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.GT - 计算机科学与博弈论
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.LO - 计算逻辑
cs.NA - 数值分析
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.SI - 社交网络与信息网络
cs.SY - 系统与控制
eess.SP - 信号处理
math.OC - 优化与控制
math.ST - 统计理论
nucl-th - 核理论
physics.soc-ph - 物理学与社会
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
• [cs.AI]CommunityGAN: Community Detection with Generative Adversarial Nets
• [cs.CL]AspeRa: Aspect-based Rating Prediction Model
• [cs.CL]Attenuating Bias in Word Vectors
• [cs.CL]Automated Essay Scoring based on Two-Stage Learning
• [cs.CL]Context based Analysis of Lexical Semantics for Hindi Language
• [cs.CL]Context-Sensitive Malicious Spelling Error Correction
• [cs.CL]Delta-training: Simple Semi-Supervised Text Classification using Pretrained Word Embeddings
• [cs.CL]Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG Challenge
• [cs.CL]Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning
• [cs.CL]Product-Aware Answer Generation in E-Commerce Question-Answering
• [cs.CL]Self-Attentive Model for Headline Generation
• [cs.CL]Sentiment and Sarcasm Classification with Multitask Learning
• [cs.CR]Deep Adversarial Learning in Intrusion Detection: A Data Augmentation Enhanced Framework
• [cs.CR]Programmable Neural Network Trojan for Pre-Trained Feature Extractor
• [cs.CV]A Boost in Revealing Subtle Facial Expressions: A Consolidated Eulerian Framework
• [cs.CV]A Top-down Approach to Articulated Human Pose Estimation and Tracking
• [cs.CV]AADS: Augmented Autonomous Driving Simulation using Data-driven Algorithms
• [cs.CV]Bottom-up Object Detection by Grouping Extreme and Center Points
• [cs.CV]CAE-P: Compressive Autoencoder with Pruning Based on ADMM
• [cs.CV]Class Activation Map Generation by Representative Class Selection and Multi-Layer Feature Fusion
• [cs.CV]Computer Vision and Metrics Learning for Hypothesis Testing: An Application of Q-Q Plot for Normality Test
• [cs.CV]Deep learning Inversion of Seismic Data
• [cs.CV]DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images
• [cs.CV]Evolving the pulmonary nodules diagnosis from classical approaches to deep learning aided decision support: three decades development course and future prospect
• [cs.CV]Exploring Uncertainty in Conditional Multi-Modal Retrieval Systems
• [cs.CV]Joint group and residual sparse coding for image compressive sensing
• [cs.CV]MIMIC-CXR: A large publicly available database of labeled chest radiographs
• [cs.CV]Max-margin Class Imbalanced Learning with Gaussian Affinity
• [cs.CV]Modeling Human Motion with Quaternion-based Neural Networks
• [cs.CV]ODN: Opening the Deep Network for Open-set Action Recognition
• [cs.CV]ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features
• [cs.CV]On Compression of Unsupervised Neural Nets by Pruning Weak Connections
• [cs.CV]Random Forest with Learned Representations for Semantic Segmentation
• [cs.CV]Removing Stripes, Scratches, and Curtaining with Non-Recoverable Compressed Sensing
• [cs.CV]Robust Learning at Noisy Labeled Medical Images:Applied to Skin Lesion Classification
• [cs.CV]Simultaneous Subspace Clustering and Cluster Number Estimating based on Triplet Relationship
• [cs.CV]Striking the Right Balance with Uncertainty
• [cs.CV]Toward Joint Image Generation and Compression using Generative Adversarial Networks
• [cs.CV]Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning
• [cs.CV]U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans
• [cs.CY]Analytics-Driven Digital Platform for Regional Growth and Development: A Case Study from Norway
• [cs.CY]Evaluation of Biases in Self-reported Demographic and Psychometric Information: Traditional versus Facebook-based Surveys
• [cs.CY]Wikipedia Cultural Diversity Dataset: A Complete Cartography for 300 Language Editions
• [cs.DC]Accelerating Channel Estimation and Demodulation of Uplink OFDM symbols for Large Scale Antenna Systems using GPU
• [cs.DC]Enhancing MapReduce Fault Recovery Through Binocular Speculation
• [cs.DC]No DNN Left Behind: Improving Inference in the Cloud with Multi-Tenancy
• [cs.GT]Single Deep Counterfactual Regret Minimization
• [cs.IR]Boosting Frequent Itemset Mining via Early Stopping Intersections
• [cs.IR]CREATE: Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records using OMOP Common Data Model
• [cs.IR]Managing Popularity Bias in Recommender Systems with Personalized Re-ranking
• [cs.IT]A Fundamental Storage-Communication Tradeoff in Distributed Computing with Straggling Nodes
• [cs.IT]A Survey of Optimization Approaches for Wireless Physical Layer Security
• [cs.IT]Bit Flipping Moment Balancing Schemes for Insertion, Deletion and Substitution Error Correction
• [cs.IT]Cascaded Coded Distributed Computing on Heterogeneous Networks
• [cs.IT]Coded Caching via Projective Geometry: A new low subpacketization scheme
• [cs.IT]Construction of One-Bit Transmit-Signal Vectors for Downlink MU-MISO Systems with PSK Signaling
• [cs.IT]Distributed and Private Coded Matrix Computation with Flexible Communication Load
• [cs.IT]Enable Super-resolution Parameter Estimation for Mm-wave Channel Sounding
• [cs.IT]Homomorphic Sensing
• [cs.IT]Minimum-Polytope-Based Linear Programming Decoder for LDPC Codes via ADMM Approach
• [cs.IT]On the Fundamental Limits of Multi-user Scheduling under Short-term Fairness Constraints
• [cs.IT]Polar Coding for Common Message Only Wiretap Broadcast Channel
• [cs.IT]Single-Server Single-Message Online Private Information Retrieval with Side Information
• [cs.IT]Sparse Graph Codes for Non-adaptive Quantitative Group Testing
• [cs.IT]Unique Information and Secret Key Decompositions
• [cs.IT]What Can Machine Learning Teach Us about Communications?
• [cs.LG]"Is this an example image?" -- Predicting the Relative Abstractness Level of Image and Text
• [cs.LG]A New CGAN Technique for Constrained Topology Design Optimization
• [cs.LG]A deep Convolutional Neural Network for topology optimization with strong generalization ability
• [cs.LG]Adaptive Exact Learning of Decision Trees from Membership Queries
• [cs.LG]An information theoretic approach to the autoencoder
• [cs.LG]Backprop with Approximate Activations for Memory-efficient Network Training
• [cs.LG]CTCModel: a Keras Model for Connectionist Temporal Classification
• [cs.LG]Composition and decomposition of GANs
• [cs.LG]Constant Time Graph Neural Networks
• [cs.LG]DTN: A Learning Rate Scheme with Convergence Rate of for SGD
• [cs.LG]Deep Clustering with a Dynamic Autoencoder
• [cs.LG]Hierarchical Reinforcement Learning for Multi-agent MOBA Game
• [cs.LG]How do Mixture Density RNNs Predict the Future?
• [cs.LG]Learning to Collaborate in Markov Decision Processes
• [cs.LG]Neural-Guided Symbolic Regression with Semantic Prior
• [cs.LG]On orthogonal projections for dimension reduction and applications in variational loss functions for learning problems
• [cs.LG]Online Adaptive Principal Component Analysis and Its extensions
• [cs.LG]Online Learning with Diverse User Preferences
• [cs.LG]PD-ML-Lite: Private Distributed Machine Learning from Lighweight Cryptography
• [cs.LG]Predicting Parkinson's Disease using Latent Information extracted from Deep Neural Networks
• [cs.LG]Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information
• [cs.LG]Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff
• [cs.LG]Robust temporal difference learning for critical domains
• [cs.LG]Submodular Maximization under Fading Model: Building Online Quizzes for Better Customer Segmentation
• [cs.LG]Thompson Sampling for a Fatigue-aware Online Recommendation System
• [cs.LG]Trust Region Value Optimization using Kalman Filtering
• [cs.LG]Typed Graph Networks
• [cs.LG]Understanding Geometry of Encoder-Decoder CNNs
• [cs.LG]Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract)
• [cs.LG]kd-switch: A Universal Online Predictor with an application to Sequential Two-Sample Testing
• [cs.LO]Predicting the Results of LTL Model Checking using Multiple Machine Learning Algorithms
• [cs.NA]Solving All Regression Models For Learning Gaussian Networks Using Givens Rotations
• [cs.NE]Analysis of the -CSA-ES with Repair by Projection Applied to a Conically Constrained Problem
• [cs.NE]Can Transfer Entropy Infer Causality in Neuronal Circuits for Cognitive Processing?
• [cs.NE]Interpolation and Denoising of Seismic Data using Convolutional Neural Networks
• [cs.NE]Robust computation with rhythmic spike patterns
• [cs.NI]Blockchain-based Content Delivery Networks: Content Transparency Meets User Privacy
• [cs.RO]A Constraint Programming Approach to Simultaneous Task Allocation and Motion Scheduling for Industrial Dual-Arm Manipulation Tasks
• [cs.RO]Active Perception based Formation Control for Multiple Aerial Vehicles
• [cs.RO]Cooperative coevolution of real predator robots and virtual robots in the pursuit domain
• [cs.RO]Estimating Configuration Space Belief from Collision Checks for Motion Planning
• [cs.RO]Provable Infinite-Horizon Real-Time Planning for Repetitive Tasks
• [cs.RO]Robust Photogeometric Localization over Time for Map-Centric Loop Closure
• [cs.SI]Approximate k-Cover in Hypergraphs: Efficient Algorithms, and Applications
• [cs.SI]The Junk News Aggregator: Examining junk news posted on Facebook, starting with the 2018 US Midterm Elections
• [cs.SY]Second Order Statistics Analysis and Comparison between Arithmetic and Geometric Average Fusion
• [eess.SP]ICLabel: An automated electroencephalographic independent component classifier, dataset, and website
• [eess.SP]MIMO-UFMC Transceiver Schemes for Millimeter Wave Wireless Communications
• [eess.SP]On the Uplink Achievable Rate of Massive MIMO System With Low-Resolution ADC and RF Impairments
• [eess.SP]Rate Balancing in Full-Duplex MIMO Two-Way Relay Networks
• [eess.SP]SC-Fano Decoding of Polar Codes
• [eess.SP]Uncertainty Principle in Distributed MIMO Radars
• [math.OC]A Universally Optimal Multistage Accelerated Stochastic Gradient Method
• [math.OC]Admissibility of solution estimators for stochastic optimization
• [math.OC]Optimal Finite-Sum Smooth Non-Convex Optimization with SARAH
• [math.OC]Reinforcement Learning of Markov Decision Processes with Peak Constraints
• [math.ST]Central limit theorem for linear spectral statistics of general separable sample covariance matrices with applications
• [math.ST]Modelling and simulation of multifractal star-shaped particles
• [nucl-th]Neutron drip line in the Ca region from Bayesian model averaging
• [physics.soc-ph]Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections
• [physics.soc-ph]Mathematical model of gender bias and homophily in professional hierarchies
• [physics.soc-ph]Navigability evaluation of complex networks by greedy routing efficiency
• [q-bio.QM]Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning
• [quant-ph]A comparative study of estimation methods in quantum tomography
• [quant-ph]Neural Decoder for Topological Codes using Pseudo-Inverse of Parity Check Matrix
• [stat.AP]Mobility-on-demand versus fixed-route transit systems: an evaluation of traveler preferences in low-income communities
• [stat.ME]Functional Continuum Regression
• [stat.ME]High-dimensional Interactions Detection with Sparse Principal Hessian Matrix
• [stat.ME]Optimal Uncertainty Quantification of a risk measurement from a thermal-hydraulic code using Canonical Moments
• [stat.ME]Ordinal Probit Functional Regression Models with Application to Computer-Use Behavior in Rhesus Monkeys
• [stat.ML]A Review on Quantile Regression for Stochastic Computer Experiments
• [stat.ML]Aggregated Pairwise Classification of Statistical Shapes
• [stat.ML]Coupling the reduced-order model and the generative model for an importance sampling estimator
• [stat.ML]Hamiltonian Monte-Carlo for Orthogonal Matrices
• [stat.ML]Incremental Principal Component Analysis Exact implementation and continuity corrections
• [stat.ML]Stein Variational Online Changepoint Detection with Applications to Hawkes Processes and Neural Networks
• [stat.ML]Stochastic Gradient Trees
• [stat.ML]Support Estimation via Regularized and Weighted Chebyshev Approximations
• [stat.ML]Unified efficient estimation framework for unnormalized models
·····································
• [cs.AI]CommunityGAN: Community Detection with Generative Adversarial Nets
Yuting Jia, Qinqin Zhang, Weinan Zhang, Xinbing Wang
http://arxiv.org/abs/1901.06631v2
• [cs.CL]AspeRa: Aspect-based Rating Prediction Model
Sergey I. Nikolenko, Elena Tutubalina, Valentin Malykh, Ilya Shenbin, Anton Alekseev
http://arxiv.org/abs/1901.07829v1
• [cs.CL]Attenuating Bias in Word Vectors
Sunipa Dev, Jeff Phillips
http://arxiv.org/abs/1901.07656v1
• [cs.CL]Automated Essay Scoring based on Two-Stage Learning
Jiawei Liu, Yang Xu, Lingzhe Zhao
http://arxiv.org/abs/1901.07744v1
• [cs.CL]Context based Analysis of Lexical Semantics for Hindi Language
Mohd Zeeshan Ansari, Lubna Khan
http://arxiv.org/abs/1901.07867v1
• [cs.CL]Context-Sensitive Malicious Spelling Error Correction
Hongyu Gong, Yuchen Li, Suma Bhat, Pramod Viswanath
http://arxiv.org/abs/1901.07688v1
• [cs.CL]Delta-training: Simple Semi-Supervised Text Classification using Pretrained Word Embeddings
Hwiyeol Jo, Ceyda Cinarel
http://arxiv.org/abs/1901.07651v1
• [cs.CL]Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG Challenge
Ondřej Dušek, Jekaterina Novikova, Verena Rieser
http://arxiv.org/abs/1901.07931v1
• [cs.CL]Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning
Haiyun Peng, Yukun Ma, Soujanya Poria, Yang Li, Erik Cambria
http://arxiv.org/abs/1901.07880v1
• [cs.CL]Product-Aware Answer Generation in E-Commerce Question-Answering
Shen Gao, Xiuying Chen, Piji Li, Zhaochun Ren, Lidong Bing, Dongyan Zhao, Rui Yan
http://arxiv.org/abs/1901.07696v1
• [cs.CL]Self-Attentive Model for Headline Generation
Daniil Gavrilov, Pavel Kalaidin, Valentin Malykh
http://arxiv.org/abs/1901.07786v1
• [cs.CL]Sentiment and Sarcasm Classification with Multitask Learning
Navonil Majumder, Soujanya Poria, Haiyun Peng, Niyati Chhaya, Erik Cambria, Alexander Gelbukh
http://arxiv.org/abs/1901.08014v1
• [cs.CR]Deep Adversarial Learning in Intrusion Detection: A Data Augmentation Enhanced Framework
He Zhang, Xingrui Yu, Peng Ren, Chunbo Luo, Geyong Min
http://arxiv.org/abs/1901.07949v1
• [cs.CR]Programmable Neural Network Trojan for Pre-Trained Feature Extractor
Yu Ji, Zixin Liu, Xing Hu, Peiqi Wang, Youhui Zhang
http://arxiv.org/abs/1901.07766v1
• [cs.CV]A Boost in Revealing Subtle Facial Expressions: A Consolidated Eulerian Framework
Wei Peng, Xiaopeng Hong, Yingyue Xu, Guoying Zhao
http://arxiv.org/abs/1901.07765v1
• [cs.CV]A Top-down Approach to Articulated Human Pose Estimation and Tracking
Guanghan Ning, Ping Liu, Xiaochuan Fan, Chi Zhang
http://arxiv.org/abs/1901.07680v1
• [cs.CV]AADS: Augmented Autonomous Driving Simulation using Data-driven Algorithms
Wei Li, Chengwei Pan, Rong Zhang, Jiaping Ren, Yuexin Ma, Jin Fang, Feilong Yan, Qichuan Geng, Xinyu Huang, Huajun Gong, Weiwei Xu, Guoping Wang, Dinesh Manocha, Ruigang Yang
http://arxiv.org/abs/1901.07849v1
• [cs.CV]Bottom-up Object Detection by Grouping Extreme and Center Points
Xingyi Zhou, Jiacheng Zhuo, Philipp Krähenbühl
http://arxiv.org/abs/1901.08043v1
• [cs.CV]CAE-P: Compressive Autoencoder with Pruning Based on ADMM
Haimeng Zhao
http://arxiv.org/abs/1901.07196v2
• [cs.CV]Class Activation Map Generation by Representative Class Selection and Multi-Layer Feature Fusion
Fanman Meng, Kaixu Huang, Hongliang Li, Qingbo Wu
http://arxiv.org/abs/1901.07683v1
• [cs.CV]Computer Vision and Metrics Learning for Hypothesis Testing: An Application of Q-Q Plot for Normality Test
Ke-Wei Huang, Mengke Qiao, Xuanqi Liu, Mingxi Dai, Siyuan Liu
http://arxiv.org/abs/1901.07851v1
• [cs.CV]Deep learning Inversion of Seismic Data
Shucai Li, Bin Liu, Yuxiao Ren, Yangkang Chen, Senlin Yang, Yunhai Wang, Peng Jiang
http://arxiv.org/abs/1901.07733v1
• [cs.CV]DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images
Yuying Ge, Ruimao Zhang, Lingyun Wu, Xiaogang Wang, Xiaoou Tang, Ping Luo
http://arxiv.org/abs/1901.07973v1
• [cs.CV]Evolving the pulmonary nodules diagnosis from classical approaches to deep learning aided decision support: three decades development course and future prospect
Bo Liu, Wenhao Chi, Xinran Li, Peng Li, Wenhua Liang, Haiping Liu, Wei Wang, Jianxing He
http://arxiv.org/abs/1901.07858v1
• [cs.CV]Exploring Uncertainty in Conditional Multi-Modal Retrieval Systems
Ahmed Taha, Yi-Ting Chen, Xitong Yang, Teruhisa Misu, Larry Davis
http://arxiv.org/abs/1901.07702v1
• [cs.CV]Joint group and residual sparse coding for image compressive sensing
Lizhao Li, Song Xiao
http://arxiv.org/abs/1901.07720v1
• [cs.CV]MIMIC-CXR: A large publicly available database of labeled chest radiographs
Alistair E. W. Johnson, Tom J. Pollard, Seth J. Berkowitz, Nathaniel R. Greenbaum, Matthew P. Lungren, Chih-ying Deng, Roger G. Mark, Steven Horng
http://arxiv.org/abs/1901.07042v2
• [cs.CV]Max-margin Class Imbalanced Learning with Gaussian Affinity
Munawar Hayat, Salman Khan, Waqas Zamir, Jianbing Shen, Ling Shao
http://arxiv.org/abs/1901.07711v1
• [cs.CV]Modeling Human Motion with Quaternion-based Neural Networks
Dario Pavllo, Christoph Feichtenhofer, Michael Auli, David Grangier
http://arxiv.org/abs/1901.07677v1
• [cs.CV]ODN: Opening the Deep Network for Open-set Action Recognition
Yu Shu, Yemin Shi, Yaowei Wang, Yixiong Zou, Qingsheng Yuan, Yonghong Tian
http://arxiv.org/abs/1901.07757v1
• [cs.CV]ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features
Xin Wu, Danfeng Hong, Jiaojiao Tian, Jocelyn Chanussot, Wei Li, Ran Tao
http://arxiv.org/abs/1901.07925v1
• [cs.CV]On Compression of Unsupervised Neural Nets by Pruning Weak Connections
Zhiwen Zuo, Lei Zhao, Liwen Zuo, Feng Jiang, Wei Xing, Dongming Lu
http://arxiv.org/abs/1901.07066v2
• [cs.CV]Random Forest with Learned Representations for Semantic Segmentation
Byeongkeun Kang, Truong Q. Nguyen
http://arxiv.org/abs/1901.07828v1
• [cs.CV]Removing Stripes, Scratches, and Curtaining with Non-Recoverable Compressed Sensing
Jonathan Schwartz, Yi Jiang, Yongjie Wang, Anthony Aiello, Pallab Bhattacharya, Hui Yuan, Zetian Mi, Nabil Bassim, Robert Hovden
http://arxiv.org/abs/1901.08001v1
• [cs.CV]Robust Learning at Noisy Labeled Medical Images:Applied to Skin Lesion Classification
Cheng Xue, Qi Dou, Xueying Shi, Hao Chen, Pheng Ann Heng
http://arxiv.org/abs/1901.07759v1
• [cs.CV]Simultaneous Subspace Clustering and Cluster Number Estimating based on Triplet Relationship
Jie Liang, Jufeng Yang, Ming-Ming Cheng, Paul L. Rosin, Liang Wang
http://arxiv.org/abs/1901.07689v1
• [cs.CV]Striking the Right Balance with Uncertainty
Salman Khan, Munawar Hayat, Waqas Zamir, Jianbing Shen, Ling Shao
http://arxiv.org/abs/1901.07590v1
• [cs.CV]Toward Joint Image Generation and Compression using Generative Adversarial Networks
Byeongkeun Kang, Subarna Tripathi, Truong Q. Nguyen
http://arxiv.org/abs/1901.07838v1
• [cs.CV]Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning
Shaohui Lin, Rongrong Ji, Yuchao Li, Cheng Deng, Xuelong Li
http://arxiv.org/abs/1901.07827v1
• [cs.CV]U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans
José Ignacio Orlando, Philipp Seeböck, Hrvoje Bogunović, Sophie Klimscha, Christoph Grechenig, Sebastian Waldstein, Bianca S. Gerendas, Ursula Schmidt-Erfurth
http://arxiv.org/abs/1901.07929v1
• [cs.CY]Analytics-Driven Digital Platform for Regional Growth and Development: A Case Study from Norway
Salah Uddin Ahmed, Steinar Aasnass, Fisnik Dalipi, Knut Hesten
http://arxiv.org/abs/1901.07584v1
• [cs.CY]Evaluation of Biases in Self-reported Demographic and Psychometric Information: Traditional versus Facebook-based Surveys
Kyriaki Kalimeri, Mariano G. Beiro, Andrea Bonanomi, Alessandro Rosina, Ciro Cattuto
http://arxiv.org/abs/1901.07876v1
• [cs.CY]Wikipedia Cultural Diversity Dataset: A Complete Cartography for 300 Language Editions
Marc Miquel-Ribé, David Laniado
http://arxiv.org/abs/1901.07999v1
• [cs.DC]Accelerating Channel Estimation and Demodulation of Uplink OFDM symbols for Large Scale Antenna Systems using GPU
Bhargav Gokalgandhi, Christina Segerholm, Nilanjan Paul, Ivan Seskar
http://arxiv.org/abs/1901.07499v2
• [cs.DC]Enhancing MapReduce Fault Recovery Through Binocular Speculation
Huansong Fu, Yue Zhu, Amit Kumar Nath, Md. Muhib Khan, Weikuan Yu
http://arxiv.org/abs/1901.07715v1
• [cs.DC]No DNN Left Behind: Improving Inference in the Cloud with Multi-Tenancy
Amit Samanta, Suhas Shrinivasan, Antoine Kaufmann, Jonathan Mace
http://arxiv.org/abs/1901.06887v2
• [cs.GT]Single Deep Counterfactual Regret Minimization
Eric Steinberger
http://arxiv.org/abs/1901.07621v1
• [cs.IR]Boosting Frequent Itemset Mining via Early Stopping Intersections
Huu Hiep Nguyen
http://arxiv.org/abs/1901.07773v1
• [cs.IR]CREATE: Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records using OMOP Common Data Model
Sijia Liu, Yanshan Wang, Andrew Wen, Liwei Wang, Na Hong, Feichen Shen, Steven Bedrick, William Hersh, Hongfang Liu
http://arxiv.org/abs/1901.07601v1
• [cs.IR]Managing Popularity Bias in Recommender Systems with Personalized Re-ranking
Himan Abdollahpouri, Robin Burke, Bamshad Mobasher
http://arxiv.org/abs/1901.07555v1
• [cs.IT]A Fundamental Storage-Communication Tradeoff in Distributed Computing with Straggling Nodes
Qifa Yan, Michèle Wigger, Sheng Yang, Xiaohu Tang
http://arxiv.org/abs/1901.07793v1
• [cs.IT]A Survey of Optimization Approaches for Wireless Physical Layer Security
Dong Wang, Bo Bai, Wenbo Zhao, Zhu Han
http://arxiv.org/abs/1901.07955v1
• [cs.IT]Bit Flipping Moment Balancing Schemes for Insertion, Deletion and Substitution Error Correction
Ling Cheng, Hendrik C. Ferreira
http://arxiv.org/abs/1901.07769v1
• [cs.IT]Cascaded Coded Distributed Computing on Heterogeneous Networks
Nicholas Woolsey, Rong-Rong Chen, Mingyue Ji
http://arxiv.org/abs/1901.07670v1
• [cs.IT]Coded Caching via Projective Geometry: A new low subpacketization scheme
Hari Hara Suthan C, Bhavana M, Prasad Krishnan
http://arxiv.org/abs/1901.07823v1
• [cs.IT]Construction of One-Bit Transmit-Signal Vectors for Downlink MU-MISO Systems with PSK Signaling
Gyu-Jeong Park, Song-Nam Hong
http://arxiv.org/abs/1901.07795v1
• [cs.IT]Distributed and Private Coded Matrix Computation with Flexible Communication Load
Malihe Aliasgari, Osvaldo Simeone, Joerg Kliewer
http://arxiv.org/abs/1901.07705v1
• [cs.IT]Enable Super-resolution Parameter Estimation for Mm-wave Channel Sounding
Rui Wang, C. Umit Bas, Zihang Cheng, Thomas Choi, Hao Feng, Zheda Li, XiaoKang Ye, Pan Tang, Seun Sangodoyin, Jorge G. Ponce, Robert Monroe, Thomas Henige, Gary Xu, Jianzhong, Zhang, Jeongho Park, Andreas F. Molisch
http://arxiv.org/abs/1901.07749v1
• [cs.IT]Homomorphic Sensing
Manolis C. Tsakiris, Liangzu Peng
http://arxiv.org/abs/1901.07852v1
• [cs.IT]Minimum-Polytope-Based Linear Programming Decoder for LDPC Codes via ADMM Approach
Jing Bai, Yongchao Wang, Francis C. M. Lau
http://arxiv.org/abs/1901.07806v1
• [cs.IT]On the Fundamental Limits of Multi-user Scheduling under Short-term Fairness Constraints
Shahram Shahsavari, Farhad Shirani, Elza Erkip
http://arxiv.org/abs/1901.07719v1
• [cs.IT]Polar Coding for Common Message Only Wiretap Broadcast Channel
Jaume del Olmo Alos, Javier R. Fonollosa
http://arxiv.org/abs/1901.07649v1
• [cs.IT]Single-Server Single-Message Online Private Information Retrieval with Side Information
Fatemeh Kazemi, Esmaeil Karimi, Anoosheh Heidarzadeh, Alex Sprintson
http://arxiv.org/abs/1901.07748v1
• [cs.IT]Sparse Graph Codes for Non-adaptive Quantitative Group Testing
Esmaeil Karimi, Fatemeh Kazemi, Anoosheh Heidarzadeh, Krishna R. Narayanan, Alex Sprintson
http://arxiv.org/abs/1901.07635v1
• [cs.IT]Unique Information and Secret Key Decompositions
Johannes Rauh, Pradeep Kr. Banerjee, Eckehard Olbrich, Jürgen Jost
http://arxiv.org/abs/1901.08007v1
• [cs.IT]What Can Machine Learning Teach Us about Communications?
Mengke Lian, Christian Häger, Henry D. Pfister
http://arxiv.org/abs/1901.07592v1
• [cs.LG]"Is this an example image?" -- Predicting the Relative Abstractness Level of Image and Text
Christian Otto, Sebastian Holzki, Ralph Ewerth
http://arxiv.org/abs/1901.07878v1
• [cs.LG]A New CGAN Technique for Constrained Topology Design Optimization
M. -H. Herman Shen, Liang Chen
http://arxiv.org/abs/1901.07675v1
• [cs.LG]A deep Convolutional Neural Network for topology optimization with strong generalization ability
Yiquan Zhang, Airong Chen, Bo Peng, Xiaoyi Zhou, Dalei Wang
http://arxiv.org/abs/1901.07761v1
• [cs.LG]Adaptive Exact Learning of Decision Trees from Membership Queries
Nader H. Bshouty, Catherine A. Haddad-Zaknoon
http://arxiv.org/abs/1901.07750v1
• [cs.LG]An information theoretic approach to the autoencoder
Vincenzo Crescimanna, Bruce Graham
http://arxiv.org/abs/1901.08019v1
• [cs.LG]Backprop with Approximate Activations for Memory-efficient Network Training
Ayan Chakrabarti, Benjamin Moseley
http://arxiv.org/abs/1901.07988v1
• [cs.LG]CTCModel: a Keras Model for Connectionist Temporal Classification
Yann Soullard, Cyprien Ruffino, Thierry Paquet
http://arxiv.org/abs/1901.07957v1
• [cs.LG]Composition and decomposition of GANs
Yeu-Chern Harn, Zhenghao Chen, Vladimir Jojic
http://arxiv.org/abs/1901.07667v1
• [cs.LG]Constant Time Graph Neural Networks
Ryoma Sato, Makoto Yamada, Hisashi Kashima
http://arxiv.org/abs/1901.07868v1
• [cs.LG]DTN: A Learning Rate Scheme with Convergence Rate of for SGD
Lam M. Nguyen, Phuong Ha Nguyen, Dzung T. Phan, Jayant R. Kalagnanam, Marten van Dijk
http://arxiv.org/abs/1901.07634v1
• [cs.LG]Deep Clustering with a Dynamic Autoencoder
Nairouz Mrabah, Naimul Mefraz Khan, Riadh Ksantini
http://arxiv.org/abs/1901.07752v1
• [cs.LG]Hierarchical Reinforcement Learning for Multi-agent MOBA Game
Zhijian Zhang, Haozheng Li, Luo Zhang, Tianyin Zheng, Ting Zhang, Xiong Hao, Xiaoxin Chen, Min Chen, Fangxu Xiao, Wei Zhou
http://arxiv.org/abs/1901.08004v1
• [cs.LG]How do Mixture Density RNNs Predict the Future?
Kai Olav Ellefsen, Charles Patrick Martin, Jim Torresen
http://arxiv.org/abs/1901.07859v1
• [cs.LG]Learning to Collaborate in Markov Decision Processes
Goran Radanovic, Rati Devidze, David Parkes, Adish Singla
http://arxiv.org/abs/1901.08029v1
• [cs.LG]Neural-Guided Symbolic Regression with Semantic Prior
Li Li, Minjie Fan, Rishabh Singh, Patrick Riley
http://arxiv.org/abs/1901.07714v1
• [cs.LG]On orthogonal projections for dimension reduction and applications in variational loss functions for learning problems
Anna Breger, Jose Ignacio Orlando, Pavol Harar, Monika Dörfler, Sophie Klimscha, Christoph Grechenig, Bianca S. Gerendas, Ursula Schmidt-Erfurth, Martin Ehler
http://arxiv.org/abs/1901.07598v1
• [cs.LG]Online Adaptive Principal Component Analysis and Its extensions
Jianjun Yuan, Andrew Lamperski
http://arxiv.org/abs/1901.07687v1
• [cs.LG]Online Learning with Diverse User Preferences
Chao Gan, Jing Yang, Ruida Zhou, Cong Shen
http://arxiv.org/abs/1901.07924v1
• [cs.LG]PD-ML-Lite: Private Distributed Machine Learning from Lighweight Cryptography
Maksim Tsikhanovich, Malik Magdon-Ismail, Muhammad Ishaq, Vassilis Zikas
http://arxiv.org/abs/1901.07986v1
• [cs.LG]Predicting Parkinson's Disease using Latent Information extracted from Deep Neural Networks
Ilianna Kollia, Andreas-Georgios Stafylopatis, Stefanos Kollias
http://arxiv.org/abs/1901.07822v1
• [cs.LG]Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information
Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi
http://arxiv.org/abs/1901.07935v1
• [cs.LG]Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff
Yochai Blau, Tomer Michaeli
http://arxiv.org/abs/1901.07821v1
• [cs.LG]Robust temporal difference learning for critical domains
Richard Klima, Daan Bloembergen, Michael Kaisers, Karl Tuyls
http://arxiv.org/abs/1901.08021v1
• [cs.LG]Submodular Maximization under Fading Model: Building Online Quizzes for Better Customer Segmentation
Shaojie Tang
http://arxiv.org/abs/1901.07708v1
• [cs.LG]Thompson Sampling for a Fatigue-aware Online Recommendation System
Yunjuan Wang, Theja Tulabandhula
http://arxiv.org/abs/1901.07734v1
• [cs.LG]Trust Region Value Optimization using Kalman Filtering
Shirli Di-Castro Shashua, Shie Mannor
http://arxiv.org/abs/1901.07860v1
• [cs.LG]Typed Graph Networks
Pedro Henrique da Costa Avelar, Henrique Lemos, Marcelo de Oliveira Rosa Prates, Marco Gori, Luis Lamb
http://arxiv.org/abs/1901.07984v1
• [cs.LG]Understanding Geometry of Encoder-Decoder CNNs
Jong Chul Ye, Woon Kyoung Sung
http://arxiv.org/abs/1901.07647v1
• [cs.LG]Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract)
Quanshi Zhang, Yu Yang, Ying Nian Wu
http://arxiv.org/abs/1901.07538v1
• [cs.LG]kd-switch: A Universal Online Predictor with an application to Sequential Two-Sample Testing
Alix Lhéritier, Frédéric Cazals
http://arxiv.org/abs/1901.07662v1
• [cs.LO]Predicting the Results of LTL Model Checking using Multiple Machine Learning Algorithms
Weijun Zhu, Mingliang Xu
http://arxiv.org/abs/1901.07891v1
• [cs.NA]Solving All Regression Models For Learning Gaussian Networks Using Givens Rotations
Borzou Alipourfard, Jean X. Gao
http://arxiv.org/abs/1901.07643v1
• [cs.NE]Analysis of the -CSA-ES with Repair by Projection Applied to a Conically Constrained Problem
Patrick Spettel, Hans-Georg Beyer
http://arxiv.org/abs/1901.07871v1
• [cs.NE]Can Transfer Entropy Infer Causality in Neuronal Circuits for Cognitive Processing?
Ali Tehrani-Saleh, Christoph Adami
http://arxiv.org/abs/1901.07589v1
• [cs.NE]Interpolation and Denoising of Seismic Data using Convolutional Neural Networks
Sara Mandelli, Vincenzo Lipari, Paolo Bestagini, Stefano Tubaro
http://arxiv.org/abs/1901.07927v1
• [cs.NE]Robust computation with rhythmic spike patterns
E. Paxon Frady, Friedrich T. Sommer
http://arxiv.org/abs/1901.07718v1
• [cs.NI]Blockchain-based Content Delivery Networks: Content Transparency Meets User Privacy
Thang X. Vu, Symeon Chatzinotas, Bjorn Ottersten
http://arxiv.org/abs/1901.07622v1
• [cs.RO]A Constraint Programming Approach to Simultaneous Task Allocation and Motion Scheduling for Industrial Dual-Arm Manipulation Tasks
Jan Kristof Behrens, Ralph Lange, Masoumeh Mansouri
http://arxiv.org/abs/1901.07914v1
• [cs.RO]Active Perception based Formation Control for Multiple Aerial Vehicles
Rahul Tallamraju, Eric Price, Roman Ludwig, Kamalakar Karlapalem, Heinrich H. Bülthoff, Michael J. Black, Aamir Ahmad
http://arxiv.org/abs/1901.07813v1
• [cs.RO]Cooperative coevolution of real predator robots and virtual robots in the pursuit domain
Lijun Sun, Chao Lyu, Yuhui Shi
http://arxiv.org/abs/1901.07865v1
• [cs.RO]Estimating Configuration Space Belief from Collision Checks for Motion Planning
Sumit Kumar, Sushman Choudhary, Siddhartha Srinivasa
http://arxiv.org/abs/1901.07646v1
• [cs.RO]Provable Infinite-Horizon Real-Time Planning for Repetitive Tasks
Fahad Islam, Oren Salzman, Maxim Likhachev
http://arxiv.org/abs/1901.07698v1
• [cs.RO]Robust Photogeometric Localization over Time for Map-Centric Loop Closure
Chanoh Park, Soohwan Kim, Peyman Moghadam, Jiadong Guo, Sridha Sridharan, Clinton Fookes
http://arxiv.org/abs/1901.07660v1
• [cs.SI]Approximate k-Cover in Hypergraphs: Efficient Algorithms, and Applications
Hung Nguyen, Phuc Thai, My Thai, Tam Vu, Thang Dinh
http://arxiv.org/abs/1901.07928v1
• [cs.SI]The Junk News Aggregator: Examining junk news posted on Facebook, starting with the 2018 US Midterm Elections
Dimitra, Liotsiou, Bence Kollanyi, Philip N. Howard
http://arxiv.org/abs/1901.07920v1
• [cs.SY]Second Order Statistics Analysis and Comparison between Arithmetic and Geometric Average Fusion
Tiancheng Li, Hongqi Fan, Jesús G. Herrero, Juan M Corchado
http://arxiv.org/abs/1901.08015v1
• [eess.SP]ICLabel: An automated electroencephalographic independent component classifier, dataset, and website
Luca Pion-Tonachini, Ken Kreutz-Delgado, Scott Makeig
http://arxiv.org/abs/1901.07915v1
• [eess.SP]MIMO-UFMC Transceiver Schemes for Millimeter Wave Wireless Communications
Stefano Buzzi, Carmen D'Andrea, Dejian Li, Shulan Feng
http://arxiv.org/abs/1901.07617v1
• [eess.SP]On the Uplink Achievable Rate of Massive MIMO System With Low-Resolution ADC and RF Impairments
Liangyuan Xu, Xintong Lu, Shi Jin, Feifei Gao, Yongxu Zhu
http://arxiv.org/abs/1901.07893v1
• [eess.SP]Rate Balancing in Full-Duplex MIMO Two-Way Relay Networks
Erfan Khordad, Ata Khalili, Soroush Akhlaghi
http://arxiv.org/abs/1901.07896v1
• [eess.SP]SC-Fano Decoding of Polar Codes
Min-Oh Jeong, Song-Nam Hong
http://arxiv.org/abs/1901.06791v1
• [eess.SP]Uncertainty Principle in Distributed MIMO Radars
Seyed MohammadReza Hosseini, Afshin Isazadeh, Ali Noroozi, Mohammad Ali Sebt
http://arxiv.org/abs/1901.07994v1
• [math.OC]A Universally Optimal Multistage Accelerated Stochastic Gradient Method
Necdet Serhat Aybat, Alireza Fallah, Mert Gurbuzbalaban, Asuman Ozdaglar
http://arxiv.org/abs/1901.08022v1
• [math.OC]Admissibility of solution estimators for stochastic optimization
Amitabh Basu, Tu Nguyen, Ao Sun
http://arxiv.org/abs/1901.06976v2
• [math.OC]Optimal Finite-Sum Smooth Non-Convex Optimization with SARAH
Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam
http://arxiv.org/abs/1901.07648v1
• [math.OC]Reinforcement Learning of Markov Decision Processes with Peak Constraints
Ather Gattami
http://arxiv.org/abs/1901.07839v1
• [math.ST]Central limit theorem for linear spectral statistics of general separable sample covariance matrices with applications
Huiqin Li, Yanqing Yin, Shurong Zheng
http://arxiv.org/abs/1901.07746v1
• [math.ST]Modelling and simulation of multifractal star-shaped particles
Alfredo Alegría
http://arxiv.org/abs/1901.07618v1
• [nucl-th]Neutron drip line in the Ca region from Bayesian model averaging
Léo Neufcourt, Yuchen Cao, Witold Nazarewicz, Erik Olsen, Frederi Viens
http://arxiv.org/abs/1901.07632v1
• [physics.soc-ph]Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections
Carolina Becatti, Guido Caldarelli, Renaud Lambiotte, Fabio Saracco
http://arxiv.org/abs/1901.07933v1
• [physics.soc-ph]Mathematical model of gender bias and homophily in professional hierarchies
Sara M. Clifton, Kaitlin Hill, Avinash J. Karamchandani, Eric A. Autry, Patrick McMahon, Grace Sun
http://arxiv.org/abs/1901.07600v1
• [physics.soc-ph]Navigability evaluation of complex networks by greedy routing efficiency
Alessandro Muscoloni, Carlo Vittorio Cannistraci
http://arxiv.org/abs/1901.07909v1
• [q-bio.QM]Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning
Chi-Sing Ho, Neal Jean, Catherine A. Hogan, Lena Blackmon, Stefanie S. Jeffrey, Mark Holodniy, Niaz Banaei, Amr A. E. Saleh, Stefano Ermon, Jennifer Dionne
http://arxiv.org/abs/1901.07666v1
• [quant-ph]A comparative study of estimation methods in quantum tomography
Anirudh Acharya, Theodore Kypraios, Madalin Guta
http://arxiv.org/abs/1901.07991v1
• [quant-ph]Neural Decoder for Topological Codes using Pseudo-Inverse of Parity Check Matrix
Chaitanya Chinni, Abhishek Kulkarni, Dheeraj M. Pai
http://arxiv.org/abs/1901.07535v1
• [stat.AP]Mobility-on-demand versus fixed-route transit systems: an evaluation of traveler preferences in low-income communities
Xiang Yan, Xilei Zhao, Yuan Han, Pascal Van Hentenryck, Tawanna Dillahunt
http://arxiv.org/abs/1901.07607v1
• [stat.ME]Functional Continuum Regression
Zhiyang Zhou
http://arxiv.org/abs/1901.07599v1
• [stat.ME]High-dimensional Interactions Detection with Sparse Principal Hessian Matrix
Cheng Yong Tang, Ethan X. Fang, Yuexiao Dong
http://arxiv.org/abs/1901.07970v1
• [stat.ME]Optimal Uncertainty Quantification of a risk measurement from a thermal-hydraulic code using Canonical Moments
Jerome Stenger, Fabrice Gamboa, Merlin Keller, Bertrand Iooss
http://arxiv.org/abs/1901.07903v1
• [stat.ME]Ordinal Probit Functional Regression Models with Application to Computer-Use Behavior in Rhesus Monkeys
Mark J. Meyer, Jeffrey S. Morris, Regina Paxton Gazes, Robert R. Hampton, Brent A. Coull
http://arxiv.org/abs/1901.07976v1
• [stat.ML]A Review on Quantile Regression for Stochastic Computer Experiments
Léonard Torossian, Victor Picheny, Robert Faivre, Aurélien Garivier
http://arxiv.org/abs/1901.07874v1
• [stat.ML]Aggregated Pairwise Classification of Statistical Shapes
Min Ho Cho, Sebastian Kurtek, Steven N. MacEachern
http://arxiv.org/abs/1901.07593v1
• [stat.ML]Coupling the reduced-order model and the generative model for an importance sampling estimator
Xiaoliang Wan, Shuangqing Wei
http://arxiv.org/abs/1901.07977v1
• [stat.ML]Hamiltonian Monte-Carlo for Orthogonal Matrices
Viktor Yanush, Dmitry Kropotov
http://arxiv.org/abs/1901.08045v1
• [stat.ML]Incremental Principal Component Analysis Exact implementation and continuity corrections
Vittorio Lippi, Giacomo Ceccarelli
http://arxiv.org/abs/1901.07922v1
• [stat.ML]Stein Variational Online Changepoint Detection with Applications to Hawkes Processes and Neural Networks
Gianluca Detommaso, Hanne Hoitzing, Tiangang Cui, Ardavan Alamir
http://arxiv.org/abs/1901.07987v1
• [stat.ML]Stochastic Gradient Trees
Henry Gouk, Bernhard Pfahringer, Eibe Frank
http://arxiv.org/abs/1901.07777v1
• [stat.ML]Support Estimation via Regularized and Weighted Chebyshev Approximations
I, Chien, Olgica Milenkovic
http://arxiv.org/abs/1901.07506v2
• [stat.ML]Unified efficient estimation framework for unnormalized models
Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda
http://arxiv.org/abs/1901.07710v1
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