astro-ph.CO - 宇宙学和天体物理学
cs.AI - 人工智能 cs.CL - 计算与语言 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 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.PF - 计算性能 cs.PL - 编程语言 cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.CO - 组合数学 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 physics.comp-ph - 计算物理学 q-fin.ST - 统计金融学 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [astro-ph.CO]Decoding Cosmological Information in Weak-Lensing Mass Maps with Generative Adversarial Networks
• [cs.AI]Abstract Argumentation and the Rational Man
• [cs.AI]DeepAlign: Alignment-based Process Anomaly Correction using Recurrent Neural Networks
• [cs.AI]Distributed Soft Actor-Critic with Multivariate Reward Representation and Knowledge Distillation
• [cs.AI]Learning Domain-Independent Planning Heuristics with Hypergraph Networks
• [cs.AI]Option-critic in cooperative multi-agent systems
• [cs.AI]Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learning
• [cs.AI]Procedural Content Generation: From Automatically Generating Game Levels to Increasing Generality in Machine Learning
• [cs.AI]Refining HTN Methods via Task Insertion with Preferences
• [cs.CL]A Fine-grained Sentiment Dataset for Norwegian
• [cs.CL]A Multi-cascaded Deep Model for Bilingual SMS Classification
• [cs.CL]An Iterative Polishing Framework based on Quality Aware Masked Language Model for Chinese Poetry Generation
• [cs.CL]Deconstructing and reconstructing word embedding algorithms
• [cs.CL]GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors
• [cs.CL]Inducing Relational Knowledge from BERT
• [cs.CL]Kurdish (Sorani) Speech to Text: Presenting an Experimental Dataset
• [cs.CL]Language-Independent Sentiment Analysis Using Subjectivity and Positional Information
• [cs.CL]Merging Weak and Active Supervision for Semantic Parsing
• [cs.CL]Metre as a stylometric feature in Latin hexameter poetry
• [cs.CL]Multimodal Machine Translation through Visuals and Speech
• [cs.CL]Neural Chinese Word Segmentation as Sequence to Sequence Translation
• [cs.CL]Sentiment Analysis On Indian Indigenous Languages: A Review On Multilingual Opinion Mining
• [cs.CL]Sentiment Analysis of German Twitter
• [cs.CV]Bi-Directional Domain Translation for Zero-Shot Sketch-Based Image Retrieval
• [cs.CV]Blockwisely Supervised Neural Architecture Search with Knowledge Distillation
• [cs.CV]CAGNet: Content-Aware Guidance for Salient Object Detection
• [cs.CV]Cameras Viewing Cameras Geometry
• [cs.CV]Collaborative Attention Network for Person Re-identification
• [cs.CV]Color inference from semantic labeling for person search in videos
• [cs.CV]Continuous Dropout
• [cs.CV]Correlation-aware Adversarial Domain Adaptation and Generalization
• [cs.CV]DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracing
• [cs.CV]Deep Object Co-segmentation via Spatial-Semantic Network Modulation
• [cs.CV]Domain-invariant Stereo Matching Networks
• [cs.CV]Geometric Feedback Network for Point Cloud Classification
• [cs.CV]Indirect Local Attacks for Context-aware Semantic Segmentation Networks
• [cs.CV]Investigations on the inference optimization techniques and their impact on multiple hardware platforms for Semantic Segmentation
• [cs.CV]Learning Generalizable Representations via Diverse Supervision
• [cs.CV]Learning Semantic Correspondence Exploiting an Object-level Prior
• [cs.CV]On the Benefits of Attributional Robustness
• [cs.CV]Online Structured Sparsity-based Moving Object Detection from Satellite Videos
• [cs.CV]Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization
• [cs.CV]Unpaired Image Translation via Adaptive Convolution-based Normalization
• [cs.CV]Using Fully Convolutional Neural Networks to detect manipulated images in videos
• [cs.CV]What’s Hidden in a Randomly Weighted Neural Network?
• [cs.CY]A Proposed Practical Problem-Solving Framework for Multi-Stakeholder Initiatives in Socio-Ecological Systems Based on a Model of the Human Cognitive Problem-Solving Process
• [cs.CY]Computer Systems Have 99 Problems, Let’s Not Make Machine Learning Another One
• [cs.CY]Recognition of Blockchain-based Multisignature E-Awards
• [cs.DB]Incremental Clustering Techniques for Multi-Party Privacy-Preserving Record Linkage
• [cs.DB]SOSD: A Benchmark for Learned Indexes
• [cs.DC]Adaptive Communication Bounds for Distributed Online Learning
• [cs.DC]Classification of distributed binary labeling problems
• [cs.DC]FirecREST: RESTful API on Cray XC systems
• [cs.DC]Lockless Transaction Isolation in Hyperledger Fabric
• [cs.DC]QoS-Aware Machine Learning-based Multiple Resources Scheduling for Microservices in Cloud Environment
• [cs.DC]Serverless seismic imaging in the cloud
• [cs.DS]Adversarially Robust Low Dimensional Representations
• [cs.HC]Designing the Next Generation of Intelligent Personal Robotic Assistants for the Physically Impaired
• [cs.IR]KPTimes: A Large-Scale Dataset for Keyphrase Generation on News Documents
• [cs.IR]Legal document retrieval across languages: topic hierarchies based on synsets
• [cs.IR]Macross: Urban Dynamics Modeling based on Metapath Guided Cross-Modal Embedding
• [cs.IT]A PHY Layer Security Analysis of Uplink Cooperative Jamming-Based Underlay CRNs with Multi-Eavesdroppers
• [cs.IT]A note on Douglas-Rachford, subgradients, and phase retrieval
• [cs.IT]Equivalence Relations for Computing Permutation Polynomials
• [cs.IT]Equivalence and Characterizations of Linear Rank-Metric Codes Based on Invariants
• [cs.IT]Lossless Size Reduction for Integer Least Squares with Application to Sphere Decoding
• [cs.IT]On the Effective Throughput of Coded Caching: A Game Theoretic Perspective
• [cs.IT]Randomized Decoding of Gabidulin Codes Beyond the Unique Decoding Radius
• [cs.IT]Rate Analysis of Cell-Free Massive MIMO-NOMA With Three Linear Precoders
• [cs.IT]Rate-Splitting for Multigroup Multicast Beamforming in Multicarrier Systems
• [cs.IT]Trainable Communication Systems: Concepts and Prototype
• [cs.LG]Augmented Random Search for Quadcopter Control: An alternative to Reinforcement Learning
• [cs.LG]Class Teaching for Inverse Reinforcement Learners
• [cs.LG]Communication-Efficient Distributed Online Learning with Kernels
• [cs.LG]Conditional Hierarchical Bayesian Tucker Decomposition
• [cs.LG]Deep Learning to Scale up Time Series Traffic Prediction
• [cs.LG]Deep Networks with Adaptive Nyström Approximation
• [cs.LG]Deep autofocus with cone-beam CT consistency constraint
• [cs.LG]FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions
• [cs.LG]Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019
• [cs.LG]Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation
• [cs.LG]Induction of Subgoal Automata for Reinforcement Learning
• [cs.LG]Learning Modular Representations for Long-Term Multi-Agent Motion Predictions
• [cs.LG]Learning and Planning for Time-Varying MDPs Using Maximum Likelihood Estimation
• [cs.LG]Machine Learning for a Low-cost Air Pollution Network
• [cs.LG]Mean Shift Rejection: Training Deep Neural Networks Without Minibatch Statistics or Normalization
• [cs.LG]Method and Dataset Mining in Scientific Papers
• [cs.LG]Model structures and fitting criteria for system identification with neural networks
• [cs.LG]Optimal Estimation of Change in a Population of Parameters
• [cs.LG]Optimal checkpointing for heterogeneous chains: how to train deep neural networks with limited memory
• [cs.LG]Orthogonal Wasserstein GANs
• [cs.LG]Product Knowledge Graph Embedding for E-commerce
• [cs.LG]QubitHD: A Stochastic Acceleration Method for HD Computing-Based Machine Learning
• [cs.LG]Richer priors for infinitely wide multi-layer perceptrons
• [cs.LG]STGRAT: A Spatio-Temporal Graph Attention Network for Traffic Forecasting
• [cs.LG]Short Term Prediction of Parking Area states Using Real Time Data and Machine Learning Techniques
• [cs.LG]Simulation-based reinforcement learning for real-world autonomous driving
• [cs.LG]Sparse and Low-Rank Tensor Regression via Parallel Proximal Method
• [cs.LG]Sparsely Grouped Input Variables for Neural Networks
• [cs.LG]Spatiotemporal deep learning model for citywide air pollution interpolation and prediction
• [cs.LG]The Weighted Tsetlin Machine: Compressed Representations with Weighted Clauses
• [cs.LG]Towards Oracle Knowledge Distillation with Neural Architecture Search
• [cs.LG]Transflow Learning: Repurposing Flow Models Without Retraining
• [cs.LG]Tropical Polynomial Division and Neural Networks
• [cs.LG]Using VAEs and Normalizing Flows for One-shot Text-To-Speech Synthesis of Expressive Speech
• [cs.LG]VIABLE: Fast Adaptation via Backpropagating Learned Loss
• [cs.LG]X-Ray Sobolev Variational Auto-Encoders
• [cs.MM]A Graph-based Ranking Approach to Extract Key-frames for Static Video Summarization
• [cs.NE]A spiking neural algorithm for the Network Flow problem
• [cs.NE]Android Botnet Detection using Convolutional Neural Networks
• [cs.NE]Operational Framework for Recent Advances in Backtracking Search Optimisation Algorithm: A Systematic Review and Performance Evaluation
• [cs.PF]Efficient method for parallel computation of geodesic transformation on CPU
• [cs.PL]Poq: Projection-based Runtime Assertions for Debugging on a Quantum Computer
• [cs.RO]A Benchmarking of DCM Based Architectures for Position, Velocity and Torque Controlled Humanoid Robots
• [cs.RO]DeepGoal: Learning to Drive with driving intention from Human Control Demonstration
• [cs.RO]Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling
• [cs.RO]LeRoP: A Learning-Based Modular Robot Photography Framework
• [cs.RO]Multiple quadrotors carrying a flexible hose: dynamics, differential flatness and control
• [cs.RO]Road Curb Detection Using A Novel Tensor Voting Algorithm
• [cs.SD]Improving Voice Separation by Incorporating End-to-end Speech Recognition
• [cs.SD]J-Net: Randomly weighted U-Net for audio source separation
• [cs.SD]Machine learning for music genre: multifaceted review and experimentation with audioset
• [cs.SI]Addressing Time Bias in Bipartite Graph Ranking for Important Node Identification
• [cs.SI]Algebraic analysis of multiple social networks with multiplex
• [cs.SI]Gender Patterns of Human Mobility in Colombia: Reexamining Ravenstein’s Laws of Migration
• [eess.IV]An adaptive and fully automatic method for estimating the 3D position of bendable instruments using endoscopic images
• [eess.IV]Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation
• [eess.IV]DIFAR: Deep Image Formation and Retouching
• [eess.IV]Learning from Irregularly Sampled Data for Endomicroscopy Super-resolution: A Comparative Study of Sparse and Dense Approaches
• [eess.IV]Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response
• [eess.SP]Data Transmission based on Exact Inverse Periodic Nonlinear Fourier Transform, Part II: Waveform Design and Experiment
• [eess.SP]Design and Prototyping of Hybrid Analogue Digital Multiuser MIMO Beamforming for Non-Orthogonal Signals
• [eess.SP]Detection of Derivative Discontinuities in Observational Data
• [eess.SP]Joint Power and Blocklength Optimization for URLLC in a Factory Automation Scenario
• [eess.SP]Resource Allocation for Secure URLLC in Vehicular Communications: A Physical Layer Perspective
• [math.CO]Constructions of Pairs of Orthogonal Latin Cubes
• [math.NA]Hierarchical Low-rank Structure of Parameterized Distributions
• [math.OC]A robust method based on LOVO functions for solving least squares problems
• [math.PR]Clique and cycle frequencies in a sparse random graph model with overlapping communities
• [math.PR]Dynamical fitness models: evidence of universality classes for preferential attachment graphs
• [math.PR]Maximum likelihood estimation for discrete exponential families and random graphs
• [math.ST]A note on the Lomax distribution
• [math.ST]Constraints in Gaussian Graphical Models
• [math.ST]Finite impulse response models: A non-asymptotic analysis of the least squares estimator
• [math.ST]Functional marked point processes — A natural structure to unify spatio-temporal frameworks and to analyse dependent functional data
• [math.ST]Goodness-of-fit test for the bivariate Hermite distribution
• [math.ST]Optimal and Adaptive Estimation of Extreme Values in the Permuted Monotone Matrix Model
• [physics.ao-ph]Detecting anthropogenic cloud perturbations with deep learning
• [physics.comp-ph]Progressive-Growing of Generative Adversarial Networks for Metasurface Optimization
• [q-fin.ST]Refinements of Barndorff-Nielsen and Shephard model: an analysis of crude oil price with machine learning
• [stat.AP]Application of Time Series Analysis to Traffic Accidents in Los Angeles
• [stat.AP]Comparative Study of Differentially Private Synthetic Data Algorithms and Evaluation Standards
• [stat.AP]Modelling dependence within and across run-off triangles for claims reserving
• [stat.AP]Predicting wave heights for marine design by prioritizing extreme events in a global model
• [stat.AP]Qini-based Uplift Regression
• [stat.ME]A review and evaluation of standard methods to handle missing data on time-varying confounders in marginal structural models
• [stat.ME]Causal inference of hazard ratio based on propensity score matching
• [stat.ME]Minkowski distances and standardisation for clustering and classification of high dimensional data
• [stat.ME]Modeling Spectral Properties in Stationary Processes of Varying Dimensions with Applications to Brain Local Field Potential Signals
• [stat.ME]Modelling publication bias and p-hacking
• [stat.ME]Novel Non-Negative Variance Estimator for (Modified) Within-Cluster Resampling
• [stat.ML]A Bayesian Dynamic Multilayered Block Network Model
• [stat.ML]Distributed estimation of principal support vector machines for sufficient dimension reduction
• [stat.ML]Embedding and learning with signatures
• [stat.ML]Link Prediction in the Stochastic Block Model with Outliers
• [stat.ML]Spike-and-wave epileptiform discharge pattern detection based on Kendall’s Tau-b coefficient
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• [astro-ph.CO]Decoding Cosmological Information in Weak-Lensing Mass Maps with Generative Adversarial Networks
Masato Shirasaki, Naoki Yoshida, Shiro Ikeda, Taira Oogi, Takahiro Nishimichi
http://arxiv.org/abs/1911.12890v1
• [cs.AI]Abstract Argumentation and the Rational Man
Timotheus Kampik, Juan Carlos Nieves
http://arxiv.org/abs/1911.13024v1
• [cs.AI]DeepAlign: Alignment-based Process Anomaly Correction using Recurrent Neural Networks
Timo Nolle, Alexander Seeliger, Nils Thoma, Max Mühlhäuser
http://arxiv.org/abs/1911.13229v1
• [cs.AI]Distributed Soft Actor-Critic with Multivariate Reward Representation and Knowledge Distillation
Dmitry Akimov
http://arxiv.org/abs/1911.13056v1
• [cs.AI]Learning Domain-Independent Planning Heuristics with Hypergraph Networks
William Shen, Felipe Trevizan, Sylvie Thiébaux
http://arxiv.org/abs/1911.13101v1
• [cs.AI]Option-critic in cooperative multi-agent systems
Jhelum Chakravorty, Nadeem Ward, Julien Roy, Maxime Chevalier-Boisvert, Sumana Basu, Andrei Lupu, Doina Precup
http://arxiv.org/abs/1911.12825v1
• [cs.AI]Playing Games in the Dark: An approach for cross-modality transfer in reinforcement learning
Rui Silva, Miguel Vasco, Francisco S. Melo, Ana Paiva, Manuela Veloso
http://arxiv.org/abs/1911.12851v1
• [cs.AI]Procedural Content Generation: From Automatically Generating Game Levels to Increasing Generality in Machine Learning
Sebastian Risi, Julian Togelius
http://arxiv.org/abs/1911.13071v1
• [cs.AI]Refining HTN Methods via Task Insertion with Preferences
Zhanhao Xiao, Hai Wan, Hankui Hankz Zhuo, Andreas Herzig, Laurent Perrussel, Peilin Chen
http://arxiv.org/abs/1911.12949v1
• [cs.CL]A Fine-grained Sentiment Dataset for Norwegian
Lilja Øvrelid, Petter Mæhlum, Jeremy Barnes, Erik Velldal
http://arxiv.org/abs/1911.12722v1
• [cs.CL]A Multi-cascaded Deep Model for Bilingual SMS Classification
Muhammad Haroon Shakeel, Asim Karim, Imdadullah Khan
http://arxiv.org/abs/1911.13066v1
• [cs.CL]An Iterative Polishing Framework based on Quality Aware Masked Language Model for Chinese Poetry Generation
Liming Deng, Jie Wang, Hangming Liang, Hui Chen, Zhiqiang Xie, Bojin Zhuang, Shaojun Wang, Jing Xiao
http://arxiv.org/abs/1911.13182v1
• [cs.CL]Deconstructing and reconstructing word embedding algorithms
Edward Newell, Kian Kenyon-Dean, Jackie Chi Kit Cheung
http://arxiv.org/abs/1911.13280v1
• [cs.CL]GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors
Masato Hagiwara, Masato Mita
http://arxiv.org/abs/1911.12893v1
• [cs.CL]Inducing Relational Knowledge from BERT
Zied Bouraoui, Jose Camacho-Collados, Steven Schockaert
http://arxiv.org/abs/1911.12753v1
• [cs.CL]Kurdish (Sorani) Speech to Text: Presenting an Experimental Dataset
Akam Qader, Hossein Hassani
http://arxiv.org/abs/1911.13087v1
• [cs.CL]Language-Independent Sentiment Analysis Using Subjectivity and Positional Information
Veselin Raychev, Preslav Nakov
http://arxiv.org/abs/1911.12544v1
• [cs.CL]Merging Weak and Active Supervision for Semantic Parsing
Ansong Ni, Pengcheng Yin, Graham Neubig
http://arxiv.org/abs/1911.12986v1
• [cs.CL]Metre as a stylometric feature in Latin hexameter poetry
Benjamin Nagy
http://arxiv.org/abs/1911.12478v1
• [cs.CL]Multimodal Machine Translation through Visuals and Speech
Umut Sulubacak, Ozan Caglayan, Stig-Arne Grönroos, Aku Rouhe, Desmond Elliott, Lucia Specia, Jörg Tiedemann
http://arxiv.org/abs/1911.12798v1
• [cs.CL]Neural Chinese Word Segmentation as Sequence to Sequence Translation
Xuewen Shi, Heyan Huang, Ping Jian, Yuhang Guo, Xiaochi Wei, Yi-Kun Tang
http://arxiv.org/abs/1911.12982v1
• [cs.CL]Sentiment Analysis On Indian Indigenous Languages: A Review On Multilingual Opinion Mining
Sonali Rajesh Shah, Abhishek Kaushik
http://arxiv.org/abs/1911.12848v1
• [cs.CL]Sentiment Analysis of German Twitter
Wladimir Sidorenko
http://arxiv.org/abs/1911.13062v1
• [cs.CV]Bi-Directional Domain Translation for Zero-Shot Sketch-Based Image Retrieval
Jiangtong Li, Zhixin Ling, Li Niu, Liqing Zhang
http://arxiv.org/abs/1911.13251v1
• [cs.CV]Blockwisely Supervised Neural Architecture Search with Knowledge Distillation
Changlin Li, Jiefeng Peng, Liuchun Yuan, Guangrun Wang, Xiaodan Liang, Liang Lin, Xiaojun Chang
http://arxiv.org/abs/1911.13053v1
• [cs.CV]CAGNet: Content-Aware Guidance for Salient Object Detection
Sina Mohammadi, Mehrdad Noori, Ali Bahri, Sina Ghofrani Majelan, Mohammad Havaei
http://arxiv.org/abs/1911.13168v1
• [cs.CV]Cameras Viewing Cameras Geometry
Danail Brezov, Michael Werman
http://arxiv.org/abs/1911.12706v1
• [cs.CV]Collaborative Attention Network for Person Re-identification
Wenpeng Li, Yongli Sun, Jinjun Wang, Han Xu, Xiangru Yang, Long Cui
http://arxiv.org/abs/1911.13008v1
• [cs.CV]Color inference from semantic labeling for person search in videos
Jules Simon, Guillaume-Alexandre Bilodeau, David Steele, Harshad Mahadik
http://arxiv.org/abs/1911.13114v1
• [cs.CV]Continuous Dropout
Xu Shen, Xinmei Tian, Tongliang Liu, Fang Xu, Dacheng Tao
http://arxiv.org/abs/1911.12675v1
• [cs.CV]Correlation-aware Adversarial Domain Adaptation and Generalization
Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan
http://arxiv.org/abs/1911.12983v1
• [cs.CV]DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracing
Shaohui Liu, Yinda Zhang, Songyou Peng, Boxin Shi, Marc Pollefeys, Zhaopeng Cui
http://arxiv.org/abs/1911.13225v1
• [cs.CV]Deep Object Co-segmentation via Spatial-Semantic Network Modulation
Kaihua Zhang, Jin Chen, Bo Liu, Qingshan Liu
http://arxiv.org/abs/1911.12950v1
• [cs.CV]Domain-invariant Stereo Matching Networks
Feihu Zhang, Xiaojuan Qi, Ruigang Yang, Victor Prisacariu, Benjamin Wah, Philip Torr
http://arxiv.org/abs/1911.13287v1
• [cs.CV]Geometric Feedback Network for Point Cloud Classification
Qiu Shi, Saeed Anwar, Nick Barnes
http://arxiv.org/abs/1911.12885v1
• [cs.CV]Indirect Local Attacks for Context-aware Semantic Segmentation Networks
Krishna Kanth Nakka, Mathieu Salzmann
http://arxiv.org/abs/1911.13038v1
• [cs.CV]Investigations on the inference optimization techniques and their impact on multiple hardware platforms for Semantic Segmentation
Sethu Hareesh Kolluru
http://arxiv.org/abs/1911.12993v1
• [cs.CV]Learning Generalizable Representations via Diverse Supervision
Ziqi Pang, Zhiyuan Hu, Pavel Tokmakov, Yu-Xiong Wang, Martial Hebert
http://arxiv.org/abs/1911.12911v1
• [cs.CV]Learning Semantic Correspondence Exploiting an Object-level Prior
Junghyup Lee, Dohyung Kim, Wonkyung Lee, Jean Ponce, Bumsub Ham
http://arxiv.org/abs/1911.12914v1
• [cs.CV]On the Benefits of Attributional Robustness
Mayank Singh, Nupur Kumari, Puneet Mangla, Abhishek Sinha, Vineeth N Balasubramanian, Balaji Krishnamurthy
http://arxiv.org/abs/1911.13073v1
• [cs.CV]Online Structured Sparsity-based Moving Object Detection from Satellite Videos
Zhang Junpeng, JIa Xiuping, Hu Junkun, Chanussot Jocelyn
http://arxiv.org/abs/1911.12989v1
• [cs.CV]Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization
Jihun Yun, Jung Hyun Lee, Sung Ju Hwang, Eunho Yang
http://arxiv.org/abs/1911.12990v1
• [cs.CV]Unpaired Image Translation via Adaptive Convolution-based Normalization
Wonwoong Cho, Kangyeol Kim, Eungyeup Kim, Hyunwoo J. Kim, Jaegul Choo
http://arxiv.org/abs/1911.13271v1
• [cs.CV]Using Fully Convolutional Neural Networks to detect manipulated images in videos
Michail Tarasiou, Stefanos Zafeiriou
http://arxiv.org/abs/1911.13269v1
• [cs.CV]What’s Hidden in a Randomly Weighted Neural Network?
Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi, Ali Farhadi, Mohammad Rastegari
http://arxiv.org/abs/1911.13299v1
• [cs.CY]A Proposed Practical Problem-Solving Framework for Multi-Stakeholder Initiatives in Socio-Ecological Systems Based on a Model of the Human Cognitive Problem-Solving Process
Kevin Kells
http://arxiv.org/abs/1911.13155v1
• [cs.CY]Computer Systems Have 99 Problems, Let’s Not Make Machine Learning Another One
David Mohaisen, Songqing Chen
http://arxiv.org/abs/1911.12593v1
• [cs.CY]Recognition of Blockchain-based Multisignature E-Awards
A. J. Santos
http://arxiv.org/abs/1911.12968v1
• [cs.DB]Incremental Clustering Techniques for Multi-Party Privacy-Preserving Record Linkage
Dinusha Vatsalan, Peter Christen, Erhard Rahm
http://arxiv.org/abs/1911.12930v1
• [cs.DB]SOSD: A Benchmark for Learned Indexes
Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann
http://arxiv.org/abs/1911.13014v1
• [cs.DC]Adaptive Communication Bounds for Distributed Online Learning
Michael Kamp, Mario Boley, Michael Mock, Daniel Keren, Assaf Schuster, Izchak Sharfman
http://arxiv.org/abs/1911.12896v1
• [cs.DC]Classification of distributed binary labeling problems
Alkida Balliu, Sebastian Brandt, Yuval Efron, Juho Hirvonen, Yannic Maus, Dennis Olivetti, Jukka Suomela
http://arxiv.org/abs/1911.13294v1
• [cs.DC]FirecREST: RESTful API on Cray XC systems
Felipe A. Cruz, Maxime Martinasso
http://arxiv.org/abs/1911.13160v1
• [cs.DC]Lockless Transaction Isolation in Hyperledger Fabric
Hagar Meir, Artem Barger, Yacov Manevich, Yoav Tock
http://arxiv.org/abs/1911.12711v1
• [cs.DC]QoS-Aware Machine Learning-based Multiple Resources Scheduling for Microservices in Cloud Environment
Lei Liu
http://arxiv.org/abs/1911.13208v1
• [cs.DC]Serverless seismic imaging in the cloud
Philipp A. Witte, Mathias Louboutin, Charles Jones, Felix J. Herrmann
http://arxiv.org/abs/1911.12447v1
• [cs.DS]Adversarially Robust Low Dimensional Representations
Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan
http://arxiv.org/abs/1911.13268v1
• [cs.HC]Designing the Next Generation of Intelligent Personal Robotic Assistants for the Physically Impaired
Basit Ayantunde, Jane Odum, Fadlullah Olawumi, Joshua Olalekan
http://arxiv.org/abs/1911.12482v1
• [cs.IR]KPTimes: A Large-Scale Dataset for Keyphrase Generation on News Documents
Ygor Gallina, Florian Boudin, Béatrice Daille
http://arxiv.org/abs/1911.12559v1
• [cs.IR]Legal document retrieval across languages: topic hierarchies based on synsets
Carlos Badenes-Olmedo, Jose-Luis Redondo-Garcia, Oscar Corcho
http://arxiv.org/abs/1911.12637v1
• [cs.IR]Macross: Urban Dynamics Modeling based on Metapath Guided Cross-Modal Embedding
Yunan Zhang, Heting Gao, Tarek Abdelzaher
http://arxiv.org/abs/1911.12866v1
• [cs.IT]A PHY Layer Security Analysis of Uplink Cooperative Jamming-Based Underlay CRNs with Multi-Eavesdroppers
Mounia Bouabdellah, Faissal El Bouanani, Mohamed-Slim Alouini
http://arxiv.org/abs/1911.12898v1
• [cs.IT]A note on Douglas-Rachford, subgradients, and phase retrieval
Eitan Levin, Tamir Bendory
http://arxiv.org/abs/1911.13179v1
• [cs.IT]Equivalence Relations for Computing Permutation Polynomials
Sergey Bereg, Brian Malouf, Linda Morales, Thomas Stanley, I. Hal Sudborough, Alexander Wong
http://arxiv.org/abs/1911.12823v1
• [cs.IT]Equivalence and Characterizations of Linear Rank-Metric Codes Based on Invariants
Alessandro Neri, Sven Puchinger, Anna-Lena Horlemann-Trautmann
http://arxiv.org/abs/1911.13059v1
• [cs.IT]Lossless Size Reduction for Integer Least Squares with Application to Sphere Decoding
Mohammad Neinavaie, Mostafa~Derakhtian, Sergiy A. Vorobyov
http://arxiv.org/abs/1911.13172v1
• [cs.IT]On the Effective Throughput of Coded Caching: A Game Theoretic Perspective
Yawei Lu, Wei Chen, H. Vincent Poor
http://arxiv.org/abs/1911.12981v1
• [cs.IT]Randomized Decoding of Gabidulin Codes Beyond the Unique Decoding Radius
Julian Renner, Thomas Jerkovits, Hannes Bartz, Sven Puchinger, Pierre Loidreau, Antonia Wachter-Zeh
http://arxiv.org/abs/1911.13193v1
• [cs.IT]Rate Analysis of Cell-Free Massive MIMO-NOMA With Three Linear Precoders
Fatemeh Rezaei, Chintha Tellambura, Aliakbar Tadaion, Ali Reza Heidarpour
http://arxiv.org/abs/1911.12797v1
• [cs.IT]Rate-Splitting for Multigroup Multicast Beamforming in Multicarrier Systems
Hongzhi Chen, De Mi, Zheng Chu, Pei Xiao, Rahim Tafazolli
http://arxiv.org/abs/1911.13130v1
• [cs.IT]Trainable Communication Systems: Concepts and Prototype
Sebastian Cammerer, Fayçal Ait Aoudia, Sebastian Dörner, Maximilian Stark, Jakob Hoydis, Stephan ten Brink
http://arxiv.org/abs/1911.13055v1
• [cs.LG]Augmented Random Search for Quadcopter Control: An alternative to Reinforcement Learning
Ashutosh Kumar Tiwari, Sandeep Varma Nadimpalli
http://arxiv.org/abs/1911.12553v1
• [cs.LG]Class Teaching for Inverse Reinforcement Learners
Manuel Lopes, Francisco Melo
http://arxiv.org/abs/1911.13009v1
• [cs.LG]Communication-Efficient Distributed Online Learning with Kernels
Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock
http://arxiv.org/abs/1911.12899v1
• [cs.LG]Conditional Hierarchical Bayesian Tucker Decomposition
Adam Sandler, Diego Klabjan, Yuan Luo
http://arxiv.org/abs/1911.12426v1
• [cs.LG]Deep Learning to Scale up Time Series Traffic Prediction
Julien Monteil, Anton Dekusar, Claudio Gambella, Yassine Lassoued, Martin Mevissen
http://arxiv.org/abs/1911.13042v1
• [cs.LG]Deep Networks with Adaptive Nyström Approximation
Luc Giffon, Stéphane Ayache, Thierry Artières, Hachem Kadri
http://arxiv.org/abs/1911.13036v1
• [cs.LG]Deep autofocus with cone-beam CT consistency constraint
Alexander Preuhs, Michael Manhart, Philipp Roser, Bernhard Stimpel, Christopher Syben, Marios Psychogios, Markus Kowarschik, Andreas Maier
http://arxiv.org/abs/1911.13162v1
• [cs.LG]FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions
Sebastian Schelter, Yuxuan He, Jatin Khilnani, Julia Stoyanovich
http://arxiv.org/abs/1911.12587v1
• [cs.LG]Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019
Omer Berat Sezer, Mehmet Ugur Gudelek, Ahmet Murat Ozbayoglu
http://arxiv.org/abs/1911.13288v1
• [cs.LG]Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation
George De Ath, Richard M. Everson, Alma A. M. Rahat, Jonathan E. Fieldsend
http://arxiv.org/abs/1911.12809v1
• [cs.LG]Induction of Subgoal Automata for Reinforcement Learning
Daniel Furelos-Blanco, Mark Law, Alessandra Russo, Krysia Broda, Anders Jonsson
http://arxiv.org/abs/1911.13152v1
• [cs.LG]Learning Modular Representations for Long-Term Multi-Agent Motion Predictions
Todor Davchev, Michael Burke, Subramanian Ramamoorhty
http://arxiv.org/abs/1911.13044v1
• [cs.LG]Learning and Planning for Time-Varying MDPs Using Maximum Likelihood Estimation
Melkior Ornik, Ufuk Topcu
http://arxiv.org/abs/1911.12976v1
• [cs.LG]Machine Learning for a Low-cost Air Pollution Network
Michael T. Smith, Joel Ssematimba, Mauricio A. Alvarez, Engineer Bainomugisha
http://arxiv.org/abs/1911.12868v1
• [cs.LG]Mean Shift Rejection: Training Deep Neural Networks Without Minibatch Statistics or Normalization
Brendan Ruff, Taylor Beck, Joscha Bach
http://arxiv.org/abs/1911.13173v1
• [cs.LG]Method and Dataset Mining in Scientific Papers
Rujing Yao, Linlin Hou, Yingchun Ye, Ou Wu, Ji Zhang, Jian Wu
http://arxiv.org/abs/1911.13096v1
• [cs.LG]Model structures and fitting criteria for system identification with neural networks
Marco Forgione, Dario Piga
http://arxiv.org/abs/1911.13034v1
• [cs.LG]Optimal Estimation of Change in a Population of Parameters
Ramya Korlakai Vinayak, Weihao Kong, Sham M. Kakade
http://arxiv.org/abs/1911.12568v1
• [cs.LG]Optimal checkpointing for heterogeneous chains: how to train deep neural networks with limited memory
Julien Herrmann, Olivier Beaumont, Lionel Eyraud-Dubois, Julien Hermann, Alexis Joly, Alena Shilova
http://arxiv.org/abs/1911.13214v1
• [cs.LG]Orthogonal Wasserstein GANs
Jan Müller, Reinhard Klein, Michael Weinmann
http://arxiv.org/abs/1911.13060v1
• [cs.LG]Product Knowledge Graph Embedding for E-commerce
Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan
http://arxiv.org/abs/1911.12481v1
• [cs.LG]QubitHD: A Stochastic Acceleration Method for HD Computing-Based Machine Learning
Samuel Bosch, Alexander Sanchez de la Cerda, Tajana Simunic Rosing, Giovanni De Micheli
http://arxiv.org/abs/1911.12446v1
• [cs.LG]Richer priors for infinitely wide multi-layer perceptrons
Russell Tsuchida, Fred Roosta, Marcus Gallagher
http://arxiv.org/abs/1911.12927v1
• [cs.LG]STGRAT: A Spatio-Temporal Graph Attention Network for Traffic Forecasting
Cheonbok Park, Chunggi Lee, Hyojin Bahng, Taeyun won, Kihwan Kim, Seungmin Jin, Sungahn Ko, Jaegul Choo
http://arxiv.org/abs/1911.13181v1
• [cs.LG]Short Term Prediction of Parking Area states Using Real Time Data and Machine Learning Techniques
Jesper Provoost, Luc Wismans, Sander Van der Drift, Andreas Kamilaris, Maurice Van Keulen
http://arxiv.org/abs/1911.13178v1
• [cs.LG]Simulation-based reinforcement learning for real-world autonomous driving
Błażej Osiński, Adam Jakubowski, Piotr Miłoś, Paweł Zięcina, Christopher Galias, Henryk Michalewski
http://arxiv.org/abs/1911.12905v1
• [cs.LG]Sparse and Low-Rank Tensor Regression via Parallel Proximal Method
Jiaqi Zhang, Beilun Wang
http://arxiv.org/abs/1911.12965v1
• [cs.LG]Sparsely Grouped Input Variables for Neural Networks
Beibin Li, Nicholas Nuechterlein, Erin Barney, Caitlin Hudac, Pamela Ventola, Linda Shapiro, Frederick Shic
http://arxiv.org/abs/1911.13068v1
• [cs.LG]Spatiotemporal deep learning model for citywide air pollution interpolation and prediction
Van-Duc Le, Tien-Cuong Bui, Sang Kyun Cha
http://arxiv.org/abs/1911.12919v1
• [cs.LG]The Weighted Tsetlin Machine: Compressed Representations with Weighted Clauses
Adrian Phoulady, Ole-Christoffer Granmo, Saeed Rahimi Gorji, Hady Ahmady Phoulady
http://arxiv.org/abs/1911.12607v1
• [cs.LG]Towards Oracle Knowledge Distillation with Neural Architecture Search
Minsoo Kang, Jonghwan Mun, Bohyung Han
http://arxiv.org/abs/1911.13019v1
• [cs.LG]Transflow Learning: Repurposing Flow Models Without Retraining
Andrew Gambardella, Atılım Güneş Baydin, Philip H. S. Torr
http://arxiv.org/abs/1911.13270v1
• [cs.LG]Tropical Polynomial Division and Neural Networks
Georgios Smyrnis, Petros Maragos
http://arxiv.org/abs/1911.12922v1
• [cs.LG]Using VAEs and Normalizing Flows for One-shot Text-To-Speech Synthesis of Expressive Speech
Vatsal Aggarwal, Marius Cotescu, Nishant Prateek, Jaime Lorenzo-Trueba, Roberto Barra-Chicote
http://arxiv.org/abs/1911.12760v1
• [cs.LG]VIABLE: Fast Adaptation via Backpropagating Learned Loss
Leo Feng, Luisa Zintgraf, Bei Peng, Shimon Whiteson
http://arxiv.org/abs/1911.13159v1
• [cs.LG]X-Ray Sobolev Variational Auto-Encoders
Gabriel Turinici
http://arxiv.org/abs/1911.13135v1
• [cs.MM]A Graph-based Ranking Approach to Extract Key-frames for Static Video Summarization
Saikat Chakraborty
http://arxiv.org/abs/1911.13279v1
• [cs.NE]A spiking neural algorithm for the Network Flow problem
Abdullahi Ali, Johan Kwisthout
http://arxiv.org/abs/1911.13097v1
• [cs.NE]Android Botnet Detection using Convolutional Neural Networks
Sina Hojjatinia, Sajad Hamzenejadi, Hadis Mohseni
http://arxiv.org/abs/1911.12457v1
• [cs.NE]Operational Framework for Recent Advances in Backtracking Search Optimisation Algorithm: A Systematic Review and Performance Evaluation
Bryar A. Hassan Tarik A. Rashid
http://arxiv.org/abs/1911.13011v1
• [cs.PF]Efficient method for parallel computation of geodesic transformation on CPU
Danijel Žlaus, Domen Mongus
http://arxiv.org/abs/1911.13074v1
• [cs.PL]Poq: Projection-based Runtime Assertions for Debugging on a Quantum Computer
Gushu Li, Li Zhou, Nengkun Yu, Yufei Ding, Mingsheng Ying, Yuan Xie
http://arxiv.org/abs/1911.12855v1
• [cs.RO]A Benchmarking of DCM Based Architectures for Position, Velocity and Torque Controlled Humanoid Robots
Giulio Romualdi, Stefano Dafarra, Yue Hu, Prashanth Ramadoss, Francisco Javier Andrade Chavez, Silvio Traversaro, Daniele Pucci
http://arxiv.org/abs/1911.13233v1
• [cs.RO]DeepGoal: Learning to Drive with driving intention from Human Control Demonstration
Huifang Ma, Yue Wang, Rong Xiong, Sarath Kodagoda, Li Tang
http://arxiv.org/abs/1911.12610v1
• [cs.RO]Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling
Xin Huang, Stephen G. McGill, Jonathan A. DeCastro, Brian C. Williams, Luke Fletcher, John J. Leonard, Guy Rosman
http://arxiv.org/abs/1911.12736v1
• [cs.RO]LeRoP: A Learning-Based Modular Robot Photography Framework
Hao Kang, Jianming Zhang, Haoxiang Li, Zhe Lin, TJ Rhodes, Bedrich Benes
http://arxiv.org/abs/1911.12470v1
• [cs.RO]Multiple quadrotors carrying a flexible hose: dynamics, differential flatness and control
Prasanth Kotaru, Koushil Sreenath
http://arxiv.org/abs/1911.12650v1
• [cs.RO]Road Curb Detection Using A Novel Tensor Voting Algorithm
Yilong Zhu, Dong Han, Bohuan Xue, Jianhao Jiao, Zuhao Zou, Ming Liu, Rui Fan
http://arxiv.org/abs/1911.12937v1
• [cs.SD]Improving Voice Separation by Incorporating End-to-end Speech Recognition
Naoya Takahashi, Mayank Kumar Singh, Sakya Basak, Parthasaarathy Sudarsanam, Sriram Ganapathy, Yuki Mitsufuji
http://arxiv.org/abs/1911.12928v1
• [cs.SD]J-Net: Randomly weighted U-Net for audio source separation
Bo-Wen Chen, Yen-Min Hsu, Hung-Yi Lee
http://arxiv.org/abs/1911.12926v1
• [cs.SD]Machine learning for music genre: multifaceted review and experimentation with audioset
Jaime Ramírez, M. Julia Flores
http://arxiv.org/abs/1911.12618v1
• [cs.SI]Addressing Time Bias in Bipartite Graph Ranking for Important Node Identification
Hao Liao, Jiao Wu, Mingyang Zhou, Alexandre Vidmer
http://arxiv.org/abs/1911.12558v1
• [cs.SI]Algebraic analysis of multiple social networks with multiplex
J Antonio Rivero Ostoic
http://arxiv.org/abs/1911.13037v1
• [cs.SI]Gender Patterns of Human Mobility in Colombia: Reexamining Ravenstein’s Laws of Migration
Mariana Macedo, Laura Lotero, Alessio Cardillo, Hugo Barbosa, Ronaldo Menezes
http://arxiv.org/abs/1911.12984v1
• [eess.IV]An adaptive and fully automatic method for estimating the 3D position of bendable instruments using endoscopic images
Paolo Cabras, Florent Nageotte, Philippe Zanne, Christophe Doignon
http://arxiv.org/abs/1911.13125v1
• [eess.IV]Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation
Alireza Mehrtash, William M. Wells III, Clare M. Tempany, Purang Abolmaesumi, Tina Kapur
http://arxiv.org/abs/1911.13273v1
• [eess.IV]DIFAR: Deep Image Formation and Retouching
Sean Moran, Gregory Slabaugh
http://arxiv.org/abs/1911.13175v1
• [eess.IV]Learning from Irregularly Sampled Data for Endomicroscopy Super-resolution: A Comparative Study of Sparse and Dense Approaches
Agnieszka Barbara Szczotka, Dzhoshkun Ismail Shakir, DanieleRavi, Matthew J. Clarkson, Stephen P. Pereira, Tom Vercauteren
http://arxiv.org/abs/1911.13169v1
• [eess.IV]Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response
Kazuya Nishimura, Dai Fei Elmer Ker, Ryoma Bise
http://arxiv.org/abs/1911.13077v1
• [eess.SP]Data Transmission based on Exact Inverse Periodic Nonlinear Fourier Transform, Part II: Waveform Design and Experiment
Jan-Willem Goossens, Hartmut Hafermann, Yves Jaouën
http://arxiv.org/abs/1911.12615v1
• [eess.SP]Design and Prototyping of Hybrid Analogue Digital Multiuser MIMO Beamforming for Non-Orthogonal Signals
Tongyang Xu, Christos Masouros, Izzat Darwazeh
http://arxiv.org/abs/1911.12880v1
• [eess.SP]Detection of Derivative Discontinuities in Observational Data
Dimitar Ninevski, Paul O’Leary
http://arxiv.org/abs/1911.12724v1
• [eess.SP]Joint Power and Blocklength Optimization for URLLC in a Factory Automation Scenario
Hong Ren, Cunhua Pan, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan
http://arxiv.org/abs/1911.13050v1
• [eess.SP]Resource Allocation for Secure URLLC in Vehicular Communications: A Physical Layer Perspective
Hong Ren, Cunhua Pan, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan
http://arxiv.org/abs/1911.13154v1
• [math.CO]Constructions of Pairs of Orthogonal Latin Cubes
Vladimir N. Potapov
http://arxiv.org/abs/1911.12960v1
• [math.NA]Hierarchical Low-rank Structure of Parameterized Distributions
Jun Qin, Lexing Ying
http://arxiv.org/abs/1911.13277v1
• [math.OC]A robust method based on LOVO functions for solving least squares problems
E. V. Castelani, R. Lopes, W. V. I. Shirabayashi, F. N. C. Sobral
http://arxiv.org/abs/1911.13078v1
• [math.PR]Clique and cycle frequencies in a sparse random graph model with overlapping communities
Tommi Gröhn, Joona Karjalainen, Lasse Leskelä
http://arxiv.org/abs/1911.12827v1
• [math.PR]Dynamical fitness models: evidence of universality classes for preferential attachment graphs
Alessandra Cipriani, Andrea Fontanari
http://arxiv.org/abs/1911.12402v1
• [math.PR]Maximum likelihood estimation for discrete exponential families and random graphs
Krzysztof Bogdan, Michał Bosy, Tomasz Skalski
http://arxiv.org/abs/1911.13143v1
• [math.ST]A note on the Lomax distribution
Tanujit Chakraborty
http://arxiv.org/abs/1911.12612v1
• [math.ST]Constraints in Gaussian Graphical Models
Bohao Yao, Robin Evans
http://arxiv.org/abs/1911.12754v1
• [math.ST]Finite impulse response models: A non-asymptotic analysis of the least squares estimator
Boualem Djehiche, Othmane Mazhar, Cristian R. Rojas
http://arxiv.org/abs/1911.12794v1
• [math.ST]Functional marked point processes — A natural structure to unify spatio-temporal frameworks and to analyse dependent functional data
Ottmar Cronie, Mohammad Ghorbani, Jorge Mateu, Jun Yu
http://arxiv.org/abs/1911.13142v1
• [math.ST]Goodness-of-fit test for the bivariate Hermite distribution
Pablo González-Albornoz, Francisco Novoa-Muñoz
http://arxiv.org/abs/1911.12400v1
• [math.ST]Optimal and Adaptive Estimation of Extreme Values in the Permuted Monotone Matrix Model
Rong Ma, T. Tony Cai, Hongzhe Li
http://arxiv.org/abs/1911.12516v1
• [physics.ao-ph]Detecting anthropogenic cloud perturbations with deep learning
Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony Caterini, Dino Sejdinovic, Philip Stier
http://arxiv.org/abs/1911.13061v1
• [physics.comp-ph]Progressive-Growing of Generative Adversarial Networks for Metasurface Optimization
Fufang Wen, Jiaqi Jiang, Jonathan A. Fan
http://arxiv.org/abs/1911.13029v1
• [q-fin.ST]Refinements of Barndorff-Nielsen and Shephard model: an analysis of crude oil price with machine learning
Indranil SenGupta, William Nganje, Erik Hanson
http://arxiv.org/abs/1911.13300v1
• [stat.AP]Application of Time Series Analysis to Traffic Accidents in Los Angeles
Qinghao Ye, Kaiyuan Hu, Yizhe Wang
http://arxiv.org/abs/1911.12813v1
• [stat.AP]Comparative Study of Differentially Private Synthetic Data Algorithms and Evaluation Standards
Claire McKay Bowen, Joshua Snoke
http://arxiv.org/abs/1911.12704v1
• [stat.AP]Modelling dependence within and across run-off triangles for claims reserving
Luis E. Nieto-Barajas, Rodrigo S. Targino
http://arxiv.org/abs/1911.12405v1
• [stat.AP]Predicting wave heights for marine design by prioritizing extreme events in a global model
Andreas F. Haselsteiner, Klaus-Dieter Thoben
http://arxiv.org/abs/1911.12835v1
• [stat.AP]Qini-based Uplift Regression
Mouloud Belbahri, Alejandro Murua, Olivier Gandouet, Vahid Partovi Nia
http://arxiv.org/abs/1911.12474v1
• [stat.ME]A review and evaluation of standard methods to handle missing data on time-varying confounders in marginal structural models
Clemence Leyrat, James R Carpenter, Sebastien Bailly, Elizabeth J Willamson
http://arxiv.org/abs/1911.12624v1
• [stat.ME]Causal inference of hazard ratio based on propensity score matching
Shuhan Tang, Shu Yang, Tongrong Wang, Zhanglin Cui, Li Li, Douglas E. Faries
http://arxiv.org/abs/1911.12430v1
• [stat.ME]Minkowski distances and standardisation for clustering and classification of high dimensional data
Christian Hennig
http://arxiv.org/abs/1911.13272v1
• [stat.ME]Modeling Spectral Properties in Stationary Processes of Varying Dimensions with Applications to Brain Local Field Potential Signals
Raanju Ragavendar Sundararajan, Ron D. Frostig, Hernando Ombao
http://arxiv.org/abs/1911.12295v2
• [stat.ME]Modelling publication bias and p-hacking
Jonas Moss, Riccardo De Bin
http://arxiv.org/abs/1911.12445v1
• [stat.ME]Novel Non-Negative Variance Estimator for (Modified) Within-Cluster Resampling
Daniel Xu, Pamela Shaw, Ian Barnett
http://arxiv.org/abs/1911.12882v1
• [stat.ML]A Bayesian Dynamic Multilayered Block Network Model
Hector Rodriguez-Deniz, Mattias Villani, Augusto Voltes-Dorta
http://arxiv.org/abs/1911.13136v1
• [stat.ML]Distributed estimation of principal support vector machines for sufficient dimension reduction
Jun Jin, Chao Ying, Zhou Yu
http://arxiv.org/abs/1911.12732v1
• [stat.ML]Embedding and learning with signatures
Adeline Fermanian
http://arxiv.org/abs/1911.13211v1
• [stat.ML]Link Prediction in the Stochastic Block Model with Outliers
Solenne Gaucher, Olga Klopp, Geneviève Robin
http://arxiv.org/abs/1911.13122v1
• [stat.ML]Spike-and-wave epileptiform discharge pattern detection based on Kendall’s Tau-b coefficient
Antonio Quintero-Rincón, Catalina Carenzo, Joaquín Ems, Lourdes Hirschson, Valeria Muro, Carlos D’Giano
http://arxiv.org/abs/1911.13018v1
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