astro-ph.IM - 仪器仪表和天体物理学方法
cond-mat.mtrl-sci - 材料科学
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.DS - 数据结构与算法
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.NE - 神经与进化计算
cs.NI - 网络和互联网体系结构
cs.PL - 编程语言
cs.RO - 机器人学
cs.SE - 软件工程
cs.SI - 社交网络与信息网络
cs.SY - 系统与控制
eess.AS - 语音处理
eess.IV - 图像与视频处理
eess.SP - 信号处理
math.MG -公制几何
math.NA - 数值分析
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.comp-ph - 计算物理学
physics.ed-ph - 物理教育
physics.geo-ph - 地球物理学
q-bio.QM - 定量方法
quant-ph - 量子物理
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
• [astro-ph.IM]Statistical Performance of Radio Interferometric Calibration
• [cond-mat.mtrl-sci]Atomistic structure learning
• [cs.AI]Coloring Big Graphs with AlphaGoZero
• [cs.AI]EL Embeddings: Geometric construction of models for the Description Logic EL ++
• [cs.AI]Learning Factored Markov Decision Processes with Unawareness
• [cs.AI]MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender Systems
• [cs.AI]On Constrained Open-World Probabilistic Databases
• [cs.AI]Reliable Deep Grade Prediction with Uncertainty Estimation
• [cs.AI]Technical report of "Empirical Study on Human Evaluation of Complex Argumentation Frameworks"
• [cs.AI]Understanding Agent Incentives using Causal Influence Diagrams. Part I: Single Action Settings
• [cs.AI]Unifying Ensemble Methods for Q-learning via Social Choice Theory
• [cs.AI]Unmasking Clever Hans Predictors and Assessing What Machines Really Learn
• [cs.CL]A Framework for Decoding Event-Related Potentials from Text
• [cs.CL]An Editorial Network for Enhanced Document Summarization
• [cs.CL]An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models
• [cs.CL]Analyzing the Perceived Severity of Cybersecurity Threats Reported on Social Media
• [cs.CL]Attention is not Explanation
• [cs.CL]BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers
• [cs.CL]Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressions
• [cs.CL]CN-Probase: A Data-driven Approach for Large-scale Chinese Taxonomy Construction
• [cs.CL]DiscoFuse: A Large-Scale Dataset for Discourse-based Sentence Fusion
• [cs.CL]Domain-Constrained Advertising Keyword Generation
• [cs.CL]F10-SGD: Fast Training of Elastic-net Linear Models for Text Classification and Named-entity Recognition
• [cs.CL]Few-Shot Text Classification with Induction Network
• [cs.CL]How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection
• [cs.CL]Learning to Generate Questions by Learning What not to Generate
• [cs.CL]Multilingual Neural Machine Translation with Knowledge Distillation
• [cs.CL]Multiresolution Graph Attention Networks for Relevance Matching
• [cs.CL]On the Idiosyncrasies of the Mandarin Chinese Classifier System
• [cs.CL]Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition
• [cs.CL]Syntactic Recurrent Neural Network for Authorship Attribution
• [cs.CL]Using Ternary Rewards to Reason over Knowledge Graphs with Deep Reinforcement Learning
• [cs.CL]Viable Dependency Parsing as Sequence Labeling
• [cs.CL]When a Tweet is Actually Sexist. A more Comprehensive Classification of Different Online Harassment Categories and The Challenges in NLP
• [cs.CL]Zoho at SemEval-2019 Task 9: Semi-supervised Domain Adaptation using Tri-training for Suggestion Mining
• [cs.CR]The Attack of the Clones against Proof-of-Authority
• [cs.CV]A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing
• [cs.CV]A Simple Prior-Free Method for Non-rigid Structure-from-Motion Factorization : Revisited
• [cs.CV]Attributes-aided Part Detection and Refinement for Person Re-identification
• [cs.CV]Aurora Guard: Real-Time Face Anti-Spoofing via Light Reflection
• [cs.CV]Cluster Regularized Quantization for Deep Networks Compression
• [cs.CV]Deep MR Fingerprinting with total-variation and low-rank subspace priors
• [cs.CV]Efficient Video Classification Using Fewer Frames
• [cs.CV]Equi-normalization of Neural Networks
• [cs.CV]FickleNet: Weakly and Semi-supervised Semantic Image Segmentation\using Stochastic Inference
• [cs.CV]Fix Your Features: Stationary and Maximally Discriminative Embeddings using Regular Polytope (Fixed Classifier) Networks
• [cs.CV]Flash Lightens Gray Pixels
• [cs.CV]Fractional spectral graph wavelets and their applications
• [cs.CV]Generative Collaborative Networks for Single Image Super-Resolution
• [cs.CV]Learning Latent Scene-Graph Representations for Referring Relationships
• [cs.CV]Modulated binary cliquenet
• [cs.CV]Multi-loss-aware Channel Pruning of Deep Networks
• [cs.CV]Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference
• [cs.CV]Single-frame Regularization for Temporally Stable CNNs
• [cs.CV]Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning
• [cs.CV]StyleRemix: An Interpretable Representation for Neural Image Style Transfer
• [cs.CV]The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning
• [cs.CV]Zero-shot Learning of 3D Point Cloud Objects
• [cs.CY]Exploiting Population Activity Dynamics to Predict Urban Epidemiological Incidence
• [cs.DC]A Graph Computation based Sequential Power Flow Calculation for Large-Scale ACDC Systems
• [cs.DC]A Survey on Graph Processing Accelerators: Challenges and Opportunities
• [cs.DC]Dispersion of Mobile Robots: The Power of Randomness
• [cs.DS]Reconciliation k-median: Clustering with Non-Polarized Representatives
• [cs.IR]Linear Time Visualization and Search in Big Data using Pixellated Factor Space Mapping
• [cs.IR]Query Scheduling in the Presence of Complex User Profiles
• [cs.IR]Query Term Weighting based on Query Performance Prediction
• [cs.IR]User-based collaborative filtering approach for content recommendation in OpenCourseWare platforms
• [cs.IT]A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems
• [cs.IT]Adaptive Caching via Deep Reinforcement Learning
• [cs.IT]Backscatter Data Collection with Unmanned Ground Vehicle: Mobility Management and Power Allocation
• [cs.IT]Compressive random access with multiple resource blocks and fast retrial
• [cs.IT]One and Two Bit Message Passing for SC-LDPC Codes with Higher-Order Modulation
• [cs.IT]Probabilistic Parity Shaping for Linear Codes
• [cs.IT]Quantized Polar Code Decoders: Analysis and Design
• [cs.IT]Skew-constacyclic codes over
• [cs.LG]A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems
• [cs.LG]ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
• [cs.LG]Accelerating Self-Play Learning in Go
• [cs.LG]Adaptive Hedging under Delayed Feedback
• [cs.LG]Alternating Synthetic and Real Gradients for Neural Language Modeling
• [cs.LG]Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification
• [cs.LG]Communication without Interception: Defense against Deep-Learning-based Modulation Detection
• [cs.LG]Continual Learning with Tiny Episodic Memories
• [cs.LG]Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning
• [cs.LG]Diagnosing Bottlenecks in Deep Q-learning Algorithms
• [cs.LG]Distributed Byzantine Tolerant Stochastic Gradient Descent in the Era of Big Data
• [cs.LG]Distributed Edge Caching via Reinforcement Learning in Fog Radio Access Networks
• [cs.LG]Epileptic seizure classification using statistical sampling and a novel feature selection algorithm
• [cs.LG]EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
• [cs.LG]Improving Missing Data Imputation with Deep Generative Models
• [cs.LG]Local Bandwidth Estimation via Mixture of Gaussian Processes
• [cs.LG]Logarithmic Regret for parameter-free Online Logistic Regression
• [cs.LG]Multi-task hypernetworks
• [cs.LG]Multiple Kernel Learning from -Statistics of Empirical Measures in the Feature Space
• [cs.LG]Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs
• [cs.LG]Nonlinear Approximation via Compositions
• [cs.LG]Online Learning with Continuous Ranked Probability Score
• [cs.LG]Ordinal Distance Metric Learning with MDS for Image Ranking
• [cs.LG]Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies
• [cs.LG]Polynomial-time Algorithms for Combinatorial Pure Exploration with Full-bandit Feedback
• [cs.LG]Provable Approximations for Constrained Regression
• [cs.LG]Provable Guarantees for Gradient-Based Meta-Learning
• [cs.LG]Quadratic Decomposable Submodular Function Minimization: Theory and Practice
• [cs.LG]Reducing Artificial Neural Network Complexity: A Case Study on Exoplanet Detection
• [cs.LG]Regularity Normalization: Constraining Implicit Space with Minimum Description Length
• [cs.LG]Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities
• [cs.LG]Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks
• [cs.LG]Robust Decision Trees Against Adversarial Examples
• [cs.LG]RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
• [cs.LG]Towards Efficient Data Valuation Based on the Shapley Value
• [cs.LG]TrIK-SVM : an alternative decomposition for kernel methods in Krein spaces
• [cs.NE]Counting to Ten with Two Fingers: Compressed Counting with Spiking Neurons
• [cs.NI]Neural Packet Classification
• [cs.PL]Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs
• [cs.RO]A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics
• [cs.RO]Achieving Non-Uniform Densities in Vibration Driven Robot Swarms Using Phase Separation Theory
• [cs.RO]Customizing Object Detectors for Indoor Robots
• [cs.RO]DeepLO: Geometry-Aware Deep LiDAR Odometry
• [cs.RO]Efficient Probabilistic Collision Detection for Non-Gaussian Noise Distributions
• [cs.RO]FastCal: Robust Online Self-Calibration for Robotic Systems
• [cs.RO]From explanation to synthesis: Compositional program induction for learning from demonstration
• [cs.RO]Improving drone localisation around wind turbines using monocular model-based tracking
• [cs.RO]Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU
• [cs.RO]Necessary and Sufficient Conditions for Passivity of Velocity-Sourced Impedance Control of Series Elastic Actuators
• [cs.RO]Obstacle-aware Adaptive Informative Path Planning for UAV-based Target Search
• [cs.RO]Road is Enough! Extrinsic Calibration of Non-overlapping Stereo Camera and LiDAR using Road Information
• [cs.RO]Whole-Body MPC for a Dynamically Stable Mobile Manipulator
• [cs.SE]Architecting Dependable Learning-enabled Autonomous Systems: A Survey
• [cs.SI]Deep Adversarial Network Alignment
• [cs.SI]Designing for Participation and Change in Digital Institutions
• [cs.SI]Leveraging Motifs to Model the Temporal Dynamics of Diffusion Networks
• [cs.SI]Prediction of the disease controllability in a complex network using machine learning algorithms
• [cs.SI]Social Credibility Incorporating Semantic Analysis and Machine Learning: A Survey of the State-of-the-Art and Future Research Directions
• [cs.SY]A Testbed for a Smart Building: Design and Implementation
• [cs.SY]Learning a Family of Optimal State Feedback Controllers
• [eess.AS]Directional Embedding Based Semi-supervised Framework For Bird Vocalization Segmentation
• [eess.IV]Deep Learning for Low-Dose CT Denoising
• [eess.IV]TensorMap: Lidar-Based Topological Mapping and Localization via Tensor Decompositions
• [eess.SP]A New Algorithm for Improved Blind Detection of Polar Coded PDCCH in 5G New Radio
• [math.MG]The optimal packing of eight points in the real projective plane
• [math.NA]Computing Nonlinear Eigenfunctions via Gradient Flow Extinction
• [math.NA]Learning to Optimize Multigrid PDE Solvers
• [math.OC]Clustering through the optimal transport barycenter problem
• [math.PR]Optimal Stopping of a Brownian Bridge with an Uncertain Pinning Time
• [math.ST]A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions
• [math.ST]A Good-Turing estimator for feature allocation models
• [math.ST]Adaptation for nonparametric estimators of locally stationary processes
• [math.ST]Brownian motion tree models are toric
• [math.ST]Consistent estimation of the missing mass for feature models
• [math.ST]Maximum Likelihood Estimation of Sparse Networks with Missing Observations
• [math.ST]On the well-posedness of Bayesian inverse problems
• [physics.comp-ph]Deep active subspaces -- a scalable method for high-dimensional uncertainty propagation
• [physics.ed-ph]Cloud service CoCalc as a means of forming the professional competencies of the mathematics teacher
• [physics.geo-ph]Can learning from natural image denoising be used for seismic data interpolation?
• [q-bio.QM]Continual Prediction from EHR Data for Inpatient Acute Kidney Injury
• [quant-ph]Efficient Learning for Deep Quantum Neural Networks
• [quant-ph]Energy efficient mining on a quantum-enabled blockchain using light
• [stat.AP]Evaluation of a length-based method to estimate discard rate and the effect of sampling size
• [stat.CO]Gait Change Detection Using Parameters Generated from Microsoft Kinect Coordinates
• [stat.ME]A permutation-based Bayesian approach for inverse covariance estimation
• [stat.ME]ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery
• [stat.ME]Bayesian Effect Selection in Structured Additive Distributional Regression Models
• [stat.ME]Bayesian data fusion for unmeasured confounding
• [stat.ME]Machine learning for subgroup discovery under treatment effect
• [stat.ME]Multivariate analysis of covariance when standard assumptions are violated
• [stat.ME]Nonnegative Bayesian nonparametric factor models with completely random measures for community detection
• [stat.ME]Profile and Globe Tests of Mean Surfaces for Two-Sample Bivariate Functional Data
• [stat.ME]Using prior expansions for prior-data conflict checking
• [stat.ML]Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation
• [stat.ML]Clustering by the local intrinsic dimension: the hidden structure of real-world data
• [stat.ML]Cross validation in sparse linear regression with piecewise continuous nonconvex penalties and its acceleration
• [stat.ML]High-Dimensional Bayesian Optimization with Manifold Gaussian Processes
• [stat.ML]Implicit Kernel Learning
• [stat.ML]On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives
• [stat.ML]Training Variational Autoencoders with Buffered Stochastic Variational Inference
• [stat.ML]Variational Inference to Measure Model Uncertainty in Deep Neural Networks
·····································
• [astro-ph.IM]Statistical Performance of Radio Interferometric Calibration
Sarod Yatawatta
http://arxiv.org/abs/1902.10448v1
• [cond-mat.mtrl-sci]Atomistic structure learning
Mathias S. Jørgensen, Henrik L. Mortensen, Søren A. Meldgaard, Esben L. Kolsbjerg, Thomas L. Jacobsen, Knud H. Sørensen, Bjørk Hammer
http://arxiv.org/abs/1902.10501v1
• [cs.AI]Coloring Big Graphs with AlphaGoZero
Jiayi Huang, Mostofa Patwary, Gregory Diamos
http://arxiv.org/abs/1902.10162v1
• [cs.AI]EL Embeddings: Geometric construction of models for the Description Logic EL ++
Maxat Kulmanov, Wang Liu-Wei, Yuan Yan, Robert Hoehndorf
http://arxiv.org/abs/1902.10499v1
• [cs.AI]Learning Factored Markov Decision Processes with Unawareness
Craig Innes, Alex Lascarides
http://arxiv.org/abs/1902.10619v1
• [cs.AI]MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender Systems
Mariana B. Santos, Amanda M. Lima, Lucas A. Silva, Felipe S. Vargas, Guilherme A. Wachs-Lopes, Paulo S. Rodrigues
http://arxiv.org/abs/1902.09291v2
• [cs.AI]On Constrained Open-World Probabilistic Databases
Tal Friedman, Guy Van den Broeck
http://arxiv.org/abs/1902.10677v1
• [cs.AI]Reliable Deep Grade Prediction with Uncertainty Estimation
Qian Hu, Huzefa Rangwala
http://arxiv.org/abs/1902.10213v1
• [cs.AI]Technical report of "Empirical Study on Human Evaluation of Complex Argumentation Frameworks"
Marcos Cramer, Mathieu Guillaume
http://arxiv.org/abs/1902.10552v1
• [cs.AI]Understanding Agent Incentives using Causal Influence Diagrams. Part I: Single Action Settings
Tom Everitt, Pedro A. Ortega, Elizabeth Barnes, Shane Legg
http://arxiv.org/abs/1902.09980v2
• [cs.AI]Unifying Ensemble Methods for Q-learning via Social Choice Theory
Rishav Chourasia, Adish Singla
http://arxiv.org/abs/1902.10646v1
• [cs.AI]Unmasking Clever Hans Predictors and Assessing What Machines Really Learn
Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
http://arxiv.org/abs/1902.10178v1
• [cs.CL]A Framework for Decoding Event-Related Potentials from Text
Shaorong Yan, Aaron Steven White
http://arxiv.org/abs/1902.10296v1
• [cs.CL]An Editorial Network for Enhanced Document Summarization
Edward Moroshko, Guy Feigenblat, Haggai Roitman, David Konopnicki
http://arxiv.org/abs/1902.10360v1
• [cs.CL]An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models
Alexandra Chronopoulou, Christos Baziotis, Alexandros Potamianos
http://arxiv.org/abs/1902.10547v1
• [cs.CL]Analyzing the Perceived Severity of Cybersecurity Threats Reported on Social Media
Shi Zong, Alan Ritter, Graham Mueller, Evan Wright
http://arxiv.org/abs/1902.10680v1
• [cs.CL]Attention is not Explanation
Sarthak Jain, Byron C. Wallace
http://arxiv.org/abs/1902.10186v1
• [cs.CL]BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers
Martin Fajcik, Lukáš Burget, Pavel Smrz
http://arxiv.org/abs/1902.10126v1
• [cs.CL]Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressions
Omid Rohanian, Shiva Taslimipoor, Samaneh Kouchaki, Le An Ha, Ruslan Mitkov
http://arxiv.org/abs/1902.10667v1
• [cs.CL]CN-Probase: A Data-driven Approach for Large-scale Chinese Taxonomy Construction
Jindong Chen, Ao Wang, Jiangjie Chen, Yanghua Xiao, Zhendong Chu, Jingping Liu, Jiaqing Liang, Wei Wang
http://arxiv.org/abs/1902.10326v1
• [cs.CL]DiscoFuse: A Large-Scale Dataset for Discourse-based Sentence Fusion
Mor Geva, Eric Malmi, Idan Szpektor, Jonathan Berant
http://arxiv.org/abs/1902.10526v1
• [cs.CL]Domain-Constrained Advertising Keyword Generation
Hao Zhou, Minlie Huang, Yishun Mao, Changlei Zhu, Peng Shu, Xiaoyan Zhu
http://arxiv.org/abs/1902.10374v1
• [cs.CL]F10-SGD: Fast Training of Elastic-net Linear Models for Text Classification and Named-entity Recognition
Stanislav Peshterliev, Alexander Hsieh, Imre Kiss
http://arxiv.org/abs/1902.10649v1
• [cs.CL]Few-Shot Text Classification with Induction Network
Ruiying Geng, Binhua Li, Yongbin Li, Yuxiao Ye, Ping Jian, Jian Sun
http://arxiv.org/abs/1902.10482v1
• [cs.CL]How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection
Wenhu Chen, Yu Su, Yilin Shen, Zhiyu Chen, Xifeng Yan, William Wang
http://arxiv.org/abs/1902.10339v1
• [cs.CL]Learning to Generate Questions by Learning What not to Generate
Bang Liu, Mingjun Zhao, Di Niu, Kunfeng Lai, Yancheng He, Haojie Wei, Yu Xu
http://arxiv.org/abs/1902.10418v1
• [cs.CL]Multilingual Neural Machine Translation with Knowledge Distillation
Xu Tan, Yi Ren, Di He, Tao Qin, Zhou Zhao, Tieyan Liu
http://arxiv.org/abs/1902.10461v1
• [cs.CL]Multiresolution Graph Attention Networks for Relevance Matching
Ting Zhang, Bang Liu, Di Niu, Kunfeng Lai, Yu Xu
http://arxiv.org/abs/1902.10580v1
• [cs.CL]On the Idiosyncrasies of the Mandarin Chinese Classifier System
Shijia Liu, Adina Williams, Hongyuan Mei, Ryan Cotterell
http://arxiv.org/abs/1902.10193v1
• [cs.CL]Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition
Vered Shwartz, Ido Dagan
http://arxiv.org/abs/1902.10618v1
• [cs.CL]Syntactic Recurrent Neural Network for Authorship Attribution
Fereshteh Jafariakinabad, Sansiri Tarnpradab, Kien A. Hua
http://arxiv.org/abs/1902.09723v2
• [cs.CL]Using Ternary Rewards to Reason over Knowledge Graphs with Deep Reinforcement Learning
Fréderic Godin, Anjishnu Kumar, Arpit Mittal
http://arxiv.org/abs/1902.10236v1
• [cs.CL]Viable Dependency Parsing as Sequence Labeling
Michalina Strzyz, David Vilares, Carlos Gómez-Rodríguez
http://arxiv.org/abs/1902.10505v1
• [cs.CL]When a Tweet is Actually Sexist. A more Comprehensive Classification of Different Online Harassment Categories and The Challenges in NLP
Sima Sharifirad, Stan Matwin
http://arxiv.org/abs/1902.10584v1
• [cs.CL]Zoho at SemEval-2019 Task 9: Semi-supervised Domain Adaptation using Tri-training for Suggestion Mining
Sai Prasanna, Sri Ananda Seelan
http://arxiv.org/abs/1902.10623v1
• [cs.CR]The Attack of the Clones against Proof-of-Authority
Parinya Ekparinya, Vincent Gramoli, Guillaume Jourjon
http://arxiv.org/abs/1902.10244v1
• [cs.CV]A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing
Sirisha Rambhatla, Xingguo Li, Jineng Ren, Jarvis Haupt
http://arxiv.org/abs/1902.10238v1
• [cs.CV]A Simple Prior-Free Method for Non-rigid Structure-from-Motion Factorization : Revisited
Suryansh Kumar
http://arxiv.org/abs/1902.10274v1
• [cs.CV]Attributes-aided Part Detection and Refinement for Person Re-identification
Shuzhao Li, Huimin Yu, Wei Huang, Jing Zhang
http://arxiv.org/abs/1902.10528v1
• [cs.CV]Aurora Guard: Real-Time Face Anti-Spoofing via Light Reflection
Yao Liu, Ying Tai, Jilin Li, Shouhong Ding, Chengjie Wang, Feiyue Huang, Dongyang Li, Wenshuai Qi, Rongrong Ji
http://arxiv.org/abs/1902.10311v1
• [cs.CV]Cluster Regularized Quantization for Deep Networks Compression
Yiming Hu, Jianquan Li, Xianlei Long, Shenhua Hu, Jiagang Zhu, Xingang Wang, Qingyi Gu
http://arxiv.org/abs/1902.10370v1
• [cs.CV]Deep MR Fingerprinting with total-variation and low-rank subspace priors
Mohammad Golbabaee, Carolin M. Pirkl, Marion I. Menzel, Guido Buonincontri, Pedro A. Gómez
http://arxiv.org/abs/1902.10205v1
• [cs.CV]Efficient Video Classification Using Fewer Frames
Shweta Bhardwaj, Mukundhan Srinivasan, Mitesh M. Khapra
http://arxiv.org/abs/1902.10640v1
• [cs.CV]Equi-normalization of Neural Networks
Pierre Stock, Benjamin Graham, Rémi Gribonval, Hervé Jégou
http://arxiv.org/abs/1902.10416v1
• [cs.CV]FickleNet: Weakly and Semi-supervised Semantic Image Segmentation\using Stochastic Inference
Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, Sungroh Yoon
http://arxiv.org/abs/1902.10421v1
• [cs.CV]Fix Your Features: Stationary and Maximally Discriminative Embeddings using Regular Polytope (Fixed Classifier) Networks
Federico Pernici, Matteo Bruni, Claudio Baecchi, Alberto Del Bimbo
http://arxiv.org/abs/1902.10441v1
• [cs.CV]Flash Lightens Gray Pixels
Yanlin Qian, Song Yan, Joni-Kristian Kämäräinen, Jiri Matas
http://arxiv.org/abs/1902.10466v1
• [cs.CV]Fractional spectral graph wavelets and their applications
Jiasong Wu, Fuzhi Wu, Qihan Yang, Youyong Kong, Xilin Liu, Yan Zhang, Lotfi Senhadji, Huazhong Shu
http://arxiv.org/abs/1902.10471v1
• [cs.CV]Generative Collaborative Networks for Single Image Super-Resolution
Mohamed El Amine Seddik, Mohamed Tamaazousti, John Lin
http://arxiv.org/abs/1902.10467v1
• [cs.CV]Learning Latent Scene-Graph Representations for Referring Relationships
Moshiko Raboh, Roei Herzig, Gal Chechik, Jonathan Berant, Amir Globerson
http://arxiv.org/abs/1902.10200v1
• [cs.CV]Modulated binary cliquenet
Jinpeng Xia, Jiasong Wu, Youyong Kong, Pinzheng Zhang, Lotfi Senhadji, Huazhong Shu
http://arxiv.org/abs/1902.10460v1
• [cs.CV]Multi-loss-aware Channel Pruning of Deep Networks
Yiming Hu, Siyang Sun, Jianquan Li, Jiagang Zhu, Xingang Wang, Qingyi Gu
http://arxiv.org/abs/1902.10364v1
• [cs.CV]Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference
Yao Yao, Zixin Luo, Shiwei Li, Tianwei Shen, Tian Fang, Long Quan
http://arxiv.org/abs/1902.10556v1
• [cs.CV]Single-frame Regularization for Temporally Stable CNNs
Gabriel Eilertsen, Rafał K. Mantiuk, Jonas Unger
http://arxiv.org/abs/1902.10424v1
• [cs.CV]Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning
Nayyer Aafaq, Naveed Akhtar, Wei Liu, Syed Zulqarnain Gilani, Ajmal Mian
http://arxiv.org/abs/1902.10322v1
• [cs.CV]StyleRemix: An Interpretable Representation for Neural Image Style Transfer
Hongmin Xu, Qiang Li, Wenbo Zhang, Wen Zheng
http://arxiv.org/abs/1902.10425v1
• [cs.CV]The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning
Benjamin J. Meyer, Tom Drummond
http://arxiv.org/abs/1902.10363v1
• [cs.CV]Zero-shot Learning of 3D Point Cloud Objects
Ali Cheraghian, Shafin Rahman, Lars Petersson
http://arxiv.org/abs/1902.10272v1
• [cs.CY]Exploiting Population Activity Dynamics to Predict Urban Epidemiological Incidence
Gergana Todorova, Anastasios Noulas
http://arxiv.org/abs/1902.10260v1
• [cs.DC]A Graph Computation based Sequential Power Flow Calculation for Large-Scale ACDC Systems
Wei Feng, Jingjin Wu, Chen Yuan, Guangyi Liu, Renchang Dai, Qingxin Shi, Fangxing Li
http://arxiv.org/abs/1902.10192v1
• [cs.DC]A Survey on Graph Processing Accelerators: Challenges and Opportunities
Chuangyi Gui, Long Zheng, Bingsheng He, Cheng Liu, Xinyu Chen, Xiaofei Liao, Hai Jin
http://arxiv.org/abs/1902.10130v1
• [cs.DC]Dispersion of Mobile Robots: The Power of Randomness
Anisur Rahaman Molla, William K. Moses Jr
http://arxiv.org/abs/1902.10489v1
• [cs.DS]Reconciliation k-median: Clustering with Non-Polarized Representatives
Bruno Ordozgoiti, Aristides Gionis
http://arxiv.org/abs/1902.10419v1
• [cs.IR]Linear Time Visualization and Search in Big Data using Pixellated Factor Space Mapping
Fionn Murtagh
http://arxiv.org/abs/1902.10655v1
• [cs.IR]Query Scheduling in the Presence of Complex User Profiles
Haggai Roitman, Avigdor Gal, Louiqa Raschid
http://arxiv.org/abs/1902.10384v1
• [cs.IR]Query Term Weighting based on Query Performance Prediction
Haggai Roitman
http://arxiv.org/abs/1902.10371v1
• [cs.IR]User-based collaborative filtering approach for content recommendation in OpenCourseWare platforms
Nikola Tomasevic, Dejan Paunovic, Sanja Vranes
http://arxiv.org/abs/1902.10376v1
• [cs.IT]A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems
Walid Saad, Mehdi Bennis, Mingzhe Chen
http://arxiv.org/abs/1902.10265v1
• [cs.IT]Adaptive Caching via Deep Reinforcement Learning
Alireza Sadeghi, Gang Wang, Georgios B. Giannakis
http://arxiv.org/abs/1902.10301v1
• [cs.IT]Backscatter Data Collection with Unmanned Ground Vehicle: Mobility Management and Power Allocation
Shuai Wang, Minghua Xia, Yik-Chung Wu
http://arxiv.org/abs/1902.10330v1
• [cs.IT]Compressive random access with multiple resource blocks and fast retrial
Jinho Choi
http://arxiv.org/abs/1902.10235v1
• [cs.IT]One and Two Bit Message Passing for SC-LDPC Codes with Higher-Order Modulation
Fabian Steiner, Emna Ben Yacoub, Balazs Matuz, Gianluigi Liva, Alexandre Graell i Amat
http://arxiv.org/abs/1902.10391v1
• [cs.IT]Probabilistic Parity Shaping for Linear Codes
Georg Böcherer, Diego Lentner, Alessandro Cirino, Fabian Steiner
http://arxiv.org/abs/1902.10648v1
• [cs.IT]Quantized Polar Code Decoders: Analysis and Design
Joachim Neu
http://arxiv.org/abs/1902.10395v1
• [cs.IT]Skew-constacyclic codes over
Joël Kabore, Alexandre Fotue-Tabue, Kenza Guenda, Mohammed E. Charkani
http://arxiv.org/abs/1902.10477v1
• [cs.LG]A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems
Rishabh Iyer, Jeff Bilmes
http://arxiv.org/abs/1902.10176v1
• [cs.LG]ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
Amir Gholami, Kurt Keutzer, George Biros
http://arxiv.org/abs/1902.10298v1
• [cs.LG]Accelerating Self-Play Learning in Go
David J. Wu
http://arxiv.org/abs/1902.10565v1
• [cs.LG]Adaptive Hedging under Delayed Feedback
Alexander Korotin, Vladimir V'yugin, Evgeny Burnaev
http://arxiv.org/abs/1902.10433v1
• [cs.LG]Alternating Synthetic and Real Gradients for Neural Language Modeling
Fangxin Shang, Hao Zhang
http://arxiv.org/abs/1902.10630v1
• [cs.LG]Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification
Pengfei Yang, Jiangchao Liu, Jianlin Li, Liqian Chen, Xiaowei Huang
http://arxiv.org/abs/1902.09866v1
• [cs.LG]Communication without Interception: Defense against Deep-Learning-based Modulation Detection
Muhammad Zaid Hameed, Andras Gyorgy, Deniz Gunduz
http://arxiv.org/abs/1902.10674v1
• [cs.LG]Continual Learning with Tiny Episodic Memories
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K. Dokania, Philip H. S. Torr, Marc'Aurelio Ranzato
http://arxiv.org/abs/1902.10486v1
• [cs.LG]Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning
Evgenii Tsymbalov, Sergei Makarychev, Alexander Shapeev, Maxim Panov
http://arxiv.org/abs/1902.10350v1
• [cs.LG]Diagnosing Bottlenecks in Deep Q-learning Algorithms
Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine
http://arxiv.org/abs/1902.10250v1
• [cs.LG]Distributed Byzantine Tolerant Stochastic Gradient Descent in the Era of Big Data
Richeng Jin, Xiaofan He, Huaiyu Dai
http://arxiv.org/abs/1902.10336v1
• [cs.LG]Distributed Edge Caching via Reinforcement Learning in Fog Radio Access Networks
Liuyang Lu, Yanxiang Jiang, Mehdi Bennis, Zhiguo Ding, Fu-Chun Zheng, Xiaohu You
http://arxiv.org/abs/1902.10574v1
• [cs.LG]Epileptic seizure classification using statistical sampling and a novel feature selection algorithm
Md Mursalin, Syed Shamsul Islam, Md Kislu Noman
http://arxiv.org/abs/1902.09962v1
• [cs.LG]EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Charles E. Leisersen
http://arxiv.org/abs/1902.10191v1
• [cs.LG]Improving Missing Data Imputation with Deep Generative Models
Ramiro D. Camino, Christian A. Hammerschmidt, Radu State
http://arxiv.org/abs/1902.10666v1
• [cs.LG]Local Bandwidth Estimation via Mixture of Gaussian Processes
Danny Panknin, Shinichi Nakajima, Thanh Binh Bui, Klaus-Robert Müller
http://arxiv.org/abs/1902.10664v1
• [cs.LG]Logarithmic Regret for parameter-free Online Logistic Regression
Joseph De Vilmarest, Olivier Wintenberger
http://arxiv.org/abs/1902.09803v1
• [cs.LG]Multi-task hypernetworks
Sylwester Klocek, Łukasz Maziarka, Maciej Wołczyk, Jacek Tabor, Marek Śmieja, Jakub Nowak
http://arxiv.org/abs/1902.10404v1
• [cs.LG]Multiple Kernel Learning from -Statistics of Empirical Measures in the Feature Space
Masoud Badiei Khuzani, Hongyi Ren, Varun Vasudevan, Lei Xing
http://arxiv.org/abs/1902.10365v1
• [cs.LG]Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs
Rishabh Iyer, Jeff Bilmes
http://arxiv.org/abs/1902.10172v1
• [cs.LG]Nonlinear Approximation via Compositions
Zuowei Shen, Haizhao Yang, Shijun Zhang
http://arxiv.org/abs/1902.10170v1
• [cs.LG]Online Learning with Continuous Ranked Probability Score
Vladimir V'yugin, Vladimir Trunov
http://arxiv.org/abs/1902.10173v1
• [cs.LG]Ordinal Distance Metric Learning with MDS for Image Ranking
Panpan Yu, Qingna Li
http://arxiv.org/abs/1902.10284v1
• [cs.LG]Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies
Tom Zahavy, Avinatan Hasidim, Haim Kaplan, Yishay Mansour
http://arxiv.org/abs/1902.10140v1
• [cs.LG]Polynomial-time Algorithms for Combinatorial Pure Exploration with Full-bandit Feedback
Yuko Kuroki, Liyuan Xu, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama
http://arxiv.org/abs/1902.10582v1
• [cs.LG]Provable Approximations for Constrained Regression
Ibrahim Jubran, David Cohn, Dan Feldman
http://arxiv.org/abs/1902.10407v1
• [cs.LG]Provable Guarantees for Gradient-Based Meta-Learning
Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar
http://arxiv.org/abs/1902.10644v1
• [cs.LG]Quadratic Decomposable Submodular Function Minimization: Theory and Practice
Pan Li, Niao He, Olgica Milenkovic
http://arxiv.org/abs/1902.10132v1
• [cs.LG]Reducing Artificial Neural Network Complexity: A Case Study on Exoplanet Detection
Sebastiaan Koning, Caspar Greeven, Eric Postma
http://arxiv.org/abs/1902.10385v1
• [cs.LG]Regularity Normalization: Constraining Implicit Space with Minimum Description Length
Baihan Lin
http://arxiv.org/abs/1902.10658v1
• [cs.LG]Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities
Geewook Kim, Akifumi Okuno, Kazuki Fukui, Hidetoshi Shimodaira
http://arxiv.org/abs/1902.10409v1
• [cs.LG]Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks
Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel
http://arxiv.org/abs/1902.10297v1
• [cs.LG]Robust Decision Trees Against Adversarial Examples
Hongge Chen, Huan Zhang, Duane Boning, Cho-Jui Hsieh
http://arxiv.org/abs/1902.10660v1
• [cs.LG]RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, Jian Tang
http://arxiv.org/abs/1902.10197v1
• [cs.LG]Towards Efficient Data Valuation Based on the Shapley Value
Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gurel, Bo Li, Ce Zhang, Dawn Song, Costas Spanos
http://arxiv.org/abs/1902.10275v1
• [cs.LG]TrIK-SVM : an alternative decomposition for kernel methods in Krein spaces
Gaëlle Loosli
http://arxiv.org/abs/1902.10569v1
• [cs.NE]Counting to Ten with Two Fingers: Compressed Counting with Spiking Neurons
Yael Hitron, Merav Parter
http://arxiv.org/abs/1902.10369v1
• [cs.NI]Neural Packet Classification
Eric Liang, Hang Zhu, Xin Jin, Ion Stoica
http://arxiv.org/abs/1902.10319v1
• [cs.PL]Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs
Tal Ben-Nun, Johannes de Fine Licht, Alexandros Nikolaos Ziogas, Timo Schneider, Torsten Hoefler
http://arxiv.org/abs/1902.10345v1
• [cs.RO]A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics
Shromona Ghosh, Somil Bansal, Alberto Sangiovanni-Vincentelli, Sanjit A. Seshia, Claire J. Tomlin
http://arxiv.org/abs/1902.10320v1
• [cs.RO]Achieving Non-Uniform Densities in Vibration Driven Robot Swarms Using Phase Separation Theory
Siddharth Mayya, Gennaro Notomista, Dylan Shell, Seth Hutchinson, Magnus Egerstedt
http://arxiv.org/abs/1902.10662v1
• [cs.RO]Customizing Object Detectors for Indoor Robots
Saif Alabachi, Gita Sukthankar, Rahul Sukthankar
http://arxiv.org/abs/1902.10671v1
• [cs.RO]DeepLO: Geometry-Aware Deep LiDAR Odometry
Younggun Cho, Giseop Kim, Ayoung Kim
http://arxiv.org/abs/1902.10562v1
• [cs.RO]Efficient Probabilistic Collision Detection for Non-Gaussian Noise Distributions
Jae Sung Park, Dinesh Manocha
http://arxiv.org/abs/1902.10252v1
• [cs.RO]FastCal: Robust Online Self-Calibration for Robotic Systems
Fernando Nobre, Christoffer Heckman
http://arxiv.org/abs/1902.10585v1
• [cs.RO]From explanation to synthesis: Compositional program induction for learning from demonstration
Michael Burke, Svetlin Penkov, Subramanian Ramamoorthy
http://arxiv.org/abs/1902.10657v1
• [cs.RO]Improving drone localisation around wind turbines using monocular model-based tracking
Oliver Moolan-Feroze, Konstantinos Karachalios, Dimitrios N. Nikolaidis, Andrew Calway
http://arxiv.org/abs/1902.10474v1
• [cs.RO]Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU
Georgi Tinchev, Adrian Penate-Sanchez, Maurice Fallon
http://arxiv.org/abs/1902.10194v1
• [cs.RO]Necessary and Sufficient Conditions for Passivity of Velocity-Sourced Impedance Control of Series Elastic Actuators
Fatih Emre Tosun, Volkan Patoglu
http://arxiv.org/abs/1902.10607v1
• [cs.RO]Obstacle-aware Adaptive Informative Path Planning for UAV-based Target Search
Ajith Anil Meera, Marija Popovic, Alexander Millane, Roland Siegwart
http://arxiv.org/abs/1902.10182v1
• [cs.RO]Road is Enough! Extrinsic Calibration of Non-overlapping Stereo Camera and LiDAR using Road Information
Jiyong Jeong, Lucas Y. Cho, Ayoung Kim
http://arxiv.org/abs/1902.10586v1
• [cs.RO]Whole-Body MPC for a Dynamically Stable Mobile Manipulator
Maria Vittoria Minniti, Farbod Farshidian, Ruben Grandia, Marco Hutter
http://arxiv.org/abs/1902.10415v1
• [cs.SE]Architecting Dependable Learning-enabled Autonomous Systems: A Survey
Chih-Hong Cheng, Dhiraj Gulati, Rongjie Yan
http://arxiv.org/abs/1902.10590v1
• [cs.SI]Deep Adversarial Network Alignment
Tyler Derr, Hamid Karimi, Xiaorui Liu, Jiejun Xu, Jiliang Tang
http://arxiv.org/abs/1902.10307v1
• [cs.SI]Designing for Participation and Change in Digital Institutions
Peter Krafft, Brian Keegan, Seth Frey
http://arxiv.org/abs/1902.08728v2
• [cs.SI]Leveraging Motifs to Model the Temporal Dynamics of Diffusion Networks
Soumajyoti Sarkar, Hamidreza Alvari, Paulo Shakarian
http://arxiv.org/abs/1902.10366v1
• [cs.SI]Prediction of the disease controllability in a complex network using machine learning algorithms
Richa Tripathi, Amit Reza, Dinesh Garg
http://arxiv.org/abs/1902.10224v1
• [cs.SI]Social Credibility Incorporating Semantic Analysis and Machine Learning: A Survey of the State-of-the-Art and Future Research Directions
Bilal Abu-Salih, Bushra Bremie, Pornpit Wongthongtham, Kevin Duan, Tomayess Issa, Kit Yan Chan, Mohammad Alhabashneh, Teshreen Albtoush, Sulaiman Alqahtani, Abdullah Alqahtani, Muteeb Alahmari, Naser Alshareef, Abdulaziz Albahlal
http://arxiv.org/abs/1902.10402v1
• [cs.SY]A Testbed for a Smart Building: Design and Implementation
Roja Eini, Lauren Linkous, Nasibeh Zohrabi, Sherif Abdelwahed
http://arxiv.org/abs/1902.10268v1
• [cs.SY]Learning a Family of Optimal State Feedback Controllers
Christopher Iliffe Sprague, Dario Izzo, Petter Ögren
http://arxiv.org/abs/1902.10139v1
• [eess.AS]Directional Embedding Based Semi-supervised Framework For Bird Vocalization Segmentation
Anshul Thakur, Padmanabhan Rajan
http://arxiv.org/abs/1902.09765v1
• [eess.IV]Deep Learning for Low-Dose CT Denoising
Maryam Gholizadeh-Ansari, Javad Alirezaie, Paul Babyn
http://arxiv.org/abs/1902.10127v1
• [eess.IV]TensorMap: Lidar-Based Topological Mapping and Localization via Tensor Decompositions
Sirisha Rambhatla, Nikos D. Sidiropoulos, Jarvis Haupt
http://arxiv.org/abs/1902.10226v1
• [eess.SP]A New Algorithm for Improved Blind Detection of Polar Coded PDCCH in 5G New Radio
Amin Jalali, Zhi Ding
http://arxiv.org/abs/1902.10280v1
• [math.MG]The optimal packing of eight points in the real projective plane
Dustin G. Mixon, Hans Parshall
http://arxiv.org/abs/1902.10177v1
• [math.NA]Computing Nonlinear Eigenfunctions via Gradient Flow Extinction
Leon Bungert, Martin Burger, Daniel Tenbrinck
http://arxiv.org/abs/1902.10414v1
• [math.NA]Learning to Optimize Multigrid PDE Solvers
Daniel Greenfeld, Meirav Galun, Ronen Basri, Irad Yavneh, Ron Kimmel
http://arxiv.org/abs/1902.10248v1
• [math.OC]Clustering through the optimal transport barycenter problem
Hongkang Yang, Esteban G. Tabak
http://arxiv.org/abs/1902.10288v1
• [math.PR]Optimal Stopping of a Brownian Bridge with an Uncertain Pinning Time
Kristoffer Glover
http://arxiv.org/abs/1902.10261v1
• [math.ST]A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions
Feras A. Saad, Cameron E. Freer, Nathanael L. Ackerman, Vikash K. Mansinghka
http://arxiv.org/abs/1902.10142v1
• [math.ST]A Good-Turing estimator for feature allocation models
Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro
http://arxiv.org/abs/1902.10490v1
• [math.ST]Adaptation for nonparametric estimators of locally stationary processes
Rainer Dahlhaus, Stefan Richter
http://arxiv.org/abs/1902.10381v1
• [math.ST]Brownian motion tree models are toric
Bernd Sturmfels, Caroline Uhler, Piotr Zwiernik
http://arxiv.org/abs/1902.09905v1
• [math.ST]Consistent estimation of the missing mass for feature models
Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro
http://arxiv.org/abs/1902.10530v1
• [math.ST]Maximum Likelihood Estimation of Sparse Networks with Missing Observations
Solenne Gaucher, Olga Klopp
http://arxiv.org/abs/1902.10605v1
• [math.ST]On the well-posedness of Bayesian inverse problems
Jonas Latz
http://arxiv.org/abs/1902.10257v1
• [physics.comp-ph]Deep active subspaces -- a scalable method for high-dimensional uncertainty propagation
Rohit Tripathy, Ilias Bilionis
http://arxiv.org/abs/1902.10527v1
• [physics.ed-ph]Cloud service CoCalc as a means of forming the professional competencies of the mathematics teacher
Maiia Popel
http://arxiv.org/abs/1902.10507v1
• [physics.geo-ph]Can learning from natural image denoising be used for seismic data interpolation?
Hao Zhang, Xiuyan Yang, Jianwei Ma
http://arxiv.org/abs/1902.10379v1
• [q-bio.QM]Continual Prediction from EHR Data for Inpatient Acute Kidney Injury
Rohit J. Kate, Noah Pearce, Debesh Mazumdar, Vani Nilakantan
http://arxiv.org/abs/1902.10228v1
• [quant-ph]Efficient Learning for Deep Quantum Neural Networks
Kerstin Beer, Dmytro Bondarenko, Terry Farrelly, Tobias J. Osborne, Robert Salzmann, Ramona Wolf
http://arxiv.org/abs/1902.10445v1
• [quant-ph]Energy efficient mining on a quantum-enabled blockchain using light
Adam J Bennet, Shakib Daryanoosh
http://arxiv.org/abs/1902.09520v2
• [stat.AP]Evaluation of a length-based method to estimate discard rate and the effect of sampling size
Erla Sturludottir, Gudjon Mar Sigurdsson, Gunnar Stefansson
http://arxiv.org/abs/1902.10579v1
• [stat.CO]Gait Change Detection Using Parameters Generated from Microsoft Kinect Coordinates
Behnam Malmir, Shing I Chang
http://arxiv.org/abs/1902.10283v1
• [stat.ME]A permutation-based Bayesian approach for inverse covariance estimation
Xuan Cao, Shaojun Zhang
http://arxiv.org/abs/1902.09353v2
• [stat.ME]ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery
Raj Agrawal, Chandler Squires, Karren Yang, Karthik Shanmugam, Caroline Uhler
http://arxiv.org/abs/1902.10347v1
• [stat.ME]Bayesian Effect Selection in Structured Additive Distributional Regression Models
Nadja Klein, Manuel Carlan, Thomas Kneib, Stefan Lang, Helga Wagner
http://arxiv.org/abs/1902.10446v1
• [stat.ME]Bayesian data fusion for unmeasured confounding
Leah Comment, Brent A. Coull, Corwin Zigler, Linda Valeri
http://arxiv.org/abs/1902.10613v1
• [stat.ME]Machine learning for subgroup discovery under treatment effect
Aleksey Buzmakov
http://arxiv.org/abs/1902.10327v1
• [stat.ME]Multivariate analysis of covariance when standard assumptions are violated
Georg Zimmermann, Markus Pauly, Arne C. Bathke
http://arxiv.org/abs/1902.10195v1
• [stat.ME]Nonnegative Bayesian nonparametric factor models with completely random measures for community detection
Fadhel Ayed, François Caron
http://arxiv.org/abs/1902.10693v1
• [stat.ME]Profile and Globe Tests of Mean Surfaces for Two-Sample Bivariate Functional Data
Jin Yang, Chunling Liu, Tao Zhang, Kam Chuen Yuen, Aiyi Liu
http://arxiv.org/abs/1902.10570v1
• [stat.ME]Using prior expansions for prior-data conflict checking
David J. Nott, Max Seah, Luai Al-Labadi, Michael Evans, Hui Khoon Ng, Berthold-Georg Englert
http://arxiv.org/abs/1902.10393v1
• [stat.ML]Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation
Antreas Antoniou, Amos Storkey
http://arxiv.org/abs/1902.09884v2
• [stat.ML]Clustering by the local intrinsic dimension: the hidden structure of real-world data
Michele Allegra, Elena Facco, Alessandro Laio, Antonietta Mira
http://arxiv.org/abs/1902.10459v1
• [stat.ML]Cross validation in sparse linear regression with piecewise continuous nonconvex penalties and its acceleration
Tomoyuki Obuchi, Ayaka Sakata
http://arxiv.org/abs/1902.10375v1
• [stat.ML]High-Dimensional Bayesian Optimization with Manifold Gaussian Processes
Riccardo Moriconi, K. S. Sesh Kumar, Marc P. Deisenroth
http://arxiv.org/abs/1902.10675v1
• [stat.ML]Implicit Kernel Learning
Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos
http://arxiv.org/abs/1902.10214v1
• [stat.ML]On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives
Alexander D'Amour
http://arxiv.org/abs/1902.10286v1
• [stat.ML]Training Variational Autoencoders with Buffered Stochastic Variational Inference
Rui Shu, Hung H. Bui, Jay Whang, Stefano Ermon
http://arxiv.org/abs/1902.10294v1
• [stat.ML]Variational Inference to Measure Model Uncertainty in Deep Neural Networks
Konstantin Posch, Jan Steinbrener, Jürgen Pilz
http://arxiv.org/abs/1902.10189v1
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