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今日学术视野(2019.3.1)

今日学术视野(2019.3.1)

作者: ZQtGe6 | 来源:发表于2019-03-01 05:01 被阅读161次

    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 \frac{\mathbb{F}_q[v]}{\langle\,v^q-v\,\rangle}
    • [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 U-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 \ell_p 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 \frac{\mathbb{F}_q[v]**}{\langle\,v^q-v\,\rangle}
    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 U-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 \ell_p 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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          本文标题:今日学术视野(2019.3.1)

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