]High-dimensional Metric Combining for Non-coherent Molecular Signal Detection
Zhuangkun Wei, Weisi Guo, Bin Li, Jerome Charmet, Chenglin Zhao
http://arxiv.org/abs/1901.11422v1
• [cs.LG]HyperGAN: A Generative Model for Diverse, Performant Neural Networks
Neale Ratzlaff, Li Fuxin
http://arxiv.org/abs/1901.11058v1
• [cs.LG]Hyperbox based machine learning algorithms: A comprehensive survey
Thanh Tung Khuat, Dymitr Ruta, Bogdan Gabrys
http://arxiv.org/abs/1901.11303v1
• [cs.LG]Improving SGD convergence by tracing multiple promising directions and estimating distance to minimum
Jarek Duda
http://arxiv.org/abs/1901.11457v1
• [cs.LG]Learning and Evaluating General Linguistic Intelligence
Dani Yogatama, Cyprien de Masson d'Autume, Jerome Connor, Tomas Kocisky, Mike Chrzanowski, Lingpeng Kong, Angeliki Lazaridou, Wang Ling, Lei Yu, Chris Dyer, Phil Blunsom
http://arxiv.org/abs/1901.11373v1
• [cs.LG]Memory-Efficient Adaptive Optimization for Large-Scale Learning
Rohan Anil, Vineet Gupta, Tomer Koren, Yoram Singer
http://arxiv.org/abs/1901.11150v1
• [cs.LG]Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty
Muhammad Raza Khan, Joshua E. Blumenstock
http://arxiv.org/abs/1901.11213v1
• [cs.LG]Natural Analysts in Adaptive Data Analysis
Tijana Zrnic, Moritz Hardt
http://arxiv.org/abs/1901.11143v1
• [cs.LG]New Tricks for Estimating Gradients of Expectations
Christian J. Walder, Richard Nock, Cheng Soon Ong, Masashi Sugiyama
http://arxiv.org/abs/1901.11311v1
• [cs.LG]On the Consistency of Top-k Surrogate Losses
Forest Yang, Sanmi Koyejo
http://arxiv.org/abs/1901.11141v1
• [cs.LG]Peer-to-peer Federated Learning on Graphs
Anusha Lalitha, Osman Cihan Kilinc, Tara Javidi, Farinaz Koushanfar
http://arxiv.org/abs/1901.11173v1
• [cs.LG]ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization
Willie Neiswanger, Kirthevasan Kandasamy, Barnabas Poczos, Jeff Schneider, Eric Xing
http://arxiv.org/abs/1901.11515v1
• [cs.LG]Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization
Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
http://arxiv.org/abs/1901.11351v1
• [cs.LG]Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition
Cleison Correia de Amorim, David Macêdo, Cleber Zanchettin
http://arxiv.org/abs/1901.11164v1
• [cs.LG]Successor Features Support Model-based and Model-free Reinforcement Learning
Lucas Lehnert, Michael L. Littman
http://arxiv.org/abs/1901.11437v1
• [cs.LG]The Evolved Transformer
David R. So, Chen Liang, Quoc V. Le
http://arxiv.org/abs/1901.11117v1
• [cs.LG]The Value Function Polytope in Reinforcement Learning
Robert Dadashi, Adrien Ali Taïga, Nicolas Le Roux, Dale Schuurmans, Marc G. Bellemare
http://arxiv.org/abs/1901.11524v1
• [cs.LG]The Wilderness Area Data Set: Adapting the Covertype data set for unsupervised learning
Richard Hugh Moulton, Jakub Zgraja
http://arxiv.org/abs/1901.11040v1
• [cs.LG]Toward Sensor-based Sleep Monitoring with Electrodermal Activity Measures
William Romine, Tanvi Banerjee, Garrett Goodman
http://arxiv.org/abs/1901.11440v1
• [cs.LG]Unsupervised Prediction of Negative Health Events Ahead of Time
Anahita Hosseini, Majid Sarrafzadeh
http://arxiv.org/abs/1901.11168v1
• [cs.MA]Priority Inheritance with Backtracking for Iterative Multi-agent Path Finding
Keisuke Okumura, Manao Machida, Xavier Défago, Yasumasa Tamura
http://arxiv.org/abs/1901.11282v1
• [cs.NE]Code Farming: A Process for Creating Generic Computational Building Blocks
David Landaeta
http://arxiv.org/abs/1901.11115v1
• [cs.NE]Improving Evolutionary Strategies with Generative Neural Networks
Louis Faury, Clement Calauzenes, Olivier Fercoq, Syrine Krichen
http://arxiv.org/abs/1901.11271v1
• [cs.NE]Neuroevolution with Perceptron Turing Machines
David Landaeta
http://arxiv.org/abs/1901.11090v1
• [cs.NE]Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution
Ke Li, Zilin Xiang, Kay Chen Tan
http://arxiv.org/abs/1901.11120v1
• [cs.NI]Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications
Desong Bian, Murat Kuzlu, Manisa Pipattanasomporn, Saifur Rahman, Di Shi
http://arxiv.org/abs/1901.11509v1
• [cs.RO]A Data Driven Method of Optimizing Feedforward Compensator for Autonomous Vehicle
Tianyu Shi, Pin Wang, Ching-Yao Chan, Chonghao Zou
http://arxiv.org/abs/1901.11212v1
• [cs.RO]A test bed for measuring UAV servo reliability
AbdElRaman ElSaid, John Nordlie, Fatima El Jamiy
http://arxiv.org/abs/1901.11486v1
• [cs.RO]Capturing Object Detection Uncertainty in Multi-Layer Grid Maps
Sascha Wirges, Marcel Reith-Braun, Martin Lauer, Christoph Stiller
http://arxiv.org/abs/1901.11284v1
• [cs.SD]Optimization of the Area Under the ROC Curve using Neural Network Supervectors for Text-Dependent Speaker Verification
Victoria Mingote, Antonio Miguel, Alfonso Ortega, Eduardo Lleida
http://arxiv.org/abs/1901.11332v1
• [cs.SE]Formal methods and software engineering for DL. Security, safety and productivity for DL systems development
Gaetan J. D. R. Hains, Arvid Jakobsson, Youry Khmelevsky
http://arxiv.org/abs/1901.11334v1
• [cs.SI]Still out there: Modeling and Identifying Russian Troll Accounts on Twitter
Jane Im, Eshwar Chandrasekharan, Jackson Sargent, Paige Lighthammer, Taylor Denby, Ankit Bhargava, Libby Hemphill, David Jurgens, Eric Gilbert
http://arxiv.org/abs/1901.11162v1
• [cs.SY]Geometric fluid approximation for general continuous-time Markov chains
Michalis Michaelides, Jane Hillston, Guido Sanguinetti
http://arxiv.org/abs/1901.11417v1
• [econ.EM]A dynamic factor model approach to incorporate Big Data in state space models for official statistics
Caterina Schiavoni, Franz Palm, Stephan Smeekes, Jan van den Brakel
http://arxiv.org/abs/1901.11355v1
• [eess.SP]Decomposition of Higher-Order Spectra for Blind Multiple-Input Deconvolution, Pattern Identification and Separation
Christopher K. Kovach, Matthew A. Howard III
http://arxiv.org/abs/1901.11395v1
• [math.OC]Lower Bounds for Smooth Nonconvex Finite-Sum Optimization
Dongruo Zhou, Quanquan Gu
http://arxiv.org/abs/1901.11224v1
• [math.OC]Stochastic Recursive Variance-Reduced Cubic Regularization Methods
Dongruo Zhou, Quanquan Gu
http://arxiv.org/abs/1901.11518v1
• [math.PR]Tight bounds on the convergence rate of generalized ratio consensus algorithms
Balázs Gerencsér, László Gerencsér
http://arxiv.org/abs/1901.11374v1
• [math.ST]Improved mathematical models of statistical regularities in precipitation
Victor Korolev, Andrey Gorshenin
http://arxiv.org/abs/1901.11052v1
• [q-bio.GN]GeNet: Deep Representations for Metagenomics
Mateo Rojas-Carulla, Ilya Tolstikhin, Guillermo Luque, Nicholas Youngblut, Ruth Ley, Bernhard Schölkopf
http://arxiv.org/abs/1901.11015v1
• [q-bio.NC]Sequential Bayesian Detection of Spike Activities from Fluorescence Observations
Zhuangkun Wei, Bin Li, Weisi Guo, Wenxiu Hu, Chenglin Zhao
http://arxiv.org/abs/1901.11418v1
• [stat.AP]Bayesian nonparametric multiway regression for clustered binomial data
Eric F. Lock, Dipankar Bandyopadhyay
http://arxiv.org/abs/1901.11172v1
• [stat.CO]Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage
Darjus Hosszejni, Gregor Kastner
http://arxiv.org/abs/1901.11491v1
• [stat.ME]Causal Proportional Hazards Estimation with a Binary Instrumental Variable
Behzad Kianian, Jung In Kim, Jason P. Fine, Limin Peng
http://arxiv.org/abs/1901.11050v1
• [stat.ME]Logistic Box-Cox Regression to Assess the Shape and Median Effect under Uncertainty about Model Specification
Li Xing, Xuekui Zhang, Igor Burstyn, Paul Gustafson
http://arxiv.org/abs/1901.11362v1
• [stat.ME]Propensity Score Matching underestimates Real Treatment Effect, in a simulated theoretical multivariate model
Daniel García Iglesias
http://arxiv.org/abs/1901.09883v2
• [stat.ME]Random forests for high-dimensional longitudinal data
Louis Capitaine, Robin Genuer, Rodolphe Thiébaut
http://arxiv.org/abs/1901.11279v1
• [stat.ML]Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model
Gi-Soo Kim, Myunghee Cho Paik
http://arxiv.org/abs/1901.11221v1
• [stat.ML]End-to-End Probabilistic Inference for Nonstationary Audio Analysis
William J. Wilkinson, Michael Riis Andersen, Joshua D. Reiss, Dan Stowell, Arno Solin
http://arxiv.org/abs/1901.11436v1
• [stat.ML]Functional Regularisation for Continual Learning using Gaussian Processes
Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews, Razvan Pascanu, Yee Whye Teh
http://arxiv.org/abs/1901.11356v1
• [stat.ML]Metric Gaussian Variational Inference
Jakob Knollmüller, Torsten A. Enßlin
http://arxiv.org/abs/1901.11033v1
• [stat.ML]Minimizing Negative Transfer of Knowledge in Multivariate Gaussian Processes: A Scalable and Regularized Approach
Raed Kontar, Garvesh Raskutti, Shiyu Zhou
http://arxiv.org/abs/1901.11512v1
• [stat.ML]Multi-dimensional Tensor Sketch
Yang Shi, Animashree Anandkumar
http://arxiv.org/abs/1901.11261v1
• [stat.ML]Robust Inference via Generative Classifiers for Handling Noisy Labels
Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin
http://arxiv.org/abs/1901.11300v1
• [stat.ML]Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee
Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin
http://arxiv.org/abs/1901.11149v1
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