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.GR - 计算机图形学
cs.GT - 计算机科学与博弈论
cs.HC - 人机接口
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.LO - 计算逻辑
cs.NE - 神经与进化计算
cs.RO - 机器人学
cs.SE - 软件工程
cs.SI - 社交网络与信息网络
eess.IV - 图像与视频处理
eess.SP - 信号处理
math.CO - 组合数学
math.DG - 微分几何
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.soc-ph - 物理学与社会
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]A new Potential-Based Reward Shaping for Reinforcement Learning Agent
• [cs.AI]Evolutionary Multitasking for Semantic Web Service Composition
• [cs.AI]Learning to Infer Program Sketches
• [cs.AI]Re-determinizing Information Set Monte Carlo Tree Search in Hanabi
• [cs.AI]SCEF: A Support-Confidence-aware Embedding Framework for Knowledge Graph Refinement
• [cs.AI]Timeline-based planning: Expressiveness and Complexity
• [cs.CL]A Comparative Study of Feature Selection Methods for Dialectal Arabic Sentiment Classification Using Support Vector Machine
• [cs.CL]A Fully Differentiable Beam Search Decoder
• [cs.CL]CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model
• [cs.CL]Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media
• [cs.CL]Contextual Word Representations: A Contextual Introduction
• [cs.CL]CruzAffect at AffCon 2019 Shared Task: A feature-rich approach to characterize happiness
• [cs.CL]Exploring Language Similarities with Dimensionality Reduction Technique
• [cs.CL]Improving Semantic Parsing for Task Oriented Dialog
• [cs.CL]Investigating the Effect of Segmentation Methods on Neural Model based Sentiment Analysis on Informal Short Texts in Turkish
• [cs.CL]Self-Attention Aligner: A Latency-Control End-to-End Model for ASR Using Self-Attention Network and Chunk-Hopping
• [cs.CL]Twitch Plays Pokemon, Machine Learns Twitch: Unsupervised Context-Aware Anomaly Detection for Identifying Trolls in Streaming Data
• [cs.CV]-CNN: Fast Tiny Object Detection in Large-scale Remote Sensing Images
• [cs.CV]2017 Robotic Instrument Segmentation Challenge
• [cs.CV]Accurate Segmentation of Dermoscopic Images based on Local Binary Pattern Clustering
• [cs.CV]Atlas-based automated detection of swim bladder in Medaka embryo
• [cs.CV]Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network
• [cs.CV]BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding
• [cs.CV]Contextual Encoder-Decoder Network for Visual Saliency Prediction
• [cs.CV]DC-Al GAN: Pseudoprogression and True Tumor Progression of Glioblastoma multiform Image Classification Based On DCGAN and Alexnet
• [cs.CV]DIViS: Domain Invariant Visual Servoing for Collision-Free Goal Reaching
• [cs.CV]Decomposing multispectral face images into diffuse and specular shading and biophysical parameters
• [cs.CV]Deep Learning for Image Super-resolution: A Survey
• [cs.CV]Detecting Colorized Images via Convolutional Neural Networks: Toward High Accuracy and Good Generalization
• [cs.CV]Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank
• [cs.CV]Exploring Stereovision-Based 3-D Scene Reconstruction for Augmented Reality
• [cs.CV]Fast Pedestrian Detection based on T-CENTRIST
• [cs.CV]Fully-Featured Attribute Transfer
• [cs.CV]GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
• [cs.CV]Generative Adversarial Networks Synthesize Realistic OCT Images of the Retina
• [cs.CV]HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification
• [cs.CV]LapEPI-Net: A Laplacian Pyramid EPI structure for Learning-based Dense Light Field Reconstruction
• [cs.CV]LocalNorm: Robust Image Classification through Dynamically Regularized Normalization
• [cs.CV]Min-Entropy Latent Model for Weakly Supervised Object Detection
• [cs.CV]Multi-layer Depth and Epipolar Feature Transformers for 3D Scene Reconstruction
• [cs.CV]Object Recognition under Multifarious Conditions: A Reliability Analysis and A Feature Similarity-based Performance Estimation
• [cs.CV]Online PCB Defect Detector On A New PCB Defect Dataset
• [cs.CV]PIXOR: Real-time 3D Object Detection from Point Clouds
• [cs.CV]Periocular Recognition in the Wild with Orthogonal Combination of Local Binary Coded Pattern in Dual-stream Convolutional Neural Network
• [cs.CV]Persistent entropy: a scale-invariant topological statistic for analyzing cell arrangements
• [cs.CV]PointIT: A Fast Tracking Framework Based on 3D Instance Segmentation
• [cs.CV]Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
• [cs.CV]SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction
• [cs.CV]Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey
• [cs.CV]Semantically Interpretable and Controllable Filter Sets
• [cs.CV]Semi-supervised Learning on Graph with an Alternating Diffusion Process
• [cs.CV]Single-shot Channel Pruning Based on Alternating Direction Method of Multipliers
• [cs.CV]Skin Lesion Segmentation and Classification with Deep Learning System
• [cs.CV]Speeding up convolutional networks pruning with coarse ranking
• [cs.CV]Structured Group Local Sparse Tracker
• [cs.CV]Study of dynamical system based obstacle avoidance via manipulating orthogonal coordinates
• [cs.CV]Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks
• [cs.CV]Using Persistent Homology to Quantify a Diurnal Cycle in Hurricane Felix
• [cs.CY]Analysis of the Main Factors Affecting M-Commerce Adoption in Iraq
• [cs.CY]BYOD, Personal Area Networks (PANs) and IOT: Threats to Patients Privacy
• [cs.CY]Base Station Allocation of Defibrillator Drones in Mountainous Regions
• [cs.CY]Digital Humanities Readiness Assessment Framework: DHuRAF
• [cs.CY]Local Media and Geo-situated Responses to Brexit: A Quantitative Analysis of Twitter, News and Survey Data
• [cs.CY]Openbots
• [cs.CY]Quality of Life Assessment of Diabetic patients from health-related blogs
• [cs.CY]What Makes a Good Team? A Large-scale Study on the Effect of Team Composition in Honor of Kings
• [cs.DC]A Timer-Augmented Cost Function for Load Balanced DSMC
• [cs.DC]Beyond the Memory Wall: A Case for Memory-centric HPC System for Deep Learning
• [cs.DC]Complexity of the quorum intersection property of the Federated Byzantine Agreement System
• [cs.DC]Reactive Liquid: Optimized Liquid Architecture for Elastic and Resilient Distributed Data Processing
• [cs.DS]RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data
• [cs.GR]Local Fourier Slice Photography
• [cs.GT]Limited Lookahead in Imperfect-Information Games
• [cs.HC]An Automated Testing Framework for Conversational Agents
• [cs.HC]Outlining the Design Space of Explainable Intelligent Systems for Medical Diagnosis
• [cs.IR]"The Michael Jordan of Greatness": Extracting Vossian Antonomasia from Two Decades of the New York Times, 1987-2007
• [cs.IR]Collaborative Similarity Embedding for Recommender Systems
• [cs.IR]Multiple Document Representations from News Alerts for Automated Bio-surveillance Event Detection
• [cs.IR]Optimizing Stochastic Gradient Descent in Text Classification Based on Fine-Tuning Hyper-Parameters Approach. A Case Study on Automatic Classification of Global Terrorist Attacks
• [cs.IR]TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts
• [cs.IR]Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences
• [cs.IT]A Novel Error Performance Analysis Methodology for OFDM-IM
• [cs.IT]Adapted Decimation on Finite Frames for Arbitrary Orders of Sigma-Delta Quantization
• [cs.IT]Analysis of Data Harvesting by Unmanned Aerial Vehicles
• [cs.IT]Asymptotic Limits of Privacy in Bayesian Time Series Matching
• [cs.IT]DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications
• [cs.IT]Delay Outage Probability of Multi-relay Selection for Mobile Relay Edge Computing Systems
• [cs.IT]Distributed Learning for Channel Allocation Over a Shared Spectrum
• [cs.IT]FDD Massive MIMO Based on Efficient Downlink Channel Reconstruction
• [cs.IT]Group testing: an information theory perspective
• [cs.IT]Load Balancing in 5G HetNets with Millimeter Wave Integrated Access and Backhaul
• [cs.IT]Maximum distance separable codes to order
• [cs.IT]Metric properties of homogeneous and spatially inhomogeneous F-divergences
• [cs.IT]Moment-Based Bound on Peak-to-Average Power Ratio and Reduction with Unitary Matrix
• [cs.IT]Neural Network-Based Dynamic Threshold Detection for Non-Volatile Memories
• [cs.IT]On the Equivalence of Semidifinite Relaxations for MIMO Detection with General Constellations
• [cs.IT]Optimal Sequence and SINR for Desired User in Asynchronous CDMA System
• [cs.IT]Optimized Trajectory Design in UAV Based Cellular Networks for 3D Users: A Double Q-Learning Approach
• [cs.IT]Private Inner Product Retrieval for Distributed Machine Learning
• [cs.IT]Simple Approximations of the SIR Meta Distribution in General Cellular Networks
• [cs.IT]Transportation Proofs of Rényi Entropy Power Inequalities
• [cs.IT]Zero-Error Capacity of Duplication Channels
• [cs.LG]A Little Is Enough: Circumventing Defenses For Distributed Learning
• [cs.LG]A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection
• [cs.LG]A parallel Fortran framework for neural networks and deep learning
• [cs.LG]A semi-supervised deep residual network for mode detection in Wi-Fi signals
• [cs.LG]Adaptive Sequence Submodularity
• [cs.LG]Adversarial Examples in RF Deep Learning: Detection of the Attack and its Physical Robustness
• [cs.LG]Asymptotic Finite Sample Information Losses in Neural Classifiers
• [cs.LG]Attention-Based Prototypical Learning Towards Interpretable, Confident and Robust Deep Neural Networks
• [cs.LG]Conformal calibrators
• [cs.LG]Deep Convolutional Sum-Product Networks for Probabilistic Image Representations
• [cs.LG]Designing recurrent neural networks by unfolding an l1-l1 minimization algorithm
• [cs.LG]Detecting and Diagnosing Incipient Building Faults Using Uncertainty Information from Deep Neural Networks
• [cs.LG]Fast Efficient Hyperparameter Tuning for Policy Gradients
• [cs.LG]Grids versus Graphs: Partitioning Space for Improved Taxi Demand-Supply Forecasts
• [cs.LG]Incremental Cluster Validity Indices for Hard Partitions: Extensions and Comparative Study
• [cs.LG]Intra- and Inter-epoch Temporal Context Network (IITNet) for Automatic Sleep Stage Scoring
• [cs.LG]Learning Linear-Quadratic Regulators Efficiently with only Regret
• [cs.LG]Making Convex Loss Functions Robust to Outliers using -Exponentiated Transformation
• [cs.LG]Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning
• [cs.LG]ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems
• [cs.LG]On Evaluating Adversarial Robustness
• [cs.LG]On resampling vs. adjusting probabilistic graphical models in estimation of distribution algorithms
• [cs.LG]Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization
• [cs.LG]Prediction of Porosity and Permeability Alteration based on Machine Learning Algorithms
• [cs.LG]ProLoNets: Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning
• [cs.LG]Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization
• [cs.LG]RES-SE-NET: Boosting Performance of Resnets by Enhancing Bridge-connections
• [cs.LG]Robustness of Neural Networks: A Probabilistic and Practical Approach
• [cs.LG]STCN: Stochastic Temporal Convolutional Networks
• [cs.LG]Screening Rules for Lasso with Non-Convex Sparse Regularizers
• [cs.LG]Structural Recurrent Neural Network for Traffic Speed Prediction
• [cs.LG]WiSE-VAE: Wide Sample Estimator VAE
• [cs.LO]Appendix for: Cut-free Calculi and Relational Semantics for Temporal STIT logics
• [cs.LO]Iterated Belief Base Revision: A Dynamic Epistemic Logic Approach
• [cs.NE]Differentiable reservoir computing
• [cs.NE]Reactive, Proactive, and Inductive Agents: An evolutionary path for biological and artificial spiking networks
• [cs.RO]"Touching to See" and "Seeing to Feel": Robotic Cross-modal SensoryData Generation for Visual-Tactile Perception
• [cs.RO]A Fleet of Miniature Cars for Experiments in Cooperative Driving
• [cs.RO]MetaGrasp: Data Efficient Grasping by Affordance Interpreter Network
• [cs.RO]Real-Time Trajectory Planning for AGV in the Presence of Moving Obstacles: A First-Search-Then-Optimization Approach
• [cs.SE]DeepFault: Fault Localization for Deep Neural Networks
• [cs.SI]A Broad Evaluation of the Tor English Content Ecosystem
• [cs.SI]Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning?
• [cs.SI]Learning Topological Representation for Networks via Hierarchical Sampling
• [cs.SI]Replications in quantitative and qualitative methods: a new era for commensurable digital social sciences
• [cs.SI]The Ambivalence of Cultural Homophily: Field Positions, Semantic Similarities, and Social Network Ties in Creative Collectives
• [eess.IV]Automated Detection of Regions of Interest for Brain Perfusion MR Images
• [eess.SP]Spatial Channel Covariance Estimation for Hybrid Architectures Based on Tensor Decompositions
• [math.CO]Jacobi Sums and Correlations of Sidelnikov Sequences
• [math.DG]On the geometric structure ofsome statistical manifolds
• [math.OC]Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization
• [math.OC]The Kalai-Smorodinski solution for many-objective Bayesian optimization
• [math.PR]Optimal Scaling and Shaping of Random Walk Metropolis via Diffusion Limits of Block-I.I.D. Targets
• [math.ST]Aggregated test of independence based on HSIC measures
• [math.ST]Intermediate efficiency of tests under heavy-tailed alternatives
• [math.ST]Towards Explainable AI: Significance Tests for Neural Networks
• [physics.soc-ph]Fundamental Diagram of Traffic Flow from Prigogine-Herman-Enskog Equation
• [physics.soc-ph]Statistical properties of user activity fluctuations in virtual worlds
• [q-bio.NC]A computational model for grid maps in neural populations
• [q-bio.NC]Power contours: optimising sample size and precision in experimental psychology and human neuroscience
• [stat.AP]A Bayesian binary algorithm for RMS-based acoustic signal segmentation
• [stat.AP]A Statistical Analysis of Noisy Crowdsourced Weather Data
• [stat.AP]A feature-based framework for detecting technical outliers in water-quality data from in situ sensors
• [stat.AP]Detected changes in precipitation extremes at their native scales derived from in situ measurements
• [stat.AP]Model fitting in Multiple Systems Analysis for the quantification of Modern Slavery: Classical and Bayesian approaches
• [stat.AP]Monte Carlo Sampling Bias in the Microwave Uncertainty Framework
• [stat.AP]Optimized data exploration applied to the simulation of a chemical process
• [stat.CO]Is a single unique Bayesian network enough to accurately represent your data?
• [stat.CO]LISA: a MATLAB package for Longitudinal Image Sequence Analysis
• [stat.ME]Approximate Bayesian Model Inversion for PDEs with Heterogeneous and State-Dependent Coefficients
• [stat.ME]Approximate leave-future-out cross-validation for time series models
• [stat.ME]Assessing Biosimilarity using FunctionalMetrics
• [stat.ME]Bayesian Methods for Multiple Mediators: Relating Principal Stratification and Causal Mediation in the Analysis of Power Plant Emission Controls
• [stat.ME]Bayesian Regularization: From Tikhonov to Horseshoe
• [stat.ME]Generalizing trial findings in nested trial designs with sub-sampling of non-randomized individuals
• [stat.ME]Privacy Preserving Integrative Regression Analysis of High-dimensional Heterogeneous Data
• [stat.ME]Projected Pólya Tree
• [stat.ME]Separating common (global and local) and distinct variation in multiple mixed types data sets
• [stat.ME]Sequentially additive nonignorable missing data modeling using auxiliary marginal information
• [stat.ME]Sparse Regression: Scalable algorithms and empirical performance
• [stat.ME]What is an Ordinal Latent Trait Model?
• [stat.ML]A Unifying Bayesian View of Continual Learning
• [stat.ML]Context-Based Dynamic Pricing with Online Clustering
• [stat.ML]Differentially Private Continual Learning
• [stat.ML]Going deep in clustering high-dimensional data: deep mixtures of unigrams for uncovering topics in textual data
• [stat.ML]Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit
• [stat.ML]Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
·····································
• [cs.AI]A new Potential-Based Reward Shaping for Reinforcement Learning Agent
Babak Badnava, Nasser Mozayani
http://arxiv.org/abs/1902.06239v1
• [cs.AI]Evolutionary Multitasking for Semantic Web Service Composition
Chen Wang, Hui Ma, Gang Chen, Sven Hartmann
http://arxiv.org/abs/1902.06370v1
• [cs.AI]Learning to Infer Program Sketches
Maxwell Nye, Luke Hewitt, Joshua Tenenbaum, Armando Solar-Lezama
http://arxiv.org/abs/1902.06349v1
• [cs.AI]Re-determinizing Information Set Monte Carlo Tree Search in Hanabi
James Goodman
http://arxiv.org/abs/1902.06075v1
• [cs.AI]SCEF: A Support-Confidence-aware Embedding Framework for Knowledge Graph Refinement
Yu Zhao, Ji Liu
http://arxiv.org/abs/1902.06377v1
• [cs.AI]Timeline-based planning: Expressiveness and Complexity
Nicola Gigante
http://arxiv.org/abs/1902.06123v1
• [cs.CL]A Comparative Study of Feature Selection Methods for Dialectal Arabic Sentiment Classification Using Support Vector Machine
Omar Al-Harbi
http://arxiv.org/abs/1902.06242v1
• [cs.CL]A Fully Differentiable Beam Search Decoder
Ronan Collobert, Awni Hannun, Gabriel Synnaeve
http://arxiv.org/abs/1902.06022v1
• [cs.CL]CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model
Florian Mai, Lukas Galke, Ansgar Scherp
http://arxiv.org/abs/1902.06423v1
• [cs.CL]Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media
Khuong Vo, Tri Nguyen, Dang Pham, Mao Nguyen, Minh Truong, Trung Mai, Tho Quan
http://arxiv.org/abs/1902.06050v1
• [cs.CL]Contextual Word Representations: A Contextual Introduction
Noah A. Smith
http://arxiv.org/abs/1902.06006v1
• [cs.CL]CruzAffect at AffCon 2019 Shared Task: A feature-rich approach to characterize happiness
Jiaqi Wu, Ryan Compton, Geetanjali Rakshit, Marilyn Walker, Pranav Anand, Steve Whittaker
http://arxiv.org/abs/1902.06024v1
• [cs.CL]Exploring Language Similarities with Dimensionality Reduction Technique
Sangarshanan Veeraraghavan
http://arxiv.org/abs/1902.06092v1
• [cs.CL]Improving Semantic Parsing for Task Oriented Dialog
Arash Einolghozati, Panupong Pasupat, Sonal Gupta, Rushin Shah, Mrinal Mohit, Mike Lewis, Luke Zettlemoyer
http://arxiv.org/abs/1902.06000v1
• [cs.CL]Investigating the Effect of Segmentation Methods on Neural Model based Sentiment Analysis on Informal Short Texts in Turkish
Fatih Kurt, Dilek Kisa, Pinar Karagoz
http://arxiv.org/abs/1902.06635v1
• [cs.CL]Self-Attention Aligner: A Latency-Control End-to-End Model for ASR Using Self-Attention Network and Chunk-Hopping
Linhao Dong, Feng Wang, Bo Xu
http://arxiv.org/abs/1902.06450v1
• [cs.CL]Twitch Plays Pokemon, Machine Learns Twitch: Unsupervised Context-Aware Anomaly Detection for Identifying Trolls in Streaming Data
Albert Haque
http://arxiv.org/abs/1902.06208v1
• [cs.CV]-CNN: Fast Tiny Object Detection in Large-scale Remote Sensing Images
Jiangmiao Pang, Cong Li, Jianping Shi, Zhihai Xu, Huajun Feng
http://arxiv.org/abs/1902.06042v1
• [cs.CV]2017 Robotic Instrument Segmentation Challenge
Max Allan, Alex Shvets, Thomas Kurmann, Zichen Zhang, Rahul Duggal, Yun-Hsuan Su, Nicola Rieke, Iro Laina, Niveditha Kalavakonda, Sebastian Bodenstedt, Luis Herrera, Wenqi Li, Vladimir Iglovikov, Huoling Luo, Jian Yang, Danail Stoyanov, Lena Maier-Hein, Stefanie Speidel, Mahdi Azizian
http://arxiv.org/abs/1902.06426v1
• [cs.CV]Accurate Segmentation of Dermoscopic Images based on Local Binary Pattern Clustering
Pedro M. M. Pereira, Rui Fonseca-Pinto, Rui Pedro Paiva, Luis M. N. Tavora, Pedro A. A. Assuncao, Sergio M. M. de Faria1
http://arxiv.org/abs/1902.06347v1
• [cs.CV]Atlas-based automated detection of swim bladder in Medaka embryo
Diane Genest, Marc Léonard, Jean Cousty, Noémie De Crozé, Hugues Talbot
http://arxiv.org/abs/1902.06130v1
• [cs.CV]Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network
Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth, Xiaowei Ding, Demetri Terzopoulos, Nima Tajbakhsh
http://arxiv.org/abs/1902.06362v1
• [cs.CV]BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding
Gencer Sumbul, Marcela Charfuelan, Begüm Demir, Volker Markl
http://arxiv.org/abs/1902.06148v1
• [cs.CV]Contextual Encoder-Decoder Network for Visual Saliency Prediction
Alexander Kroner, Mario Senden, Kurt Driessens, Rainer Goebel
http://arxiv.org/abs/1902.06634v1
• [cs.CV]DC-Al GAN: Pseudoprogression and True Tumor Progression of Glioblastoma multiform Image Classification Based On DCGAN and Alexnet
Meiyu Li
http://arxiv.org/abs/1902.06085v1
• [cs.CV]DIViS: Domain Invariant Visual Servoing for Collision-Free Goal Reaching
Fereshteh Sadeghi
http://arxiv.org/abs/1902.05947v1
• [cs.CV]Decomposing multispectral face images into diffuse and specular shading and biophysical parameters
Sarah Alotaibi, William A. P. Smith
http://arxiv.org/abs/1902.06557v1
• [cs.CV]Deep Learning for Image Super-resolution: A Survey
Zhihao Wang, Jian Chen, Steven C. H. Hoi
http://arxiv.org/abs/1902.06068v1
• [cs.CV]Detecting Colorized Images via Convolutional Neural Networks: Toward High Accuracy and Good Generalization
Weize Quan, Dong-Ming Yan, Kai Wang, Xiaopeng Zhang, Denis Pellerin
http://arxiv.org/abs/1902.06222v1
• [cs.CV]Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank
Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov
http://arxiv.org/abs/1902.06285v1
• [cs.CV]Exploring Stereovision-Based 3-D Scene Reconstruction for Augmented Reality
Guang-Yu Nie, Yun Liu, Cong Wang, Yue Liu, Yongtian Wang
http://arxiv.org/abs/1902.06255v1
• [cs.CV]Fast Pedestrian Detection based on T-CENTRIST
Hongyin Ni, Bin Lia
http://arxiv.org/abs/1902.06218v1
• [cs.CV]Fully-Featured Attribute Transfer
De Xie, Muli Yang, Cheng Deng, Wei Liu, Dacheng Tao
http://arxiv.org/abs/1902.06258v1
• [cs.CV]GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
Baris Gecer, Stylianos Ploumpis, Irene Kotsia, Stefanos Zafeiriou
http://arxiv.org/abs/1902.05978v1
• [cs.CV]Generative Adversarial Networks Synthesize Realistic OCT Images of the Retina
Stephen G. Odaibo, M. D., M. S., M. S.
http://arxiv.org/abs/1902.06676v1
• [cs.CV]HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification
Swalpa Kumar Roy, Gopal Krishna, Shiv Ram Dubey, Bidyut B. Chaudhuri
http://arxiv.org/abs/1902.06701v1
• [cs.CV]LapEPI-Net: A Laplacian Pyramid EPI structure for Learning-based Dense Light Field Reconstruction
Gaochang Wu, Yebin Liu, Lu Fang, Tianyou Chai
http://arxiv.org/abs/1902.06221v1
• [cs.CV]LocalNorm: Robust Image Classification through Dynamically Regularized Normalization
Bojian Yin, Siebren Schaafsma, Henk Corporaal, H. Steven Scholte, Sander M. Bohte
http://arxiv.org/abs/1902.06550v1
• [cs.CV]Min-Entropy Latent Model for Weakly Supervised Object Detection
Fang Wan, Pengxu Wei, Zhenjun Han, Jianbin Jiao, Qixiang Ye
http://arxiv.org/abs/1902.06057v1
• [cs.CV]Multi-layer Depth and Epipolar Feature Transformers for 3D Scene Reconstruction
Daeyun Shin, Zhile Ren, Erik B. Sudderth, Charless C. Fowlkes
http://arxiv.org/abs/1902.06729v1
• [cs.CV]Object Recognition under Multifarious Conditions: A Reliability Analysis and A Feature Similarity-based Performance Estimation
Dogancan Temel, Jinsol Lee, Ghassan AlRegib
http://arxiv.org/abs/1902.06585v1
• [cs.CV]Online PCB Defect Detector On A New PCB Defect Dataset
Sanli Tang, Fan He, Xiaolin Huang, Jie Yang
http://arxiv.org/abs/1902.06197v1
• [cs.CV]PIXOR: Real-time 3D Object Detection from Point Clouds
Bin Yang, Wenjie Luo, Raquel Urtasun
http://arxiv.org/abs/1902.06326v1
• [cs.CV]Periocular Recognition in the Wild with Orthogonal Combination of Local Binary Coded Pattern in Dual-stream Convolutional Neural Network
Leslie Ching Ow Tiong, Andrew Beng Jin Teoh, Yunli Lee
http://arxiv.org/abs/1902.06383v1
• [cs.CV]Persistent entropy: a scale-invariant topological statistic for analyzing cell arrangements
N. Atienza, L. M. Escudero, M. J. Jimenez, M. Soriano-Trigueros
http://arxiv.org/abs/1902.06467v1
• [cs.CV]PointIT: A Fast Tracking Framework Based on 3D Instance Segmentation
Yuan Wang, Yang Yu, Ming Liu
http://arxiv.org/abs/1902.06379v1
• [cs.CV]Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
David Tellez, Geert Litjens, Peter Bandi, Wouter Bulten, John-Melle Bokhorst, Francesco Ciompi, Jeroen van der Laak
http://arxiv.org/abs/1902.06543v1
• [cs.CV]SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction
Zhongnian Li, Tao Zhang, Daoqiang Zhang
http://arxiv.org/abs/1902.06455v1
• [cs.CV]Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey
Longlong Jing, Yingli Tian
http://arxiv.org/abs/1902.06162v1
• [cs.CV]Semantically Interpretable and Controllable Filter Sets
Mohit Prabhushankar, Gukyeong Kwon, Dogancan Temel, Ghassan AlRegib
http://arxiv.org/abs/1902.06334v1
• [cs.CV]Semi-supervised Learning on Graph with an Alternating Diffusion Process
Qilin Li, Senjian An, Ling Li, Wanquan Liu
http://arxiv.org/abs/1902.06105v1
• [cs.CV]Single-shot Channel Pruning Based on Alternating Direction Method of Multipliers
Chengcheng Li, Zi Wang, Xiangyang Wang, Hairong Qi
http://arxiv.org/abs/1902.06382v1
• [cs.CV]Skin Lesion Segmentation and Classification with Deep Learning System
Devansh Bisla, Anna Choromanska, Jennifer A. Stein, David Polsky, Russell Berman
http://arxiv.org/abs/1902.06061v1
• [cs.CV]Speeding up convolutional networks pruning with coarse ranking
Zi Wang, Chengcheng Li, Dali Wang, Xiangyang Wang, Hairong Qi
http://arxiv.org/abs/1902.06385v1
• [cs.CV]Structured Group Local Sparse Tracker
Mohammadreza Javanmardi, Xiaojun Qi
http://arxiv.org/abs/1902.06182v1
• [cs.CV]Study of dynamical system based obstacle avoidance via manipulating orthogonal coordinates
Weiya Ren
http://arxiv.org/abs/1902.05343v2
• [cs.CV]Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks
Jinyong Hou, Xuejie Ding, Jeremiah D. Deng
http://arxiv.org/abs/1902.06328v1
• [cs.CV]Using Persistent Homology to Quantify a Diurnal Cycle in Hurricane Felix
Sarah Tymochko, Elizabeth Munch, Jason Dunion, Kristen Corbosiero, Ryan Torn
http://arxiv.org/abs/1902.06202v1
• [cs.CY]Analysis of the Main Factors Affecting M-Commerce Adoption in Iraq
Alaa Mahdi Sahi
http://arxiv.org/abs/1902.06682v1
• [cs.CY]BYOD, Personal Area Networks (PANs) and IOT: Threats to Patients Privacy
Samara Ahmed
http://arxiv.org/abs/1902.06462v1
• [cs.CY]Base Station Allocation of Defibrillator Drones in Mountainous Regions
Christian Wankmüller, Christian Truden, Christopher Korzen, Philipp Hungerländer, Gerald Reiner, Ewald Kolesnik
http://arxiv.org/abs/1902.06685v1
• [cs.CY]Digital Humanities Readiness Assessment Framework: DHuRAF
Hossein Hassani, Emir Turajlić, Kemal Taljanović
http://arxiv.org/abs/1902.06532v1
• [cs.CY]Local Media and Geo-situated Responses to Brexit: A Quantitative Analysis of Twitter, News and Survey Data
Genevieve Gorrell, Mehmet E. Bakir, Luke Temple, Diana Maynard, Paolo Cifariello, Jackie Harrison, J. Miguel Kanai, Kalina Bontcheva
http://arxiv.org/abs/1902.06521v1
• [cs.CY]Openbots
Dennis Assenmacher, Lena Adam, Lena Frischlich, Heike Trautmann, Christian Grimme
http://arxiv.org/abs/1902.06691v1
• [cs.CY]Quality of Life Assessment of Diabetic patients from health-related blogs
Andrea Lenzi, Marianna Maranghi, Giovanni Stilo, Paola Velardi
http://arxiv.org/abs/1902.06548v1
• [cs.CY]What Makes a Good Team? A Large-scale Study on the Effect of Team Composition in Honor of Kings
Ziqiang Cheng, Yang Yang, Chenhao Tan, Denny Cheng, Yueting Zhuang, Alex Cheng
http://arxiv.org/abs/1902.06432v1
• [cs.DC]A Timer-Augmented Cost Function for Load Balanced DSMC
William McDoniel, Paolo Bientinesi
http://arxiv.org/abs/1902.06040v1
• [cs.DC]Beyond the Memory Wall: A Case for Memory-centric HPC System for Deep Learning
Youngeun Kwon, Minsoo Rhu
http://arxiv.org/abs/1902.06468v1
• [cs.DC]Complexity of the quorum intersection property of the Federated Byzantine Agreement System
Łukasz Lachowski
http://arxiv.org/abs/1902.06493v1
• [cs.DC]Reactive Liquid: Optimized Liquid Architecture for Elastic and Resilient Distributed Data Processing
Seyed Esmaeil Mirvakili, MohammadAmin Fazli, Jafar Habibi
http://arxiv.org/abs/1902.05968v1
• [cs.DS]RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data
Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk
http://arxiv.org/abs/1902.06687v1
• [cs.GR]Local Fourier Slice Photography
Christian Lessig
http://arxiv.org/abs/1902.06082v1
• [cs.GT]Limited Lookahead in Imperfect-Information Games
Christian Kroer, Tuomas Sandholm
http://arxiv.org/abs/1902.06335v1
• [cs.HC]An Automated Testing Framework for Conversational Agents
Soodeh Atefi, Mohammad Amin Alipour
http://arxiv.org/abs/1902.06193v1
• [cs.HC]Outlining the Design Space of Explainable Intelligent Systems for Medical Diagnosis
Yao Xie, Ge Gao, Xiang 'Anthony' Chen
http://arxiv.org/abs/1902.06019v1
• [cs.IR]"The Michael Jordan of Greatness": Extracting Vossian Antonomasia from Two Decades of the New York Times, 1987-2007
Frank Fischer, Robert Jäschke
http://arxiv.org/abs/1902.06428v1
• [cs.IR]Collaborative Similarity Embedding for Recommender Systems
Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai, Yi-Hsuan Yang
http://arxiv.org/abs/1902.06188v1
• [cs.IR]Multiple Document Representations from News Alerts for Automated Bio-surveillance Event Detection
Aaron Tuor, Fnu Anubhav, Lauren Charles
http://arxiv.org/abs/1902.06231v1
• [cs.IR]Optimizing Stochastic Gradient Descent in Text Classification Based on Fine-Tuning Hyper-Parameters Approach. A Case Study on Automatic Classification of Global Terrorist Attacks
Shadi Diab
http://arxiv.org/abs/1902.06542v1
• [cs.IR]TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts
Michihiro Yasunaga, John Lafferty
http://arxiv.org/abs/1902.06034v1
• [cs.IR]Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences
Yixin Cao, Xiang Wang, Xiangnan He, Zikun hu, Tat-Seng Chua
http://arxiv.org/abs/1902.06236v1
• [cs.IT]A Novel Error Performance Analysis Methodology for OFDM-IM
Shuping Dang, Guoqing Ma, Basem Shihada, Mohamed-Slim Alouini
http://arxiv.org/abs/1902.06213v1
• [cs.IT]Adapted Decimation on Finite Frames for Arbitrary Orders of Sigma-Delta Quantization
Kung-Ching Lin
http://arxiv.org/abs/1902.05976v1
• [cs.IT]Analysis of Data Harvesting by Unmanned Aerial Vehicles
Chang-sik Choi, Francois Baccelli, Gustavo de Veciana
http://arxiv.org/abs/1902.06350v1
• [cs.IT]Asymptotic Limits of Privacy in Bayesian Time Series Matching
Nazanin Takbiri, Dennis L. Goeckel, Amir Houmansadr, Hossein Pishro-Nik
http://arxiv.org/abs/1902.06404v1
• [cs.IT]DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications
Ahmed Alkhateeb
http://arxiv.org/abs/1902.06435v1
• [cs.IT]Delay Outage Probability of Multi-relay Selection for Mobile Relay Edge Computing Systems
Jie Liang, Zhiyong Chen, Cheng Li, Bin Xia, Ning Liu
http://arxiv.org/abs/1902.06012v1
• [cs.IT]Distributed Learning for Channel Allocation Over a Shared Spectrum
S. M. Zafaruddin, Ilai Bistritz, Amir Leshem, Dusit, Niyato
http://arxiv.org/abs/1902.06353v1
• [cs.IT]FDD Massive MIMO Based on Efficient Downlink Channel Reconstruction
Yu Han, Qi Liu, Chao-Kai Wen, Shi Jin, Kai-Kit Wong
http://arxiv.org/abs/1902.06174v1
• [cs.IT]Group testing: an information theory perspective
Matthew Aldridge, Oliver Johnson, Jonathan Scarlett
http://arxiv.org/abs/1902.06002v1
• [cs.IT]Load Balancing in 5G HetNets with Millimeter Wave Integrated Access and Backhaul
Chiranjib Saha, Harpreet S. Dhillon
http://arxiv.org/abs/1902.06300v1
• [cs.IT]Maximum distance separable codes to order
Ted Hurley, Donny Hurley, Barry Hurley
http://arxiv.org/abs/1902.06624v1
• [cs.IT]Metric properties of homogeneous and spatially inhomogeneous F-divergences
Nicolò De Ponti
http://arxiv.org/abs/1902.06305v1
• [cs.IT]Moment-Based Bound on Peak-to-Average Power Ratio and Reduction with Unitary Matrix
Hirofumi Tsuda
http://arxiv.org/abs/1902.06420v1
• [cs.IT]Neural Network-Based Dynamic Threshold Detection for Non-Volatile Memories
Zhen Mei, Kui Cai, Xingwei Zhong
http://arxiv.org/abs/1902.06289v1
• [cs.IT]On the Equivalence of Semidifinite Relaxations for MIMO Detection with General Constellations
Ya-Feng Liu, Zi Xu, Cheng Lu
http://arxiv.org/abs/1902.06381v1
• [cs.IT]Optimal Sequence and SINR for Desired User in Asynchronous CDMA System
Hirofumi Tsuda
http://arxiv.org/abs/1902.06422v1
• [cs.IT]Optimized Trajectory Design in UAV Based Cellular Networks for 3D Users: A Double Q-Learning Approach
Xuanlin Liu, Mingzhe Chen, Changchuan Yin
http://arxiv.org/abs/1902.06610v1
• [cs.IT]Private Inner Product Retrieval for Distributed Machine Learning
Mohammad Hossein Mousavi, Mohammad Ali Maddah-Ali, Mahtab Mirmohseni
http://arxiv.org/abs/1902.06319v1
• [cs.IT]Simple Approximations of the SIR Meta Distribution in General Cellular Networks
Sanket S. Kalamkar, Martin Haenggi
http://arxiv.org/abs/1902.06457v1
• [cs.IT]Transportation Proofs of Rényi Entropy Power Inequalities
Olivier Rioul
http://arxiv.org/abs/1902.06120v1
• [cs.IT]Zero-Error Capacity of Duplication Channels
Mladen Kovačević
http://arxiv.org/abs/1902.06275v1
• [cs.LG]A Little Is Enough: Circumventing Defenses For Distributed Learning
Moran Baruch, Gilad Baruch, Yoav Goldberg
http://arxiv.org/abs/1902.06156v1
• [cs.LG]A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection
Baihong Jin, Yuxin Chen, Dan Li, Kameshwar Poolla, Alberto Sangiovanni-Vincentelli
http://arxiv.org/abs/1902.06361v1
• [cs.LG]A parallel Fortran framework for neural networks and deep learning
Milan Curcic
http://arxiv.org/abs/1902.06714v1
• [cs.LG]A semi-supervised deep residual network for mode detection in Wi-Fi signals
Arash Kalatian, Bilal Farooq
http://arxiv.org/abs/1902.06284v1
• [cs.LG]Adaptive Sequence Submodularity
Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi
http://arxiv.org/abs/1902.05981v1
• [cs.LG]Adversarial Examples in RF Deep Learning: Detection of the Attack and its Physical Robustness
Silvija Kokalj-Filipovic, Rob Miller
http://arxiv.org/abs/1902.06044v1
• [cs.LG]Asymptotic Finite Sample Information Losses in Neural Classifiers
Brandon Foggo, Nanpeng Yu, Jie Shi, Yuanqi Gao
http://arxiv.org/abs/1902.05991v1
• [cs.LG]Attention-Based Prototypical Learning Towards Interpretable, Confident and Robust Deep Neural Networks
Sercan O. Arik, Tomas Pfister
http://arxiv.org/abs/1902.06292v1
• [cs.LG]Conformal calibrators
Vladimir Vovk, Ivan Petej, Paolo Toccaceli, Alex Gammerman
http://arxiv.org/abs/1902.06579v1
• [cs.LG]Deep Convolutional Sum-Product Networks for Probabilistic Image Representations
Jos van de Wolfshaar, Andrzej Pronobis
http://arxiv.org/abs/1902.06155v1
• [cs.LG]Designing recurrent neural networks by unfolding an l1-l1 minimization algorithm
Hung Duy Le, Huynh Van Luong, Nikos Deligiannis
http://arxiv.org/abs/1902.06522v1
• [cs.LG]Detecting and Diagnosing Incipient Building Faults Using Uncertainty Information from Deep Neural Networks
Baihong Jin, Dan Li, Seshadhri Srinivasan, See-Kiong Ng, Kameshwar Poolla, Alberto~Sangiovanni-Vincentelli
http://arxiv.org/abs/1902.06366v1
• [cs.LG]Fast Efficient Hyperparameter Tuning for Policy Gradients
Supratik Paul, Vitaly Kurin, Shimon Whiteson
http://arxiv.org/abs/1902.06583v1
• [cs.LG]Grids versus Graphs: Partitioning Space for Improved Taxi Demand-Supply Forecasts
Neema Davis, Gaurav Raina, Krishna Jagannathan
http://arxiv.org/abs/1902.06515v1
• [cs.LG]Incremental Cluster Validity Indices for Hard Partitions: Extensions and Comparative Study
Leonardo Enzo Brito da Silva, Niklas M. Melton, Donald C. Wunsch II
http://arxiv.org/abs/1902.06711v1
• [cs.LG]Intra- and Inter-epoch Temporal Context Network (IITNet) for Automatic Sleep Stage Scoring
Seunghyeok Back, Seongju Lee, Hogeon Seo, Deokhwan Park, Tae Kim, Kyoobin Lee
http://arxiv.org/abs/1902.06562v1
• [cs.LG]Learning Linear-Quadratic Regulators Efficiently with only Regret
Alon Cohen, Tomer Koren, Yishay Mansour
http://arxiv.org/abs/1902.06223v1
• [cs.LG]Making Convex Loss Functions Robust to Outliers using -Exponentiated Transformation
Suvadeep Hajra
http://arxiv.org/abs/1902.06127v1
• [cs.LG]Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning
Woojun Kim, Myungsik Cho, Youngchul Sung
http://arxiv.org/abs/1902.06527v1
• [cs.LG]ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems
Philippe Wenk, Gabriele Abbati, Stefan Bauer, Michael A Osborne, Andreas Krause, Bernhard Schölkopf
http://arxiv.org/abs/1902.06278v1
• [cs.LG]On Evaluating Adversarial Robustness
Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian Goodfellow, Aleksander Madry
http://arxiv.org/abs/1902.06705v1
• [cs.LG]On resampling vs. adjusting probabilistic graphical models in estimation of distribution algorithms
Mohamed El Yafrani, Marcella S. R. Martins, Myriam R. B. S. Delgado, Inkyung Sung, Ricardo Lüders, Markus Wagner
http://arxiv.org/abs/1902.05946v1
• [cs.LG]Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization
Hesham Mostafa, Xin Wang
http://arxiv.org/abs/1902.05967v1
• [cs.LG]Prediction of Porosity and Permeability Alteration based on Machine Learning Algorithms
Andrei Erofeev, Denis Orlov, Alexey Ryzhov, Dmitry Koroteev
http://arxiv.org/abs/1902.06525v1
• [cs.LG]ProLoNets: Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning
Andrew Silva, Matthew Gombolay
http://arxiv.org/abs/1902.06007v1
• [cs.LG]Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization
Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi
http://arxiv.org/abs/1902.06332v1
• [cs.LG]RES-SE-NET: Boosting Performance of Resnets by Enhancing Bridge-connections
Varshaneya V, Balasubramanian S, Darshan Gera
http://arxiv.org/abs/1902.06066v1
• [cs.LG]Robustness of Neural Networks: A Probabilistic and Practical Approach
Ravi Mangal, Aditya V. Nori, Alessandro Orso
http://arxiv.org/abs/1902.05983v1
• [cs.LG]STCN: Stochastic Temporal Convolutional Networks
Emre Aksan, Otmar Hilliges
http://arxiv.org/abs/1902.06568v1
• [cs.LG]Screening Rules for Lasso with Non-Convex Sparse Regularizers
Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon
http://arxiv.org/abs/1902.06125v1
• [cs.LG]Structural Recurrent Neural Network for Traffic Speed Prediction
Youngjoo Kim, Peng Wang, Lyudmila Mihaylova
http://arxiv.org/abs/1902.06506v1
• [cs.LG]WiSE-VAE: Wide Sample Estimator VAE
Shuyu Lin, Ronald Clark, Robert Birke, Niki Trigoni, Stephen Roberts
http://arxiv.org/abs/1902.06160v1
• [cs.LO]Appendix for: Cut-free Calculi and Relational Semantics for Temporal STIT logics
Kees van Berkel, Tim Lyon
http://arxiv.org/abs/1902.06632v1
• [cs.LO]Iterated Belief Base Revision: A Dynamic Epistemic Logic Approach
Marlo Souza, Álvaro Moreira, Renata Vieira
http://arxiv.org/abs/1902.06178v1
• [cs.NE]Differentiable reservoir computing
Lyudmila Grigoryeva, Juan-Pablo Ortega
http://arxiv.org/abs/1902.06094v1
• [cs.NE]Reactive, Proactive, and Inductive Agents: An evolutionary path for biological and artificial spiking networks
Lana Sinapayen, Atsushi Masumori, Ikegami Takashi
http://arxiv.org/abs/1902.06410v1
• [cs.RO]"Touching to See" and "Seeing to Feel": Robotic Cross-modal SensoryData Generation for Visual-Tactile Perception
Jet-Tsyn Lee, Danushka Bollegala, Shan Luo
http://arxiv.org/abs/1902.06273v1
• [cs.RO]A Fleet of Miniature Cars for Experiments in Cooperative Driving
Nicholas Hyldmar, Yijun He, Amanda Prorok
http://arxiv.org/abs/1902.06133v1
• [cs.RO]MetaGrasp: Data Efficient Grasping by Affordance Interpreter Network
Junhao Cai, Hui Cheng, Zhanpeng Zhang, Jingcheng Su
http://arxiv.org/abs/1902.06554v1
• [cs.RO]Real-Time Trajectory Planning for AGV in the Presence of Moving Obstacles: A First-Search-Then-Optimization Approach
Bai Li, Youmin Zhang, Fengqian Dou, Yi Liu
http://arxiv.org/abs/1902.06201v1
• [cs.SE]DeepFault: Fault Localization for Deep Neural Networks
Hasan Ferit Eniser, Simos Gerasimou, Alper Sen
http://arxiv.org/abs/1902.05974v1
• [cs.SI]A Broad Evaluation of the Tor English Content Ecosystem
Mahdieh Zabihimayvan, Reza Sadeghi, Derek Doran, Mehdi Allahyari
http://arxiv.org/abs/1902.06680v1
• [cs.SI]Can We Achieve Fresh Information with Selfish Users in Mobile Crowd-Learning?
Bin Li, Jia Liu
http://arxiv.org/abs/1902.06149v1
• [cs.SI]Learning Topological Representation for Networks via Hierarchical Sampling
Guoji Fu, Chengbin Hou, Xin Yao
http://arxiv.org/abs/1902.06684v1
• [cs.SI]Replications in quantitative and qualitative methods: a new era for commensurable digital social sciences
Dominique Boullier
http://arxiv.org/abs/1902.05984v1
• [cs.SI]The Ambivalence of Cultural Homophily: Field Positions, Semantic Similarities, and Social Network Ties in Creative Collectives
Nikita Basov, Centre for German, European Studies, St. Petersburg State University
http://arxiv.org/abs/1902.06597v1
• [eess.IV]Automated Detection of Regions of Interest for Brain Perfusion MR Images
Svitlana M Alkhimova
http://arxiv.org/abs/1902.06323v1
• [eess.SP]Spatial Channel Covariance Estimation for Hybrid Architectures Based on Tensor Decompositions
Sungwoo Park, Anum Ali, Nuria González-Prelcic, Robert W. Heath Jr
http://arxiv.org/abs/1902.06297v1
• [math.CO]Jacobi Sums and Correlations of Sidelnikov Sequences
Ayse Alaca, Goldwyn Millar
http://arxiv.org/abs/1902.06728v1
• [math.DG]On the geometric structure ofsome statistical manifolds
Mingao Yuan
http://arxiv.org/abs/1902.06144v1
• [math.OC]Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization
Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang
http://arxiv.org/abs/1902.06158v1
• [math.OC]The Kalai-Smorodinski solution for many-objective Bayesian optimization
Mickaël Binois, Victor Picheny, Patrick Taillandier, Abderrahmane Habbal
http://arxiv.org/abs/1902.06565v1
• [math.PR]Optimal Scaling and Shaping of Random Walk Metropolis via Diffusion Limits of Block-I.I.D. Targets
Jeffrey Negrea
http://arxiv.org/abs/1902.06603v1
• [math.ST]Aggregated test of independence based on HSIC measures
Anouar Meynaoui, Béatrice Laurent, Mélisande Albert, Amandine Marrel
http://arxiv.org/abs/1902.06441v1
• [math.ST]Intermediate efficiency of tests under heavy-tailed alternatives
Tadeusz Inglot
http://arxiv.org/abs/1902.06622v1
• [math.ST]Towards Explainable AI: Significance Tests for Neural Networks
Enguerrand Horel, Kay Giesecke
http://arxiv.org/abs/1902.06021v1
• [physics.soc-ph]Fundamental Diagram of Traffic Flow from Prigogine-Herman-Enskog Equation
W. Marques Jr., A. R. Mendez, R. M. Velasco
http://arxiv.org/abs/1902.06688v1
• [physics.soc-ph]Statistical properties of user activity fluctuations in virtual worlds
Yan-Hong Yang, Wen-Jie Xie, Ming-Xia Li, Zhi-Qiang Jiang, Wei-Xing Zhou
http://arxiv.org/abs/1902.06070v1
• [q-bio.NC]A computational model for grid maps in neural populations
Fabio Anselmi, Benedetta Franceschiello, Micah M. Murray, Lorenzo Rosasco
http://arxiv.org/abs/1902.06553v1
• [q-bio.NC]Power contours: optimising sample size and precision in experimental psychology and human neuroscience
Daniel H. Baker, Greta Vilidaite, Freya A. Lygo, Anika K. Smith, Tessa R. Flack, Andre D. Gouws, Timothy J. Andrews
http://arxiv.org/abs/1902.06122v1
• [stat.AP]A Bayesian binary algorithm for RMS-based acoustic signal segmentation
Paulo Hubert, Alexandra Chung, Linilson Padovese
http://arxiv.org/abs/1902.06315v1
• [stat.AP]A Statistical Analysis of Noisy Crowdsourced Weather Data
Arnab Chakraborty, Soumendra Nath Lahiri, Alyson Wilson
http://arxiv.org/abs/1902.06183v1
• [stat.AP]A feature-based framework for detecting technical outliers in water-quality data from in situ sensors
Priyanga Dilini Talagala, Rob J. Hyndman, Catherine Leigh, Kerrie Mengersen, Kate Smith-Miles
http://arxiv.org/abs/1902.06351v1
• [stat.AP]Detected changes in precipitation extremes at their native scales derived from in situ measurements
Mark D. Risser, Christopher J. Paciorek, Travis A. O'Brien, Michael F. Wehner, William D. Collins
http://arxiv.org/abs/1902.05977v1
• [stat.AP]Model fitting in Multiple Systems Analysis for the quantification of Modern Slavery: Classical and Bayesian approaches
Bernard W. Silverman
http://arxiv.org/abs/1902.06078v1
• [stat.AP]Monte Carlo Sampling Bias in the Microwave Uncertainty Framework
Michael Frey, Benjamin F. Jamroz, Amanda Koepke, Jacob D. Rezac, Dylan Williams
http://arxiv.org/abs/1902.05979v1
• [stat.AP]Optimized data exploration applied to the simulation of a chemical process
Raoul Heese, Michal Walczak, Tobias Seidel, Norbert Asprion, Michael Bortz
http://arxiv.org/abs/1902.06453v1
• [stat.CO]Is a single unique Bayesian network enough to accurately represent your data?
Gilles Kratzer, Reinhard Furrer
http://arxiv.org/abs/1902.06641v1
• [stat.CO]LISA: a MATLAB package for Longitudinal Image Sequence Analysis
Jang Ik Cho, Xiaofeng Wang, Yifan Xu, Jiayang Sun
http://arxiv.org/abs/1902.06131v1
• [stat.ME]Approximate Bayesian Model Inversion for PDEs with Heterogeneous and State-Dependent Coefficients
David A. Barajas-Solano, Alexandre M. Tartakovsky
http://arxiv.org/abs/1902.06718v1
• [stat.ME]Approximate leave-future-out cross-validation for time series models
Paul-Christian Bürkner, Jonah Gabry, Aki Vehtari
http://arxiv.org/abs/1902.06281v1
• [stat.ME]Assessing Biosimilarity using FunctionalMetrics
Lin Dong, Sujit K. Ghosh
http://arxiv.org/abs/1902.06036v1
• [stat.ME]Bayesian Methods for Multiple Mediators: Relating Principal Stratification and Causal Mediation in the Analysis of Power Plant Emission Controls
Chanmin Kim, Michael Daniels, Joseph Hogan, Christine Choirat, Corwin Zigler
http://arxiv.org/abs/1902.06194v1
• [stat.ME]Bayesian Regularization: From Tikhonov to Horseshoe
Nicholas G. Polson, Vadim Sokolov
http://arxiv.org/abs/1902.06269v1
• [stat.ME]Generalizing trial findings in nested trial designs with sub-sampling of non-randomized individuals
Issa J. Dahabreh, Miguel A. Hernan, Sarah E. Robertson, Ashley Buchanan, Jon A. Steingrimsson
http://arxiv.org/abs/1902.06080v1
• [stat.ME]Privacy Preserving Integrative Regression Analysis of High-dimensional Heterogeneous Data
Tianxi Cai, Molei Liu, Yin Xia
http://arxiv.org/abs/1902.06115v1
• [stat.ME]Projected Pólya Tree
Luis Nieto-Barajas, Gabriel Nuñez-Antonio
http://arxiv.org/abs/1902.06020v1
• [stat.ME]Separating common (global and local) and distinct variation in multiple mixed types data sets
Yipeng Song, Johan A. Westerhuis, Age K. Smilde
http://arxiv.org/abs/1902.06241v1
• [stat.ME]Sequentially additive nonignorable missing data modeling using auxiliary marginal information
Mauricio Sadinle, Jerome P. Reiter
http://arxiv.org/abs/1902.06043v1
• [stat.ME]Sparse Regression: Scalable algorithms and empirical performance
Dimitris Bertsimas, Jean Pauphilet, Bart Van Parys
http://arxiv.org/abs/1902.06547v1
• [stat.ME]What is an Ordinal Latent Trait Model?
Gerhard Tutz
http://arxiv.org/abs/1902.06303v1
• [stat.ML]A Unifying Bayesian View of Continual Learning
Sebastian Farquhar, Yarin Gal
http://arxiv.org/abs/1902.06494v1
• [stat.ML]Context-Based Dynamic Pricing with Online Clustering
Sentao Miao, Xi Chen, Xiuli Chao, Jiaxi Liu, Yidong Zhang
http://arxiv.org/abs/1902.06199v1
• [stat.ML]Differentially Private Continual Learning
Sebastian Farquhar, Yarin Gal
http://arxiv.org/abs/1902.06497v1
• [stat.ML]Going deep in clustering high-dimensional data: deep mixtures of unigrams for uncovering topics in textual data
Laura Anderlucci, Cinzia Viroli
http://arxiv.org/abs/1902.06615v1
• [stat.ML]Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit
Song Mei, Theodor Misiakiewicz, Andrea Montanari
http://arxiv.org/abs/1902.06015v1
• [stat.ML]Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
Jaehoon Lee, Lechao Xiao, Samuel S. Schoenholz, Yasaman Bahri, Jascha Sohl-Dickstein, Jeffrey Pennington
http://arxiv.org/abs/1902.06720v1
网友评论