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今日学术视野(2019.2.28)

今日学术视野(2019.2.28)

作者: ZQtGe6 | 来源:发表于2019-02-28 04:59 被阅读129次

    cond-mat.stat-mech - 统计数学
    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.DC - 分布式、并行与集群计算
    cs.GT - 计算机科学与博弈论
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.MM - 多媒体
    cs.NE - 神经与进化计算
    cs.NI - 网络和互联网体系结构
    cs.RO - 机器人学
    cs.SI - 社交网络与信息网络
    econ.EM - 计量经济学
    math.ST - 统计理论
    q-bio.QM - 定量方法
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cond-mat.stat-mech]Ternary Representation of Stochastic Change and the Origin of Entropy and Its Fluctuations
    • [cs.AI]Autonomous Identification and Goal-Directed Invocation of Event-Predictive Behavioral Primitives
    • [cs.AI]Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?
    • [cs.AI]Community-based 3-SAT Formulas with a Predefined Solution
    • [cs.AI]Conservative Agency via Attainable Utility Preservation
    • [cs.AI]Design of intentional backdoors in sequential models
    • [cs.AI]Information Gathering in Decentralized POMDPs by Policy Graph Improvement
    • [cs.AI]Intelligent Autonomous Things on the Battlefield
    • [cs.AI]The Termination Critic
    • [cs.AI]Transfer Learning for Performance Modeling of Configurable Systems: A Causal Analysis
    • [cs.AI]Understanding Agent Incentives using Causal Influence Diagrams, Part I: Single Action Settings
    • [cs.CL]A framework for information extraction from tables in biomedical literature
    • [cs.CL]Developing and Using Special-Purpose Lexicons for Cohort Selection from Clinical Notes
    • [cs.CL]Entity Recognition at First Sight: Improving NER with Eye Movement Information
    • [cs.CL]Image-Question-Answer Synergistic Network for Visual Dialog
    • [cs.CL]Improving a tf-idf weighted document vector embedding
    • [cs.CL]Multi-Task Learning with Contextualized Word Representations for Extented Named Entity Recognition
    • [cs.CL]On the Use of Emojis to Train Emotion Classifiers
    • [cs.CL]Polyglot Contextual Representations Improve Crosslingual Transfer
    • [cs.CL]Predicting the Type and Target of Offensive Posts in Social Media
    • [cs.CL]Recursive Subtree Composition in LSTM-Based Dependency Parsing
    • [cs.CL]Semantic Hilbert Space for Text Representation Learning
    • [cs.CL]Structure Tree-LSTM: Structure-aware Attentional Document Encoders
    • [cs.CL]Syntactic Recurrent Neural Network for Authorship Attribution
    • [cs.CL]Text Analysis in Adversarial Settings: Does Deception Leave a Stylistic Trace?
    • [cs.CR]An Access Control Model for Robot Calibration
    • [cs.CV]An Annotation Saved is an Annotation Earned: Using Fully Synthetic Training for Object Instance Detection
    • [cs.CV]Anomalous Situation Detection in Complex Scenes
    • [cs.CV]Associatively Segmenting Instances and Semantics in Point Clouds
    • [cs.CV]Bi-stream Pose Guided Region Ensemble Network for Fingertip Localization from Stereo Images
    • [cs.CV]BoostGAN for Occlusive Profile Face Frontalization and Recognition
    • [cs.CV]Capsule Neural Network based Height Classification using Low-Cost Automotive Ultrasonic Sensors
    • [cs.CV]Convolutional Neural Networks for Automatic Meter Reading
    • [cs.CV]Detecting Lesion Bounding Ellipses With Gaussian Proposal Networks
    • [cs.CV]Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Network
    • [cs.CV]Disentangled Representation Learning for 3D Face Shape
    • [cs.CV]Event-driven Video Frame Synthesis
    • [cs.CV]Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
    • [cs.CV]Generative Visual Dialogue System via Adaptive Reasoning and Weighted Likelihood Estimation
    • [cs.CV]Harmonic Unpaired Image-to-image Translation
    • [cs.CV]IF-TTN: Information Fused Temporal Transformation Network for Video Action Recognition
    • [cs.CV]LaSO: Label-Set Operations networks for multi-label few-shot learning
    • [cs.CV]Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR images
    • [cs.CV]Learning a Deep ConvNet for Multi-label Classification with Partial Labels
    • [cs.CV]MC-ISTA-Net: Adaptive Measurement and Initialization and Channel Attention Optimization inspired Neural Network for Compressive Sensing
    • [cs.CV]MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Video
    • [cs.CV]Making History Matter: Gold-Critic Sequence Training for Visual Dialog
    • [cs.CV]Mining Objects: Fully Unsupervised Object Discovery and Localization From a Single Image
    • [cs.CV]QLMC-HD: Quasi Large Margin Classifier based on Hyperdisk
    • [cs.CV]Realistic Ultrasonic Environment Simulation Using Conditional Generative Adversarial Networks
    • [cs.CV]Recurrent Convolution for Compact and Cost-Adjustable Neural Networks: An Empirical Study
    • [cs.CV]Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos
    • [cs.CV]RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation
    • [cs.CV]STAR-Net: Action Recognition using Spatio-Temporal Activation Reprojection
    • [cs.CV]SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation
    • [cs.CV]Self-Selective Correlation Ship Tracking Method for Smart Ocean System
    • [cs.CV]Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding
    • [cs.CV]Stereo R-CNN based 3D Object Detection for Autonomous Driving
    • [cs.CV]TCDCaps: Visual Tracking via Cascaded Dense Capsules
    • [cs.CV]Towards Corner Case Detection for Autonomous Driving
    • [cs.CV]TraVeLGAN: Image-to-image Translation by Transformation Vector Learning
    • [cs.CV]Unsupervised Part Mining for Fine-grained Image Classification
    • [cs.CV]Unsupervised learning-based long-term superpixel tracking
    • [cs.CV]Using Deep Object Features for Image Descriptions
    • [cs.CV]Utterance-level Aggregation For Speaker Recognition In The Wild
    • [cs.CV]Variational Multi-Phase Segmentation using High-Dimensional Local Features
    • [cs.DC]A Review on the Application of Blockchain for the Next Generation of Cybersecure Industry 4.0 Smart Factories
    • [cs.DC]Addressing Scalability with Message Queues: Architecture and Use Cases for DIRAC Interware
    • [cs.DC]An Automatic Speedup Theorem for Distributed Problems
    • [cs.DC]Byzantine Fault Tolerant Vector Consensus with Anonymous Proposals
    • [cs.DC]Fractal: Automated Application Scaling
    • [cs.DC]Population protocols with unreliable communication
    • [cs.DC]PubSub-SGX: Exploiting Trusted Execution Environments for Privacy-Preserving Publish/Subscribe Systems
    • [cs.DC]Rucio - Scientific Data Management
    • [cs.DC]Simulating Data Access Profiles of Computational Jobs in Data Grids
    • [cs.DC]clusterNOR: A NUMA-Optimized Clustering Framework
    • [cs.DC]cuSten -- CUDA Finite Difference and Stencil Library
    • [cs.GT]Selling a Single Item with Negative Externalities
    • [cs.HC]Analyzing the Use of Camera Glasses in the Wild
    • [cs.IR]Bootstrapping Domain-Specific Content Discovery on the Web
    • [cs.IR]Multi-Scale Quasi-RNN for Next Item Recommendation
    • [cs.IT]Achieving Secrecy Capacity of Minimum Storage Regenerating Codes for all Feasible (n, k, d) Parameter Values
    • [cs.IT]Communications and Radar Coexistence in the Massive MIMO Regime: Uplink Analysis
    • [cs.IT]Fast Decoder for Overloaded Uniquely Decodable Synchronous Optical CDMA
    • [cs.IT]Joint Communication and Motion Energy Minimization in UGV Backscatter Communication
    • [cs.IT]Joint Downlink Scheduling for File Placement and Delivery in Cache-Assisted Wireless Networks with Finite File Lifetime
    • [cs.IT]Joint Task Assignment and Resource Allocation for D2D-Enabled Mobile-Edge Computing
    • [cs.IT]Performance of Non-orthogonal Multiple Access under Finite Blocklength
    • [cs.IT]Robust Resource Allocation for PD-NOMA-Based MISO Heterogeneous Networks with CoMP Technology
    • [cs.IT]Statistical Learning Aided Decoding of BMST of Tail-Biting Convolutional Code
    • [cs.IT]Towards Higher Spectral Efficiency: Spatial Path Index Modulation Improves Millimeter-Wave Hybrid Beamforming
    • [cs.IT]Uniquely Decodable Ternary Codes for Synchronous CDMA Systems
    • [cs.IT]Vector Gaussian CEO Problem Under Logarithmic Loss
    • [cs.LG]A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
    • [cs.LG]A Feature Selection Based on Perturbation Theory
    • [cs.LG]Adaptive Gradient Methods with Dynamic Bound of Learning Rate
    • [cs.LG]Anomaly Detection for an E-commerce Pricing System
    • [cs.LG]Approximate Dynamic Programming with Neural Networks in Linear Discrete Action Spaces
    • [cs.LG]Automated Model Selection with Bayesian Quadrature
    • [cs.LG]Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control
    • [cs.LG]Fully Distributed Bayesian Optimization with Stochastic Policies
    • [cs.LG]Functional Transparency for Structured Data: a Game-Theoretic Approach
    • [cs.LG]Fused Lasso for Feature Selection using Structural Information
    • [cs.LG]GAN-based Projector for Faster Recovery in Compressed Sensing with Convergence Guarantees
    • [cs.LG]GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks
    • [cs.LG]Graph Neural Processes: Towards Bayesian Graph Neural Networks
    • [cs.LG]HexaGAN: Generative Adversarial Nets for Real World Classification
    • [cs.LG]Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets
    • [cs.LG]Interaction-aware Factorization Machines for Recommender Systems
    • [cs.LG]Interpreting Active Learning Methods Through Information Losses
    • [cs.LG]Learning Implicitly Recurrent CNNs Through Parameter Sharing
    • [cs.LG]Learning Vertex Convolutional Networks for Graph Classification
    • [cs.LG]Learning to Find Hard Instances of Graph Problems
    • [cs.LG]MisGAN: Learning from Incomplete Data with Generative Adversarial Networks
    • [cs.LG]NAS-Bench-101: Towards Reproducible Neural Architecture Search
    • [cs.LG]Perturbed-History Exploration in Stochastic Multi-Armed Bandits
    • [cs.LG]Robust and Subject-Independent Driving Manoeuvre Anticipation through Domain-Adversarial Recurrent Neural Networks
    • [cs.LG]Short-term Road Traffic Prediction based on Deep Cluster at Large-scale Networks
    • [cs.LG]Stochastic Prediction of Multi-Agent Interactions from Partial Observations
    • [cs.LG]The State of Sparsity in Deep Neural Networks
    • [cs.LG]Topological Bayesian Optimization with Persistence Diagrams
    • [cs.LG]Verification of Non-Linear Specifications for Neural Networks
    • [cs.MM]A multimodal movie review corpus for fine-grained opinion mining
    • [cs.NE]Band-to-Band Tunneling based Ultra-Energy Efficient Silicon Neuron
    • [cs.NE]Spiking Neural Network based Region Proposal Networks for Neuromorphic Vision Sensors
    • [cs.NE]The importance of space and time in neuromorphic cognitive agents
    • [cs.NI]Optimal and Fast Real-time Resources Slicing with Deep Dueling Neural Networks
    • [cs.RO]A Multi-Domain Feature Learning Method for Visual Place Recognition
    • [cs.RO]Acting Is Seeing: Navigating Tight Space Using Flapping Wings
    • [cs.RO]Beyond the Self: Using Grounded Affordances to Interpret and Describe Others' Actions
    • [cs.RO]Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals
    • [cs.RO]Informative Path Planning and Mapping for Active Sensing Under Localization Uncertainty
    • [cs.RO]Learning Extreme Hummingbird Maneuvers on Flapping Wing Robots
    • [cs.RO]MRS-VPR: a multi-resolution sampling based global visual place recognition method
    • [cs.RO]Semantic Relational Object Tracking
    • [cs.RO]Sequential Learning of Visual Tracking and Mapping Using Unsupervised Deep Neural Networks
    • [cs.RO]Simultaneous Detection of Loop-Closures and Changed Objects
    • [cs.SI]Community structure in co-inventor networks affects time to first citation for patents
    • [econ.EM]On Binscatter
    • [econ.EM]Semiparametric estimation of heterogeneous treatment effects under the nonignorable assignment condition
    • [math.ST]A Dynamic Model for Double Bounded Time Series With Chaotic Driven Conditional Averages
    • [math.ST]Effect Inference from Two-Group Data with Sampling Bias
    • [math.ST]Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions
    • [math.ST]Sample Splitting and Weak Assumption Inference For Time Series
    • [q-bio.QM]A Fully-Automatic Framework for Parkinson's Disease Diagnosis by Multi-Modality Images
    • [stat.AP]A Nested K-Nearest Prognostic Approach for Microwave Precipitation Phase Detection over Snow Cover
    • [stat.AP]A Source-Oriented Approach to Coal Power Plant Emissions Health Effects
    • [stat.AP]Estimating Atmospheric Motion Winds from Satellite Image Data using Space-time Drift Models
    • [stat.AP]Protocol for an Observational Study of the Association of High School Football Participation on Health in Late Adulthood
    • [stat.ME]Doubly stochastic distributions of extreme events
    • [stat.ME]Multiscale quantile regression
    • [stat.ME]Parameter Redundancy and the Existence of Maximum Likelihood Estimates in Log-linear Models
    • [stat.ML]AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
    • [stat.ML]Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation
    • [stat.ML]Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era
    • [stat.ML]Context Vectors are Reflections of Word Vectors in Half the Dimensions
    • [stat.ML]Efficient online learning with kernels for adversarial large scale problems
    • [stat.ML]Function Space Particle Optimization for Bayesian Neural Networks
    • [stat.ML]Multiscale Gaussian Process Level Set Estimation
    • [stat.ML]Online Framework for Demand-Responsive Stochastic Route Optimization
    • [stat.ML]Optimal Clustering with Missing Values

    ·····································

    • [cond-mat.stat-mech]Ternary Representation of Stochastic Change and the Origin of Entropy and Its Fluctuations
    Hong Qian, Yu-Chen Cheng, Lowell F. Thompson
    http://arxiv.org/abs/1902.09536v1

    • [cs.AI]Autonomous Identification and Goal-Directed Invocation of Event-Predictive Behavioral Primitives
    Christian Gumbsch, Martin V. Butz, Georg Martius
    http://arxiv.org/abs/1902.09948v1

    • [cs.AI]Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?
    Céline Hocquette, Stephen H. Muggleton
    http://arxiv.org/abs/1902.09835v1

    • [cs.AI]Community-based 3-SAT Formulas with a Predefined Solution
    Yamin Hu, Wenjian Luo, Junteng Wang
    http://arxiv.org/abs/1902.09706v1

    • [cs.AI]Conservative Agency via Attainable Utility Preservation
    Alexander Matt Turner, Dylan Hadfield-Menell, Prasad Tadepalli
    http://arxiv.org/abs/1902.09725v1

    • [cs.AI]Design of intentional backdoors in sequential models
    Zhaoyuan Yang, Naresh Iyer, Johan Reimann, Nurali Virani
    http://arxiv.org/abs/1902.09972v1

    • [cs.AI]Information Gathering in Decentralized POMDPs by Policy Graph Improvement
    Mikko Lauri, Joni Pajarinen, Jan Peters
    http://arxiv.org/abs/1902.09840v1

    • [cs.AI]Intelligent Autonomous Things on the Battlefield
    Alexander Kott, Ethan Stump
    http://arxiv.org/abs/1902.10086v1

    • [cs.AI]The Termination Critic
    Anna Harutyunyan, Will Dabney, Diana Borsa, Nicolas Heess, Remi Munos, Doina Precup
    http://arxiv.org/abs/1902.09996v1

    • [cs.AI]Transfer Learning for Performance Modeling of Configurable Systems: A Causal Analysis
    Mohammad Ali Javidian, Pooyan Jamshidi, Marco Valtorta
    http://arxiv.org/abs/1902.10119v1

    • [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/1902.09980v1

    • [cs.CL]A framework for information extraction from tables in biomedical literature
    Nikola Milosevic, Cassie Gregson, Robert Hernandez, Goran Nenadic
    http://arxiv.org/abs/1902.10031v1

    • [cs.CL]Developing and Using Special-Purpose Lexicons for Cohort Selection from Clinical Notes
    Samarth Rawal, Ashok Prakash, Soumya Adhya, Sidharth Kulkarni, Saadat Anwar, Chitta Baral, Murthy Devarakonda
    http://arxiv.org/abs/1902.09674v1

    • [cs.CL]Entity Recognition at First Sight: Improving NER with Eye Movement Information
    Nora Hollenstein, Ce Zhang
    http://arxiv.org/abs/1902.10068v1

    • [cs.CL]Image-Question-Answer Synergistic Network for Visual Dialog
    Dalu Guo, Chang Xu, Dacheng Tao
    http://arxiv.org/abs/1902.09774v1

    • [cs.CL]Improving a tf-idf weighted document vector embedding
    Craig W. Schmidt
    http://arxiv.org/abs/1902.09875v1

    • [cs.CL]Multi-Task Learning with Contextualized Word Representations for Extented Named Entity Recognition
    Thai-Hoang Pham, Khai Mai, Nguyen Minh Trung, Nguyen Tuan Duc, Danushka Bolegala, Ryohei Sasano, Satoshi Sekine
    http://arxiv.org/abs/1902.10118v1

    • [cs.CL]On the Use of Emojis to Train Emotion Classifiers
    Wegdan Hussien, Mahmoud Al-Ayyoub, Yahya Tashtoush, Mohammed Al-Kabi
    http://arxiv.org/abs/1902.08906v2

    • [cs.CL]Polyglot Contextual Representations Improve Crosslingual Transfer
    Phoebe Mulcaire, Jungo Kasai, Noah Smith
    http://arxiv.org/abs/1902.09697v1

    • [cs.CL]Predicting the Type and Target of Offensive Posts in Social Media
    Marcos Zampieri, Shervin Malmasi, Preslav Nakov, Sara Rosenthal, Noura Farra, Ritesh Kumar
    http://arxiv.org/abs/1902.09666v1

    • [cs.CL]Recursive Subtree Composition in LSTM-Based Dependency Parsing
    Miryam de Lhoneux, Miguel Ballesteros, Joakim Nivre
    http://arxiv.org/abs/1902.09781v1

    • [cs.CL]Semantic Hilbert Space for Text Representation Learning
    Benyou Wang, Qiuchi Li, Massimo Melucci, Dawei Song
    http://arxiv.org/abs/1902.09802v1

    • [cs.CL]Structure Tree-LSTM: Structure-aware Attentional Document Encoders
    Khalil Mrini, Claudiu Musat, Michael Baeriswyl, Martin Jaggi
    http://arxiv.org/abs/1902.09713v1

    • [cs.CL]Syntactic Recurrent Neural Network for Authorship Attribution
    Fereshteh Jafariakinabad, Sansiri Tarnpradab, Kien A. Hua
    http://arxiv.org/abs/1902.09723v1

    • [cs.CL]Text Analysis in Adversarial Settings: Does Deception Leave a Stylistic Trace?
    Tommi Gröndahl, N. Asokan
    http://arxiv.org/abs/1902.08939v2

    • [cs.CR]An Access Control Model for Robot Calibration
    Ryan Shah, Shishir Nagaraja
    http://arxiv.org/abs/1902.09587v1

    • [cs.CV]An Annotation Saved is an Annotation Earned: Using Fully Synthetic Training for Object Instance Detection
    Stefan Hinterstoisser, Olivier Pauly, Hauke Heibel, Martina Marek, Martin Bokeloh
    http://arxiv.org/abs/1902.09967v1

    • [cs.CV]Anomalous Situation Detection in Complex Scenes
    Michalis Voutouris, Giovanni Sachi, Hina Afridi
    http://arxiv.org/abs/1902.10016v1

    • [cs.CV]Associatively Segmenting Instances and Semantics in Point Clouds
    Xinlong Wang, Shu Liu, Xiaoyong Shen, Chunhua Shen, Jiaya Jia
    http://arxiv.org/abs/1902.09852v1

    • [cs.CV]Bi-stream Pose Guided Region Ensemble Network for Fingertip Localization from Stereo Images
    Guijin Wang, Cairong Zhang, Xinghao Chen, Xiangyang Ji, Jing-Hao Xue, Hang Wang
    http://arxiv.org/abs/1902.09795v1

    • [cs.CV]BoostGAN for Occlusive Profile Face Frontalization and Recognition
    Qingyan Duan, Lei Zhang
    http://arxiv.org/abs/1902.09782v1

    • [cs.CV]Capsule Neural Network based Height Classification using Low-Cost Automotive Ultrasonic Sensors
    Maximilian Pöpperl, Raghavendra Gulagundi, Senthil Yogamani, Stefan Milz
    http://arxiv.org/abs/1902.09839v1

    • [cs.CV]Convolutional Neural Networks for Automatic Meter Reading
    Rayson Laroca, Victor Barroso, Matheus A. Diniz, Gabriel R. Gonçalves, William Robson Schwartz, David Menotti
    http://arxiv.org/abs/1902.09600v1

    • [cs.CV]Detecting Lesion Bounding Ellipses With Gaussian Proposal Networks
    Yi Li
    http://arxiv.org/abs/1902.09658v1

    • [cs.CV]Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Network
    Yechong Huang, Jiahang Xu, Yuncheng Zhou, Tong Tong, Xiahai Zhuang, the Alzheimer's Disease Neuroimaging Initiative
    http://arxiv.org/abs/1902.09904v1

    • [cs.CV]Disentangled Representation Learning for 3D Face Shape
    Zi-Hang Jiang, Qianyi Wu, Keyu Chen, Juyong Zhang
    http://arxiv.org/abs/1902.09887v1

    • [cs.CV]Event-driven Video Frame Synthesis
    Zihao Wang, Weixin Jiang, Aggelos Katsaggelos, Oliver Cossairt
    http://arxiv.org/abs/1902.09680v1

    • [cs.CV]Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
    Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak, Amir Sadeghian, Ian Reid, Silvio Savarese
    http://arxiv.org/abs/1902.09630v1

    • [cs.CV]Generative Visual Dialogue System via Adaptive Reasoning and Weighted Likelihood Estimation
    Heming Zhang, Shalini Ghosh, Larry Heck, Stephen Walsh, Junting Zhang, Jie Zhang, C. -C. Jay Kuo
    http://arxiv.org/abs/1902.09818v1

    • [cs.CV]Harmonic Unpaired Image-to-image Translation
    Rui Zhang, Tomas Pfister, Jia Li
    http://arxiv.org/abs/1902.09727v1

    • [cs.CV]IF-TTN: Information Fused Temporal Transformation Network for Video Action Recognition
    Ke Yang, Jingjing Fu, Xun Guo, Yan Lu, Peng Qiao, Dongsheng Li, Yong Dou
    http://arxiv.org/abs/1902.09928v1

    • [cs.CV]LaSO: Label-Set Operations networks for multi-label few-shot learning
    Amit Alfassy, Leonid Karlinsky, Amit Aides, Joseph Shtok, Sivan Harary, Rogerio Feris, Raja Giryes, Alex M. Bronstein
    http://arxiv.org/abs/1902.09811v1

    • [cs.CV]Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR images
    Changhee Han, Kohei Murao, Tomoyuki Noguchi, Yusuke Kawata, Fumiya Uchiyama, Leonardo Rundo, Hideki Nakayama, Shin'ichi Satoh
    http://arxiv.org/abs/1902.09856v1

    • [cs.CV]Learning a Deep ConvNet for Multi-label Classification with Partial Labels
    Thibaut Durand, Nazanin Mehrasa, Greg Mori
    http://arxiv.org/abs/1902.09720v1

    • [cs.CV]MC-ISTA-Net: Adaptive Measurement and Initialization and Channel Attention Optimization inspired Neural Network for Compressive Sensing
    Nanyu Li, Cuiyin Liu, Wei Dai
    http://arxiv.org/abs/1902.09878v1

    • [cs.CV]MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Video
    Zhenyu Guan, Qunliang Xing, Mai Xu, Ren Yang, Tie Liu, Zulin Wang
    http://arxiv.org/abs/1902.09707v1

    • [cs.CV]Making History Matter: Gold-Critic Sequence Training for Visual Dialog
    Tianhao Yang, Zheng-Jun Zha, Hanwang Zhang
    http://arxiv.org/abs/1902.09326v2

    • [cs.CV]Mining Objects: Fully Unsupervised Object Discovery and Localization From a Single Image
    Runsheng Zhang, Yaping Huang, Mengyang Pu, Qingji Guan, Jian Zhang, Qi Zou
    http://arxiv.org/abs/1902.09968v1

    • [cs.CV]QLMC-HD: Quasi Large Margin Classifier based on Hyperdisk
    Hassan Ataeian, Shahriar Esmaeili, Ali Amiri, Neda Maleki Khas, Hossein Safari
    http://arxiv.org/abs/1902.09692v1

    • [cs.CV]Realistic Ultrasonic Environment Simulation Using Conditional Generative Adversarial Networks
    Maximilian Pöpperl, Raghavendra Gulagundi, Senthil Yogamani, Stefan Milz
    http://arxiv.org/abs/1902.09842v1

    • [cs.CV]Recurrent Convolution for Compact and Cost-Adjustable Neural Networks: An Empirical Study
    Zhendong Zhang, Cheolkon Jung
    http://arxiv.org/abs/1902.09809v1

    • [cs.CV]Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos
    Haofei Xu, Jianmin Zheng, Jianfei Cai, Juyong Zhang
    http://arxiv.org/abs/1902.09907v1

    • [cs.CV]RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation
    Bastian Wandt, Bodo Rosenhahn
    http://arxiv.org/abs/1902.09868v1

    • [cs.CV]STAR-Net: Action Recognition using Spatio-Temporal Activation Reprojection
    William McNally, Alexander Wong, John McPhee
    http://arxiv.org/abs/1902.10024v1

    • [cs.CV]SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation
    René Schuster, Oliver Wasenmüller, Christian Unger, Georg Kuschk, Didier Stricker
    http://arxiv.org/abs/1902.10099v1

    • [cs.CV]Self-Selective Correlation Ship Tracking Method for Smart Ocean System
    Xu Kang, Bin Song, Jie Guo, Xiaojiang Du, Mohsen Guizani
    http://arxiv.org/abs/1902.09690v1

    • [cs.CV]Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding
    Zehao Yu, Jia Zheng, Dongze Lian, Zihan Zhou, Shenghua Gao
    http://arxiv.org/abs/1902.09777v1

    • [cs.CV]Stereo R-CNN based 3D Object Detection for Autonomous Driving
    Peiliang Li, Xiaozhi Chen, Shaojie Shen
    http://arxiv.org/abs/1902.09738v1

    • [cs.CV]TCDCaps: Visual Tracking via Cascaded Dense Capsules
    Ding Ma, Xiangqian Wu
    http://arxiv.org/abs/1902.10054v1

    • [cs.CV]Towards Corner Case Detection for Autonomous Driving
    Jan-Aike Bolte, Andreas Bär, Daniel Lipinski, Tim Fingscheidt
    http://arxiv.org/abs/1902.09184v2

    • [cs.CV]TraVeLGAN: Image-to-image Translation by Transformation Vector Learning
    Matthew Amodio, Smita Krishnaswamy
    http://arxiv.org/abs/1902.09631v1

    • [cs.CV]Unsupervised Part Mining for Fine-grained Image Classification
    Jian Zhang, Runsheng Zhang, Yaping Huang, Qi Zou
    http://arxiv.org/abs/1902.09941v1

    • [cs.CV]Unsupervised learning-based long-term superpixel tracking
    Pierre-Henri Conze, Florian Tilquin, Mathieu Lamard, Fabrice Heitz, Gwenolé Quellec
    http://arxiv.org/abs/1902.09596v1

    • [cs.CV]Using Deep Object Features for Image Descriptions
    Ashutosh Mishra, Marcus Liwicki
    http://arxiv.org/abs/1902.09969v1

    • [cs.CV]Utterance-level Aggregation For Speaker Recognition In The Wild
    Weidi Xie, Arsha Nagrani, Joon Son Chung, Andrew Zisserman
    http://arxiv.org/abs/1902.10107v1

    • [cs.CV]Variational Multi-Phase Segmentation using High-Dimensional Local Features
    Niklas Mevenkamp, Benjamin Berkels
    http://arxiv.org/abs/1902.09863v1

    • [cs.DC]A Review on the Application of Blockchain for the Next Generation of Cybersecure Industry 4.0 Smart Factories
    Tiago M. Fernández-Caramés, Paula Fraga-Lamas
    http://arxiv.org/abs/1902.09604v1

    • [cs.DC]Addressing Scalability with Message Queues: Architecture and Use Cases for DIRAC Interware
    Wojciech Krzemien, Federico Stagni, Christophe Haen, Zoltan Mathe, Andrew McNab, Milosz Zdybal
    http://arxiv.org/abs/1902.09645v1

    • [cs.DC]An Automatic Speedup Theorem for Distributed Problems
    Sebastian Brandt
    http://arxiv.org/abs/1902.09958v1

    • [cs.DC]Byzantine Fault Tolerant Vector Consensus with Anonymous Proposals
    Christian Cachin, Daniel Collins, Tyler Crain, Vincent Gramoli
    http://arxiv.org/abs/1902.10010v1

    • [cs.DC]Fractal: Automated Application Scaling
    Masoud Koleini, Carlos Oviedo, Derek McAuley, Charalampos Rotsos, Anil Madhavapeddy, Thomas Gazagnaire, Magnus Skejgstad, Richard Mortier
    http://arxiv.org/abs/1902.09636v1

    • [cs.DC]Population protocols with unreliable communication
    Mikhail, Raskin
    http://arxiv.org/abs/1902.10041v1

    • [cs.DC]PubSub-SGX: Exploiting Trusted Execution Environments for Privacy-Preserving Publish/Subscribe Systems
    Sergei Arnautov, Andrey Brito, Pascal Felber, Christof Fetzer, Franz Gregor, Robert Krahn, Wojciech Ozga, André Martin, Valerio Schiavoni, Fábio Silva, Marcus Tenorio, Nikolaus Thümmel
    http://arxiv.org/abs/1902.09848v1

    • [cs.DC]Rucio - Scientific Data Management
    Martin Barisits, Thomas Beermann, Frank Berghaus, Brian Bockelman, Joaquin Bogado, David Cameron, Dimitrios Christidis, Diego Ciangottini, Gancho Dimitrov, Markus Elsing, Vincent Garonne, Alessandro di Girolamo, Luc Goossens, Wen Guan, Jaroslav Guenther, Tomas Javurek, Dietmar Kuhn, Mario Lassnig, Fernando Lopez, Nicolo Magini, Angelos Molfetas, Armin Nairz, Farid Ould-Saada, Stefan Prenner, Cedric Serfon, Graeme Stewart, Eric Vaandering, Petya Vasileva, Ralph Vigne, Tobias Wegner
    http://arxiv.org/abs/1902.09857v1

    • [cs.DC]Simulating Data Access Profiles of Computational Jobs in Data Grids
    Volodimir Begy, Joeri Hermans, Martin Barisits, Mario Lassnig, Erich Schikuta
    http://arxiv.org/abs/1902.10069v1

    • [cs.DC]clusterNOR: A NUMA-Optimized Clustering Framework
    Dia Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal Burns
    http://arxiv.org/abs/1902.09527v1

    • [cs.DC]cuSten -- CUDA Finite Difference and Stencil Library
    Andrew Gloster, Lennon O'Naraigh
    http://arxiv.org/abs/1902.09931v1

    • [cs.GT]Selling a Single Item with Negative Externalities
    Tithi Chattopadhyay, Nick Feamster, Matheus V. X. Ferreira, Danny Yuxing Huang, S. Matthew Weinberg
    http://arxiv.org/abs/1902.10008v1

    • [cs.HC]Analyzing the Use of Camera Glasses in the Wild
    Taryn Bipat, Maarten Willem Bos, Rajan Vaish, Andrés Monroy-Hernández
    http://arxiv.org/abs/1902.09749v1

    • [cs.IR]Bootstrapping Domain-Specific Content Discovery on the Web
    Kien Pham, Aécio Santos, Juliana Freire
    http://arxiv.org/abs/1902.09667v1

    • [cs.IR]Multi-Scale Quasi-RNN for Next Item Recommendation
    Chaoyue He, Yong Liu, Qingyu Guo, Chunyan Miao
    http://arxiv.org/abs/1902.09849v1

    • [cs.IT]Achieving Secrecy Capacity of Minimum Storage Regenerating Codes for all Feasible (n, k, d) Parameter Values
    V. Arvind Rameshwar, Navin Kashyap
    http://arxiv.org/abs/1902.09865v1

    • [cs.IT]Communications and Radar Coexistence in the Massive MIMO Regime: Uplink Analysis
    Carmen D'Andrea, Stefano Buzzi, Marco Lops
    http://arxiv.org/abs/1902.09603v1

    • [cs.IT]Fast Decoder for Overloaded Uniquely Decodable Synchronous Optical CDMA
    Michel Kulhandjian, Hovannes Kulhandjian, Claude D'Amours, Halim Yanikomeroglu, Gurgen Khachatrian
    http://arxiv.org/abs/1902.09525v1

    • [cs.IT]Joint Communication and Motion Energy Minimization in UGV Backscatter Communication
    Shuai Wang, Minghua Xia, Yik-Chung Wu
    http://arxiv.org/abs/1902.09759v1

    • [cs.IT]Joint Downlink Scheduling for File Placement and Delivery in Cache-Assisted Wireless Networks with Finite File Lifetime
    Bojie Lv, Lexiang Huang, Rui wang
    http://arxiv.org/abs/1902.09529v1

    • [cs.IT]Joint Task Assignment and Resource Allocation for D2D-Enabled Mobile-Edge Computing
    Hong Xing, Liang Liu, Jie Xu, Arumugam Nallanathan
    http://arxiv.org/abs/1902.10017v1

    • [cs.IT]Performance of Non-orthogonal Multiple Access under Finite Blocklength
    Endrit Dosit, Mohammad Shehabb, Hirley Alves, Matti Latva-aho
    http://arxiv.org/abs/1902.09993v1

    • [cs.IT]Robust Resource Allocation for PD-NOMA-Based MISO Heterogeneous Networks with CoMP Technology
    Atefeh Rezaei, Paeiz Azmi, Nader Mokari, Mohammad Reza Javan
    http://arxiv.org/abs/1902.09879v1

    • [cs.IT]Statistical Learning Aided Decoding of BMST of Tail-Biting Convolutional Code
    Xiao Ma, Wenchao Lin, Suihua Cai, Baodian Wei
    http://arxiv.org/abs/1902.09808v1

    • [cs.IT]Towards Higher Spectral Efficiency: Spatial Path Index Modulation Improves Millimeter-Wave Hybrid Beamforming
    Jintao Wang, Longzhuang He, Jian Song
    http://arxiv.org/abs/1902.09709v1

    • [cs.IT]Uniquely Decodable Ternary Codes for Synchronous CDMA Systems
    Michel Kulhandjian, Claude D'Amours, Hovannes Kulhandjian
    http://arxiv.org/abs/1902.09526v1

    • [cs.IT]Vector Gaussian CEO Problem Under Logarithmic Loss
    Yigit Ugur, Inaki Estella Aguerri, Abdellatif Zaidi
    http://arxiv.org/abs/1902.09537v1

    • [cs.LG]A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
    Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang
    http://arxiv.org/abs/1902.08722v2

    • [cs.LG]A Feature Selection Based on Perturbation Theory
    Javad Rahimipour Anaraki, Hamid Usefi
    http://arxiv.org/abs/1902.09938v1

    • [cs.LG]Adaptive Gradient Methods with Dynamic Bound of Learning Rate
    Liangchen Luo, Yuanhao Xiong, Yan Liu, Xu Sun
    http://arxiv.org/abs/1902.09843v1

    • [cs.LG]Anomaly Detection for an E-commerce Pricing System
    Jagdish Ramakrishnan, Elham Shaabani, Chao Li, Mátyás A. Sustik
    http://arxiv.org/abs/1902.09566v1

    • [cs.LG]Approximate Dynamic Programming with Neural Networks in Linear Discrete Action Spaces
    Wouter van Heeswijk, Han La Poutré
    http://arxiv.org/abs/1902.09855v1

    • [cs.LG]Automated Model Selection with Bayesian Quadrature
    Henry Chai, Jean-Francois Ton, Roman Garnett, Michael A. Osborne
    http://arxiv.org/abs/1902.09724v1

    • [cs.LG]Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control
    Jeremy Morton, Freddie D Witherden, Mykel J Kochenderfer
    http://arxiv.org/abs/1902.09742v1

    • [cs.LG]Fully Distributed Bayesian Optimization with Stochastic Policies
    Javier Garcia-Barcos, Ruben Martinez-Cantin
    http://arxiv.org/abs/1902.09992v1

    • [cs.LG]Functional Transparency for Structured Data: a Game-Theoretic Approach
    Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola
    http://arxiv.org/abs/1902.09737v1

    • [cs.LG]Fused Lasso for Feature Selection using Structural Information
    Lixin Cui, Lu Bai, Edwin R. Hancock
    http://arxiv.org/abs/1902.09947v1

    • [cs.LG]GAN-based Projector for Faster Recovery in Compressed Sensing with Convergence Guarantees
    Ankit Raj, Yuqi Li, Yoram Bresler
    http://arxiv.org/abs/1902.09698v1

    • [cs.LG]GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks
    Ziyao Li, Liang Zhang, Guojie Song
    http://arxiv.org/abs/1902.09817v1

    • [cs.LG]Graph Neural Processes: Towards Bayesian Graph Neural Networks
    Andrew N. Carr, David Wingate
    http://arxiv.org/abs/1902.10042v1

    • [cs.LG]HexaGAN: Generative Adversarial Nets for Real World Classification
    Uiwon Hwang, Dahuin Jung, Sungroh Yoon
    http://arxiv.org/abs/1902.09913v1

    • [cs.LG]Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets
    Homayun Afrabandpey, Tomi Peltola, Samuel Kaski
    http://arxiv.org/abs/1902.09834v1

    • [cs.LG]Interaction-aware Factorization Machines for Recommender Systems
    Fuxing Hong, Dongbo Huang, Ge Chen
    http://arxiv.org/abs/1902.09757v1

    • [cs.LG]Interpreting Active Learning Methods Through Information Losses
    Brandon Foggo, Nanpeng Yu
    http://arxiv.org/abs/1902.09602v1

    • [cs.LG]Learning Implicitly Recurrent CNNs Through Parameter Sharing
    Pedro Savarese, Michael Maire
    http://arxiv.org/abs/1902.09701v1

    • [cs.LG]Learning Vertex Convolutional Networks for Graph Classification
    Lu Bai, Lixin Cui, Shu Wu, Yuhang Jiao, Edwin R. Hancock
    http://arxiv.org/abs/1902.09936v1

    • [cs.LG]Learning to Find Hard Instances of Graph Problems
    Ryoma Sato, Makoto Yamada, Hisashi Kashima
    http://arxiv.org/abs/1902.09700v1

    • [cs.LG]MisGAN: Learning from Incomplete Data with Generative Adversarial Networks
    Steven Cheng-Xian Li, Bo Jiang, Benjamin Marlin
    http://arxiv.org/abs/1902.09599v1

    • [cs.LG]NAS-Bench-101: Towards Reproducible Neural Architecture Search
    Chris Ying, Aaron Klein, Esteban Real, Eric Christiansen, Kevin Murphy, Frank Hutter
    http://arxiv.org/abs/1902.09635v1

    • [cs.LG]Perturbed-History Exploration in Stochastic Multi-Armed Bandits
    Branislav Kveton, Csaba Szepesvari, Mohammad Ghavamzadeh, Craig Boutilier
    http://arxiv.org/abs/1902.10089v1

    • [cs.LG]Robust and Subject-Independent Driving Manoeuvre Anticipation through Domain-Adversarial Recurrent Neural Networks
    Michele Tonutti, Emanuele Ruffaldi, Alessandro Cattaneo, Carlo Alberto Avizzano
    http://arxiv.org/abs/1902.09820v1

    • [cs.LG]Short-term Road Traffic Prediction based on Deep Cluster at Large-scale Networks
    Lingyi Han, Kan Zheng, Long Zhao, Xianbin Wang, Xuemin Shen
    http://arxiv.org/abs/1902.09601v1

    • [cs.LG]Stochastic Prediction of Multi-Agent Interactions from Partial Observations
    Chen Sun, Per Karlsson, Jiajun Wu, Joshua B Tenenbaum, Kevin Murphy
    http://arxiv.org/abs/1902.09641v1

    • [cs.LG]The State of Sparsity in Deep Neural Networks
    Trevor Gale, Erich Elsen, Sara Hooker
    http://arxiv.org/abs/1902.09574v1

    • [cs.LG]Topological Bayesian Optimization with Persistence Diagrams
    Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada
    http://arxiv.org/abs/1902.09722v1

    • [cs.LG]Verification of Non-Linear Specifications for Neural Networks
    Chongli Qin, Krishnamurthy, Dvijotham, Brendan O'Donoghue, Rudy Bunel, Robert Stanforth, Sven Gowal, Jonathan Uesato, Grzegorz Swirszcz, Pushmeet Kohli
    http://arxiv.org/abs/1902.09592v1

    • [cs.MM]A multimodal movie review corpus for fine-grained opinion mining
    Alexandre Garcia, Slim Essid, Florence d'Alché-Buc, Chloé Clavel
    http://arxiv.org/abs/1902.10102v1

    • [cs.NE]Band-to-Band Tunneling based Ultra-Energy Efficient Silicon Neuron
    Tanmay Chavan, Sangya Dutta, Nihar R. Mohapatra, Udayan Ganguly
    http://arxiv.org/abs/1902.09726v1

    • [cs.NE]Spiking Neural Network based Region Proposal Networks for Neuromorphic Vision Sensors
    Jyotibdha Acharya, Vandana Padala, Arindam Basu
    http://arxiv.org/abs/1902.09864v1

    • [cs.NE]The importance of space and time in neuromorphic cognitive agents
    Giacomo Indiveri, Yulia Sandamirskaya
    http://arxiv.org/abs/1902.09791v1

    • [cs.NI]Optimal and Fast Real-time Resources Slicing with Deep Dueling Neural Networks
    Nguyen Van Huynh, Dinh Thai Hoang, Diep N. Nguyen, Eryk Dutkiewicz
    http://arxiv.org/abs/1902.09696v1

    • [cs.RO]A Multi-Domain Feature Learning Method for Visual Place Recognition
    Peng Yin, Lingyun Xu, Xueqian Li, Chen Yin, Yingli Li, Rangaprasad Arun Srivatsan, Lu Li, Jianmin Ji, Yuqing He
    http://arxiv.org/abs/1902.10058v1

    • [cs.RO]Acting Is Seeing: Navigating Tight Space Using Flapping Wings
    Zhan Tu, Fan Fei, Jian Zhang, Xinyan Deng
    http://arxiv.org/abs/1902.08688v1

    • [cs.RO]Beyond the Self: Using Grounded Affordances to Interpret and Describe Others' Actions
    Giovanni Saponaro, Lorenzo Jamone, Alexandre Bernardino, Giampiero Salvi
    http://arxiv.org/abs/1902.09705v1

    • [cs.RO]Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals
    Fan Fei, Zhan Tu, Yilun Yang, Jian Zhang, Xinyan Deng
    http://arxiv.org/abs/1902.09628v1

    • [cs.RO]Informative Path Planning and Mapping for Active Sensing Under Localization Uncertainty
    Marija Popovic, Teresa Vidal-Calleja, Jen Jen Chung, Juan Nieto, Roland Siegwart
    http://arxiv.org/abs/1902.09660v1

    • [cs.RO]Learning Extreme Hummingbird Maneuvers on Flapping Wing Robots
    Fan Fei, Zhan Tu, Jian Zhang, Xinyan Deng
    http://arxiv.org/abs/1902.09626v1

    • [cs.RO]MRS-VPR: a multi-resolution sampling based global visual place recognition method
    Peng Yin, Rangaprasad Arun Srivatsan, Yin Chen, Xueqian Li, Hongda Zhang, Lingyun Xu, Lu Li, Zhenzhong Jia, Jianmin Ji, Yuqing He
    http://arxiv.org/abs/1902.10059v1

    • [cs.RO]Semantic Relational Object Tracking
    Andreas Persson, Pedro Zuidberg Dos Martires, Amy Loutfi, Luc De Raedt
    http://arxiv.org/abs/1902.09937v1

    • [cs.RO]Sequential Learning of Visual Tracking and Mapping Using Unsupervised Deep Neural Networks
    Youngji Kim, Ayoung Kim
    http://arxiv.org/abs/1902.09826v1

    • [cs.RO]Simultaneous Detection of Loop-Closures and Changed Objects
    Tanaka Kanji, Yamaguchi Kousuke, Sugimoto Takuma
    http://arxiv.org/abs/1902.09822v1

    • [cs.SI]Community structure in co-inventor networks affects time to first citation for patents
    W. Doonan, K. W. Higham, M. Governale, U. Zülicke
    http://arxiv.org/abs/1902.09679v1

    • [econ.EM]On Binscatter
    Matias D. Cattaneo, Richard K. Crump, Max H. Farrell, Yingjie Feng
    http://arxiv.org/abs/1902.09608v1

    • [econ.EM]Semiparametric estimation of heterogeneous treatment effects under the nonignorable assignment condition
    Keisuke Takahata, Takahiro Hoshino
    http://arxiv.org/abs/1902.09978v1

    • [math.ST]A Dynamic Model for Double Bounded Time Series With Chaotic Driven Conditional Averages
    Guilherme Pumi, Taiane Schaedler Prass, Rafael Rigão Souza
    http://arxiv.org/abs/1902.09614v1

    • [math.ST]Effect Inference from Two-Group Data with Sampling Bias
    Dave Zachariah, Petre Stoica
    http://arxiv.org/abs/1902.09923v1

    • [math.ST]Penalized Sieve GEL for Weighted Average Derivatives of Nonparametric Quantile IV Regressions
    Xiaohong Chen, Demian Pouzo, James L. Powell
    http://arxiv.org/abs/1902.10100v1

    • [math.ST]Sample Splitting and Weak Assumption Inference For Time Series
    Robert Lunde
    http://arxiv.org/abs/1902.07425v2

    • [q-bio.QM]A Fully-Automatic Framework for Parkinson's Disease Diagnosis by Multi-Modality Images
    Jiahang Xu, Fangyang Jiao, Yechong Huang, Xinzhe Luo, Qian Xu, Ling Li, Xueling Liu, Chuantao Zuo, Ping Wu, Xiahai Zhuang
    http://arxiv.org/abs/1902.09934v1

    • [stat.AP]A Nested K-Nearest Prognostic Approach for Microwave Precipitation Phase Detection over Snow Cover
    Zeinab Takbiri, Ardeshir Ebtehaj, Efi Foufoula-Georgiou, Pierre-Emmanuel Kirstetter, F. Joseph Turk
    http://arxiv.org/abs/1902.09578v1

    • [stat.AP]A Source-Oriented Approach to Coal Power Plant Emissions Health Effects
    Kevin Cummiskey, Chanmin Kim, Christine Choirat, Lucas R. F. Henneman, Joel Schwartz, Corwin Zigler
    http://arxiv.org/abs/1902.09703v1

    • [stat.AP]Estimating Atmospheric Motion Winds from Satellite Image Data using Space-time Drift Models
    Indranil Sahoo, Joseph Guinness, Brian J. Reich
    http://arxiv.org/abs/1902.09653v1

    • [stat.AP]Protocol for an Observational Study of the Association of High School Football Participation on Health in Late Adulthood
    Timothy G. Gaulton, Sameer K. Deshpande, Dylan S. Small, Mark D. Neuman
    http://arxiv.org/abs/1902.10106v1

    • [stat.ME]Doubly stochastic distributions of extreme events
    Marco Marani, Enrico Zorzetto
    http://arxiv.org/abs/1902.09862v1

    • [stat.ME]Multiscale quantile regression
    Laura Jula Vanegas, Merle Behr, Axel Munk
    http://arxiv.org/abs/1902.09321v2

    • [stat.ME]Parameter Redundancy and the Existence of Maximum Likelihood Estimates in Log-linear Models
    Serveh Sharifi Far, Michail Papathomas, Ruth King
    http://arxiv.org/abs/1902.10009v1

    • [stat.ML]AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
    Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi
    http://arxiv.org/abs/1902.09689v1

    • [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/1902.09884v1

    • [stat.ML]Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era
    Nicolas Durrande, Vincent Adam, Lucas Bordeaux, Stefanos Eleftheriadis, James Hensman
    http://arxiv.org/abs/1902.10078v1

    • [stat.ML]Context Vectors are Reflections of Word Vectors in Half the Dimensions
    Zhenisbek Assylbekov, Rustem Takhanov
    http://arxiv.org/abs/1902.09859v1

    • [stat.ML]Efficient online learning with kernels for adversarial large scale problems
    Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
    http://arxiv.org/abs/1902.09917v1

    • [stat.ML]Function Space Particle Optimization for Bayesian Neural Networks
    Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang
    http://arxiv.org/abs/1902.09754v1

    • [stat.ML]Multiscale Gaussian Process Level Set Estimation
    Shubhanshu Shekhar, Tara Javidi
    http://arxiv.org/abs/1902.09682v1

    • [stat.ML]Online Framework for Demand-Responsive Stochastic Route Optimization
    Inon Peled, Kelvin Lee, Yu Jiang, Justin Dauwels, Francisco C. Pereira
    http://arxiv.org/abs/1902.09745v1

    • [stat.ML]Optimal Clustering with Missing Values
    Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian, Edward R. Dougherty
    http://arxiv.org/abs/1902.09694v1

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