cs.AI - 人工智能
cs.CE - 计算工程、 金融和科学 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.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.GR - 计算机图形学 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 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习 stat.OT - 其他统计学
• [cs.AI]Challenges of Human-Aware AI Systems
• [cs.AI]On the Relation between Weak Completion Semantics and Answer Set Semantics
• [cs.AI]The NAI Suite — Drafting and Reasoning over Legal Texts
• [cs.CE]Exploring the fitness landscape of a realistic turbofan rotor blade optimization
• [cs.CL]A Probabilistic Framework for Learning Domain Specific Hierarchical Word Embeddings
• [cs.CL]Answering Complex Open-domain Questions Through Iterative Query Generation
• [cs.CL]BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance
• [cs.CL]Bridging the Knowledge Gap: Enhancing Question Answering with World and Domain Knowledge
• [cs.CL]Comprehend Medical: a Named Entity Recognition and Relationship Extraction Web Service
• [cs.CL]Content Enhanced BERT-based Text-to-SQL Generation
• [cs.CL]Efficiency through Auto-Sizing: Notre Dame NLP’s Submission to the WNGT 2019 Efficiency Task
• [cs.CL]Evolution of transfer learning in natural language processing
• [cs.CL]FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
• [cs.CL]Fine-grained evaluation of German-English Machine Translation based on a Test Suite
• [cs.CL]Fine-grained evaluation of Quality Estimation for Machine translation based on a linguistically-motivated Test Suite
• [cs.CL]Generating Challenge Datasets for Task-Oriented Conversational Agents through Self-Play
• [cs.CL]Imperial College London Submission to VATEX Video Captioning Task
• [cs.CL]Iterative Delexicalization for Improved Spoken Language Understanding
• [cs.CL]Joint Learning of Word and Label Embeddings for Sequence Labelling in Spoken Language Understanding
• [cs.CL]Lead2Gold: Towards exploiting the full potential of noisy transcriptions for speech recognition
• [cs.CL]Linguistic evaluation of German-English Machine Translation using a Test Suite
• [cs.CL]MLQA: Evaluating Cross-lingual Extractive Question Answering
• [cs.CL]Meemi: Finding the Middle Ground in Cross-lingual Word Embeddings
• [cs.CL]Mix-review: Alleviate Forgetting in the Pretrain-Finetune Framework for Neural Language Generation Models
• [cs.CL]Unsupervised Question Answering for Fact-Checking
• [cs.CL]Using Whole Document Context in Neural Machine Translation
• [cs.CL]Why can’t memory networks read effectively?
• [cs.CR]Statically Detecting Vulnerabilities by Processing Programming Languages as Natural Languages
• [cs.CV]A Generalized and Robust Method Towards Practical Gaze Estimation on Smart Phone
• [cs.CV]Aerial Images Processing for Car Detection using Convolutional Neural Networks: Comparison between Faster R-CNN and YoloV3
• [cs.CV]Attention Network Robustification for Person ReID
• [cs.CV]Conservation AI: Live Stream Analysis for the Detection of Endangered Species Using Convolutional Neural Networks and Drone Technology
• [cs.CV]DeepErase: Weakly Supervised Ink Artifact Removal in Document Text Images
• [cs.CV]Design of a Simple Orthogonal Multiwavelet Filter by Matrix Spectral Factorization
• [cs.CV]Generative Modeling for Small-Data Object Detection
• [cs.CV]Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks
• [cs.CV]LOST: A flexible framework for semi-automatic image annotation
• [cs.CV]Large-Scale Landslides Detection from Satellite Images with Incomplete Labels
• [cs.CV]Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis
• [cs.CV]Offline handwritten mathematical symbol recognition utilising deep learning
• [cs.CV]On adversarial patches: real-world attack on ArcFace-100 face recognition system
• [cs.CV]Segmentation Criteria in the Problem of Porosity Determination based on CT Scans
• [cs.CV]Transform the Set: Memory Attentive Generation of Guided and Unguided Image Collages
• [cs.CV]Understanding Misclassifications by Attributes
• [cs.CY]On Constructing a Knowledge Base of Chinese Criminal Cases
• [cs.DB]Efficiently Embedding Dynamic Knowledge Graphs
• [cs.DB]Similarity Driven Approximation for Text Analytics
• [cs.DC]A High-Throughput Solver for Marginalized Graph Kernels on GPU
• [cs.DC]A new CP-approach for a parallel machine scheduling problem with time constraints on machine qualifications
• [cs.DC]Alleviating Bottlenecks for DNN Execution on GPUs via Opportunistic Computing
• [cs.DC]Consentio: Managing Consent to Data Access using Permissioned Blockchains
• [cs.DC]GraVF-M: Graph Processing System Generation for Multi-FPGA Platforms
• [cs.DC]Hyper: Distributed Cloud Processing for Large-Scale Deep Learning Tasks
• [cs.DC]In Search of a Fast and Efficient Serverless DAG Engine
• [cs.DC]JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training
• [cs.DC]SCALPEL3: a scalable open-source library for healthcare claims databases
• [cs.GR]Animating Landscape: Self-Supervised Learning of Decoupled Motion and Appearance for Single-Image Video Synthesis
• [cs.HC]Designing Style Matching Conversational Agents
• [cs.HC]Gaze Gestures and Their Applications in human-computer interaction with a head-mounted display
• [cs.HC]Using learning analytics to provide personalized recommendations for finding peers
• [cs.IR]NLPExplorer: Exploring the Universe of NLP Papers
• [cs.IR]Rule based Approach for Word Normalization by resolving Transcription Ambiguity in Transliterated Search Queries
• [cs.IR]The Impact of Popularity Bias on Fairness and Calibration in Recommendation
• [cs.IT]An Overview of Capacity Results for Synchronization Channels
• [cs.IT]Covariance Matrix Estimation from Correlated Sub-Gaussian Samples
• [cs.IT]Covert Wireless Communication in Presence of a Multi-Antenna Adversary and Delay Constraints
• [cs.IT]Long Optimal LRC Codes with Unbounded Localities and Unbounded Minimum Distances
• [cs.IT]Machine Learning for Error Correction with Natural Redundancy
• [cs.IT]Universal Bounds for Size and Energy of Codes of Given Minimum and Maximum Distances
• [cs.LG]A Notion of Harmonic Clustering in Simplicial Complexes
• [cs.LG]Adaptive Exploration in Linear Contextual Bandit
• [cs.LG]Adaptive Trade-Offs in Off-Policy Learning
• [cs.LG]An Exponential Learning Rate Schedule for Deep Learning
• [cs.LG]Audio-Conditioned U-Net for Position Estimation in Full Sheet Images
• [cs.LG]Conditional Importance Sampling for Off-Policy Learning
• [cs.LG]Conditional Invertible Flow for Point Cloud Generation
• [cs.LG]Conditional Learning of Fair Representations
• [cs.LG]Consistency-Based Semi-Supervised Active Learning: Towards Minimizing Labeling Cost
• [cs.LG]Conversion Rate Prediction via Post-Click Behaviour Modeling
• [cs.LG]Creativity in Robot Manipulation with Deep Reinforcement Learning
• [cs.LG]Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation
• [cs.LG]Embodiment dictates learnability in neural controllers
• [cs.LG]Explaining with Impact: A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms
• [cs.LG]FISHDBC: Flexible, Incremental, Scalable, Hierarchical Density-Based Clustering for Arbitrary Data and Distance
• [cs.LG]HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories
• [cs.LG]Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation
• [cs.LG]How a minimal learning agent can infer the existence of unobserved variables in a complex environment
• [cs.LG]MAVEN: Multi-Agent Variational Exploration
• [cs.LG]MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design
• [cs.LG]Model-Agnostic Meta-Learning using Runge-Kutta Methods
• [cs.LG]Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
• [cs.LG]Multiclass spectral feature scaling method for dimensionality reduction
• [cs.LG]On Learning Paradigms for the Travelling Salesman Problem
• [cs.LG]On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
• [cs.LG]On the Global Optima of Kernelized Adversarial Representation Learning
• [cs.LG]Optimising Individual-Treatment-Effect Using Bandits
• [cs.LG]Orthogonal Gradient Descent for Continual Learning
• [cs.LG]Reduced-Order Modeling of Deep Neural Networks
• [cs.LG]Reinforcement Learning for Robotic Manipulation using Simulated Locomotion Demonstrations
• [cs.LG]Root Mean Square Layer Normalization
• [cs.LG]Rugby-Bot: Utilizing Multi-Task Learning & Fine-Grained Features for Rugby League Analysis
• [cs.LG]SGD Learns One-Layer Networks in WGANs
• [cs.LG]Soft Actor-Critic for Discrete Action Settings
• [cs.LG]Solving Rubik’s Cube with a Robot Hand
• [cs.LG]Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
• [cs.LG]Transfer Learning for Algorithm Recommendation
• [cs.LG]Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs
• [cs.MM]A Study of Annotation and Alignment Accuracy for Performance Comparison in Complex Orchestral Music
• [cs.NE]AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation
• [cs.NE]Negatively Correlated Search as a Parallel Exploration Search Strategy
• [cs.NE]On-chip Few-shot Learning with Surrogate Gradient Descent on a Neuromorphic Processor
• [cs.NE]Structural Analysis of Sparse Neural Networks
• [cs.NE]The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks
• [cs.NI]Sub-Channel Allocation for Device-to-Device Underlaying Full-Duplex mmWave Small Cells using Coalition Formation Games
• [cs.RO]Autonomous Aerial Cinematography In Unstructured Environments With Learned Artistic Decision-Making
• [cs.RO]Explainable Semantic Mapping for First Responders
• [cs.RO]FlowNorm: A Learning-based Method for Increasing Convergence Range of Direct Alignment
• [cs.RO]Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation
• [cs.SI]Beyond Fortune 500: Women in a Global Network of Directors
• [cs.SI]Design method of Temporary Horizontal Visibility Graph for information sources impact network
• [cs.SI]Eva: Attribute-Aware Network Segmentation
• [cs.SI]SGP: Spotting Groups Polluting the Online Political Discourse
• [cs.SI]Tutorial on NLP-Inspired Network Embedding
• [econ.EM]Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition
• [eess.AS]Analyzing Large Receptive Field Convolutional Networks for Distant Speech Recognition
• [eess.AS]MIMO-SPEECH: End-to-End Multi-Channel Multi-Speaker Speech Recognition
• [eess.AS]Transformer ASR with Contextual Block Processing
• [eess.IV]A Survey on Recent Advancements for AI Enabled Radiomics in Neuro-Oncology
• [eess.IV]Wasserstein GANs for MR Imaging: from Paired to Unpaired Training
• [eess.SP]Joint Transmit and Reflective Beamforming Design for IRS-Assisted Multiuser MISO SWIPT Systems
• [eess.SP]Neural Network Design for Energy-Autonomous AI Applications using Temporal Encoding
• [eess.SP]Reconfigurable Intelligent Surface Empowered Downlink Non-Orthogonal Multiple Access
• [eess.SP]Self-supervised Learning for ECG-based Emotion Recognition
• [eess.SP]Variance State Propagation for Structured Sparse Bayesian Learning
• [eess.SY]Decentralized Heading Control with Rate Constraints using Pulse-Coupled Oscillators
• [math.OC]Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games
• [math.OC]Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize
• [math.PR]Representations of Hermite processes using local time of intersecting stationary stable regenerative sets
• [math.ST]Alternatives of the EM Algorithm for Estimating the Parameters of the Student-t Distribution
• [math.ST]Bayesian Inverse Problems with Heterogeneous Variance
• [math.ST]Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem
• [math.ST]IRLS for Sparse Recovery Revisited: Examples of Failure and a Remedy
• [math.ST]Lomax distribution and asymptotical ML estimations based on record values for probability density function and cumulative distribution function
• [math.ST]Matrix Means and a Novel High-Dimensional Shrinkage Phenomenon
• [math.ST]Splinets — efficient orthonormalization of the B-splines
• [math.ST]Stochastic Orderings of Multivariate Elliptical Distributions
• [q-bio.QM]Automated Detection of Left Ventricle in Arterial Input Function Images for Inline Perfusion Mapping using Deep Learning: A study of 15,000 Patients
• [quant-ph]Modeling Sequences with Quantum States: A Look Under the Hood
• [stat.AP]Estimating FARIMA models with uncorrelated but non-independent error terms
• [stat.AP]Identifying relationships between cognitive processes across tasks, contexts, and time
• [stat.AP]Lurking Inferential Monsters? Quantifying bias in non-experimental evaluations of school programs
• [stat.AP]Psychometric Analysis of Forensic Examiner Behavior
• [stat.AP]Sampling by Reversing The Landmarking Process
• [stat.ME]A Semi-Parametric Estimation Method for the Quantile Spectrum with an Application to Earthquake Classification Using Convolutional Neural Network
• [stat.ME]A new INARMA(1, 1) model with Poisson marginals
• [stat.ME]An Instrumental Variable Estimator for Mixed Indicators: Analytic Derivatives and Alternative Parameterizations
• [stat.ME]Bayesian variable selection in hierarchical difference-in-differences models
• [stat.ME]Conjugate Bayesian Unit-level Modeling of Count Data Under Informative Sampling Designs
• [stat.ME]Discussion of “The Blessings of Multiple Causes” by Wang and Blei
• [stat.ME]Multivariate Forecasting Evaluation: On Sensitive and Strictly Proper Scoring Rules
• [stat.ME]On the Interplay Between Exposure Misclassification and Informative Cluster Size
• [stat.ML]Constrained Bayesian Optimization with Max-Value Entropy Search
• [stat.ML]Excess risk bounds in robust empirical risk minimization
• [stat.ML]Generative Learning of Counterfactual for Synthetic Control Applications in Econometrics
• [stat.ML]Sparse Gaussian Process Regression Beyond Variational Inference
• [stat.ML]The Blessings of Multiple Causes: A Reply to Ogburn et al. (2019)
• [stat.ML]The Rényi Gaussian Process
• [stat.ML]Unsupervised Domain Adaptation Meets Offline Recommender Learning
• [stat.OT]\texttt{code::proof}: Prepare for \emph{most} weather conditions
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• [cs.AI]Challenges of Human-Aware AI Systems
Subbarao Kambhampati
http://arxiv.org/abs/1910.07089v1
• [cs.AI]On the Relation between Weak Completion Semantics and Answer Set Semantics
Emmanuelle-Anna Dietz Saldanha, Jorge Fandinno
http://arxiv.org/abs/1910.07278v1
• [cs.AI]The NAI Suite — Drafting and Reasoning over Legal Texts
Tomer Libal, Alexander Steen
http://arxiv.org/abs/1910.07004v1
• [cs.CE]Exploring the fitness landscape of a realistic turbofan rotor blade optimization
Jakub Kmec, Sebastian Schmitt
http://arxiv.org/abs/1910.07268v1
• [cs.CL]A Probabilistic Framework for Learning Domain Specific Hierarchical Word Embeddings
Lahari Poddar, Gyorgy Szarvas, Lea Frermann
http://arxiv.org/abs/1910.07333v1
• [cs.CL]Answering Complex Open-domain Questions Through Iterative Query Generation
Peng Qi, Xiaowen Lin, Leo Mehr, Zijian Wang, Christopher D. Manning
http://arxiv.org/abs/1910.07000v1
• [cs.CL]BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance
Timo Schick, Hinrich Schütze
http://arxiv.org/abs/1910.07181v1
• [cs.CL]Bridging the Knowledge Gap: Enhancing Question Answering with World and Domain Knowledge
Travis R. Goodwin, Dina Demner-Fushman
http://arxiv.org/abs/1910.07429v1
• [cs.CL]Comprehend Medical: a Named Entity Recognition and Relationship Extraction Web Service
Parminder Bhatia, Busra Celikkaya, Mohammed Khalilia, Selvan Senthivel
http://arxiv.org/abs/1910.07419v1
• [cs.CL]Content Enhanced BERT-based Text-to-SQL Generation
Tong Guo, Huilin Gao
http://arxiv.org/abs/1910.07179v1
• [cs.CL]Efficiency through Auto-Sizing: Notre Dame NLP’s Submission to the WNGT 2019 Efficiency Task
Kenton Murray, Brian DuSell, David Chiang
http://arxiv.org/abs/1910.07134v1
• [cs.CL]Evolution of transfer learning in natural language processing
Aditya Malte, Pratik Ratadiya
http://arxiv.org/abs/1910.07370v1
• [cs.CL]FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou
http://arxiv.org/abs/1910.07124v1
• [cs.CL]Fine-grained evaluation of German-English Machine Translation based on a Test Suite
Vivien Macketanz, Eleftherios Avramidis, Aljoscha Burchardt, Hans Uszkoreit
http://arxiv.org/abs/1910.07460v1
• [cs.CL]Fine-grained evaluation of Quality Estimation for Machine translation based on a linguistically-motivated Test Suite
Avramidis Eleftherios, Vivien Macketanz, Arle Lommel, Hans Uszkoreit
http://arxiv.org/abs/1910.07468v1
• [cs.CL]Generating Challenge Datasets for Task-Oriented Conversational Agents through Self-Play
Sourabh Majumdar, Serra Sinem Tekiroglu, Marco Guerini
http://arxiv.org/abs/1910.07357v1
• [cs.CL]Imperial College London Submission to VATEX Video Captioning Task
Ozan Caglayan, Zixiu Wu, Pranava Madhyastha, Josiah Wang, Lucia Specia
http://arxiv.org/abs/1910.07482v1
• [cs.CL]Iterative Delexicalization for Improved Spoken Language Understanding
Avik Ray, Yilin Shen, Hongxia Jin
http://arxiv.org/abs/1910.07060v1
• [cs.CL]Joint Learning of Word and Label Embeddings for Sequence Labelling in Spoken Language Understanding
Jiewen Wu, Luis Fernando D’Haro, Nancy F. Chen, Pavitra Krishnaswamy, Rafael E. Banchs
http://arxiv.org/abs/1910.07150v1
• [cs.CL]Lead2Gold: Towards exploiting the full potential of noisy transcriptions for speech recognition
Adrien Dufraux, Emmanuel Vincent, Awni Hannun, Armelle Brun, Matthijs Douze
http://arxiv.org/abs/1910.07323v1
• [cs.CL]Linguistic evaluation of German-English Machine Translation using a Test Suite
Eleftherios Avramidis, Vivien Macketanz, Ursula Strohriegel, Hans Uszkoreit
http://arxiv.org/abs/1910.07457v1
• [cs.CL]MLQA: Evaluating Cross-lingual Extractive Question Answering
Patrick Lewis, Barlas Oğuz, Ruty Rinott, Sebastian Riedel, Holger Schwenk
http://arxiv.org/abs/1910.07475v1
• [cs.CL]Meemi: Finding the Middle Ground in Cross-lingual Word Embeddings
Yerai Doval, Jose Camacho-Collados, Luis Espinosa-Anke, Steven Schockaert
http://arxiv.org/abs/1910.07221v1
• [cs.CL]Mix-review: Alleviate Forgetting in the Pretrain-Finetune Framework for Neural Language Generation Models
Tianxing He, Jun Liu, Kyunghyun Cho, Myle Ott, Bing Liu, James Glass, Fuchun Peng
http://arxiv.org/abs/1910.07117v1
• [cs.CL]Unsupervised Question Answering for Fact-Checking
Mayank Jobanputra
http://arxiv.org/abs/1910.07154v1
• [cs.CL]Using Whole Document Context in Neural Machine Translation
Valentin Macé, Christophe Servan
http://arxiv.org/abs/1910.07481v1
• [cs.CL]Why can’t memory networks read effectively?
Simon Šuster, Madhumita Sushil, Walter Daelemans
http://arxiv.org/abs/1910.07350v1
• [cs.CR]Statically Detecting Vulnerabilities by Processing Programming Languages as Natural Languages
Ibéria Medeiros, Nuno Neves, Miguel Correia
http://arxiv.org/abs/1910.06826v1
• [cs.CV]A Generalized and Robust Method Towards Practical Gaze Estimation on Smart Phone
Tianchu Guo, Yongchao Liu, Hui Zhang, Xiabing Liu, Youngjun Kwak, Byung In Yoo, Jae-Joon Han, Changkyu Choi
http://arxiv.org/abs/1910.07331v1
• [cs.CV]Aerial Images Processing for Car Detection using Convolutional Neural Networks: Comparison between Faster R-CNN and YoloV3
Adel Ammar, Anis Koubaa, Mohanned Ahmed, Abdulrahman Saad
http://arxiv.org/abs/1910.07234v1
• [cs.CV]Attention Network Robustification for Person ReID
Hussam Lawen, Avi Ben-Cohen, Matan Protter, Itamar Friedman, Lihi Zelnik-Manor
http://arxiv.org/abs/1910.07038v1
• [cs.CV]Conservation AI: Live Stream Analysis for the Detection of Endangered Species Using Convolutional Neural Networks and Drone Technology
C. Chalmers, P. Fergus, Serge Wich, Aday Curbelo Montanez
http://arxiv.org/abs/1910.07360v1
• [cs.CV]DeepErase: Weakly Supervised Ink Artifact Removal in Document Text Images
W. Ronny Huang, Yike Qi, Qianqian Li, Jonathan Degange
http://arxiv.org/abs/1910.07070v1
• [cs.CV]Design of a Simple Orthogonal Multiwavelet Filter by Matrix Spectral Factorization
Vasil Kolev, Todor Cooklev, Fritz Keinert
http://arxiv.org/abs/1910.07133v1
• [cs.CV]Generative Modeling for Small-Data Object Detection
Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li
http://arxiv.org/abs/1910.07169v1
• [cs.CV]Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks
Cristina González-Gonzalo, Bart Liefers, Bram van Ginneken, Clara I. Sánchez
http://arxiv.org/abs/1910.07373v1
• [cs.CV]LOST: A flexible framework for semi-automatic image annotation
Jonas Jäger, Gereon Reus, Joachim Denzler, Viviane Wolff, Klaus Fricke-Neuderth
http://arxiv.org/abs/1910.07486v1
• [cs.CV]Large-Scale Landslides Detection from Satellite Images with Incomplete Labels
Masanari Kimura
http://arxiv.org/abs/1910.07129v1
• [cs.CV]Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis
Xihui Liu, Guojun Yin, Jing Shao, Xiaogang Wang, Hongsheng Li
http://arxiv.org/abs/1910.06809v2
• [cs.CV]Offline handwritten mathematical symbol recognition utilising deep learning
Azadeh Nazemi, Niloofar Tavakolian, Donal Fitzpatrick, Chandrik a Fernando, Ching Y. Suen
http://arxiv.org/abs/1910.07395v1
• [cs.CV]On adversarial patches: real-world attack on ArcFace-100 face recognition system
Mikhail Pautov, Grigorii Melnikov, Edgar Kaziakhmedov, Klim Kireev, Aleksandr Petiushko
http://arxiv.org/abs/1910.07067v1
• [cs.CV]Segmentation Criteria in the Problem of Porosity Determination based on CT Scans
V. Kokhan, M. Grigoriev, A. Buzmakov, V. Uvarov, A. Ingacheva, E. Shvets, M. Chukalina
http://arxiv.org/abs/1910.07328v1
• [cs.CV]Transform the Set: Memory Attentive Generation of Guided and Unguided Image Collages
Nikolay Jetchev, Urs Bergmann, Gökhan Yildirim
http://arxiv.org/abs/1910.07236v1
• [cs.CV]Understanding Misclassifications by Attributes
Sadaf Gulshad, Zeynep Akata, Jan Hendrik Metzen, Arnold Smeulders
http://arxiv.org/abs/1910.07416v1
• [cs.CY]On Constructing a Knowledge Base of Chinese Criminal Cases
Xiaohan Wu, Benjamin L. Liebman, Rachel E. Stern, Margaret E. Roberts, Amarnath Gupta
http://arxiv.org/abs/1910.07494v1
• [cs.DB]Efficiently Embedding Dynamic Knowledge Graphs
Tianxing Wu, Arijit Khan, Huan Gao, Cheng Li
http://arxiv.org/abs/1910.06708v1
• [cs.DB]Similarity Driven Approximation for Text Analytics
Guangyan Hu, Yongfeng Zhang, Sandro Rigo, Thu D. Nguyen
http://arxiv.org/abs/1910.07144v1
• [cs.DC]A High-Throughput Solver for Marginalized Graph Kernels on GPU
Yu-Hang Tang, Oguz Selvitopi, Doru Popovici, Aydın Buluç
http://arxiv.org/abs/1910.06310v2
• [cs.DC]A new CP-approach for a parallel machine scheduling problem with time constraints on machine qualifications
Arnaud Malapert, Margaux Nattaf
http://arxiv.org/abs/1910.07203v1
• [cs.DC]Alleviating Bottlenecks for DNN Execution on GPUs via Opportunistic Computing
Xianwei Cheng, Hui Zhao, Mahmut Kandemir, Saraju Mohanty, Beilei Jiang
http://arxiv.org/abs/1910.07055v1
• [cs.DC]Consentio: Managing Consent to Data Access using Permissioned Blockchains
Rishav Raj Agarwal, Dhruv Kumar, Lukasz Golab, Srinivasan Keshav
http://arxiv.org/abs/1910.07110v1
• [cs.DC]GraVF-M: Graph Processing System Generation for Multi-FPGA Platforms
Nina Engelhardt, Hayden K. -H. So
http://arxiv.org/abs/1910.07408v1
• [cs.DC]Hyper: Distributed Cloud Processing for Large-Scale Deep Learning Tasks
Davit Buniatyan
http://arxiv.org/abs/1910.07172v1
• [cs.DC]In Search of a Fast and Efficient Serverless DAG Engine
Benjamin Carver, Jingyuan Zhang, Ao Wang, Yue Cheng
http://arxiv.org/abs/1910.05896v2
• [cs.DC]JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training
José Á. Morell, Andrés Camero, Enrique Alba
http://arxiv.org/abs/1910.07402v1
• [cs.DC]SCALPEL3: a scalable open-source library for healthcare claims databases
Emmanuel Bacry, Stéphane Gaïffas, Fanny Leroy, Maryan Morel, Dinh Phong Nguyen, Youcef Sebiat, Dian Sun
http://arxiv.org/abs/1910.07045v1
• [cs.GR]Animating Landscape: Self-Supervised Learning of Decoupled Motion and Appearance for Single-Image Video Synthesis
Yuki Endo, Yoshihiro Kanamori, Shigeru Kuriyama
http://arxiv.org/abs/1910.07192v1
• [cs.HC]Designing Style Matching Conversational Agents
Deepali Aneja, Rens Hoegen, Daniel McDuff, Mary Czerwinski
http://arxiv.org/abs/1910.07514v1
• [cs.HC]Gaze Gestures and Their Applications in human-computer interaction with a head-mounted display
W. X. Chen, X. Y. Cui, J. Zheng, J. M. Zhang, S. Chen, Y. D. Yao
http://arxiv.org/abs/1910.07428v1
• [cs.HC]Using learning analytics to provide personalized recommendations for finding peers
Irene-Angelica Chounta
http://arxiv.org/abs/1910.07381v1
• [cs.IR]NLPExplorer: Exploring the Universe of NLP Papers
Monarch Parmar, Naman Jain, Pranjali Jain, P Jayakrishna Sahit, Soham Pachpande, Shruti Singh, Mayank Singh
http://arxiv.org/abs/1910.07351v1
• [cs.IR]Rule based Approach for Word Normalization by resolving Transcription Ambiguity in Transliterated Search Queries
Varsha Pathak, Manish Joshi
http://arxiv.org/abs/1910.07233v1
• [cs.IR]The Impact of Popularity Bias on Fairness and Calibration in Recommendation
Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher
http://arxiv.org/abs/1910.05755v3
• [cs.IT]An Overview of Capacity Results for Synchronization Channels
Mahdi Cheraghchi, João Ribeiro
http://arxiv.org/abs/1910.07199v1
• [cs.IT]Covariance Matrix Estimation from Correlated Sub-Gaussian Samples
Xu Zhang, Wei Cui, Yulong Liu
http://arxiv.org/abs/1910.07183v1
• [cs.IT]Covert Wireless Communication in Presence of a Multi-Antenna Adversary and Delay Constraints
Khurram Shahzad, Xiangyun Zhou, Shihao Yan
http://arxiv.org/abs/1910.07246v1
• [cs.IT]Long Optimal LRC Codes with Unbounded Localities and Unbounded Minimum Distances
Hao Chen, Jian Weng, Weiqi Luo
http://arxiv.org/abs/1910.07267v1
• [cs.IT]Machine Learning for Error Correction with Natural Redundancy
Pulakesh Upadhyaya, Anxiao Jiang
http://arxiv.org/abs/1910.07420v1
• [cs.IT]Universal Bounds for Size and Energy of Codes of Given Minimum and Maximum Distances
Peter Boyvalenkov, Peter Dragnev, Douglas Hardin, Edward Saff, Maya Stoyanova
http://arxiv.org/abs/1910.07274v1
• [cs.LG]A Notion of Harmonic Clustering in Simplicial Complexes
Stefania Ebli, Gard Spreemann
http://arxiv.org/abs/1910.07247v1
• [cs.LG]Adaptive Exploration in Linear Contextual Bandit
Botao Hao, Tor Lattimore, Csaba Szepesvari
http://arxiv.org/abs/1910.06996v1
• [cs.LG]Adaptive Trade-Offs in Off-Policy Learning
Mark Rowland, Will Dabney, Rémi Munos
http://arxiv.org/abs/1910.07478v1
• [cs.LG]An Exponential Learning Rate Schedule for Deep Learning
Zhiyuan Li, Sanjeev Arora
http://arxiv.org/abs/1910.07454v1
• [cs.LG]Audio-Conditioned U-Net for Position Estimation in Full Sheet Images
Florian Henkel, Rainer Kelz, Gerhard Widmer
http://arxiv.org/abs/1910.07254v1
• [cs.LG]Conditional Importance Sampling for Off-Policy Learning
Mark Rowland, Anna Harutyunyan, Hado van Hasselt, Diana Borsa, Tom Schaul, Rémi Munos, Will Dabney
http://arxiv.org/abs/1910.07479v1
• [cs.LG]Conditional Invertible Flow for Point Cloud Generation
Michał Stypułkowski, Maciej Zamorski, Maciej Zięba, Jan Chorowski
http://arxiv.org/abs/1910.07344v1
• [cs.LG]Conditional Learning of Fair Representations
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
http://arxiv.org/abs/1910.07162v1
• [cs.LG]Consistency-Based Semi-Supervised Active Learning: Towards Minimizing Labeling Cost
Mingfei Gao, Zizhao Zhang, Guo Yu, Sercan O. Arik, Larry S. Davis, Tomas Pfister
http://arxiv.org/abs/1910.07153v1
• [cs.LG]Conversion Rate Prediction via Post-Click Behaviour Modeling
Hong Wen, Jing Zhang, Yuan Wang, Wentian Bao, Quan Lin, Keping Yang
http://arxiv.org/abs/1910.07099v1
• [cs.LG]Creativity in Robot Manipulation with Deep Reinforcement Learning
Juan Carlos Vargas, Malhar Bhoite, Amir Barati Farimani
http://arxiv.org/abs/1910.07459v1
• [cs.LG]Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation
Ziyang Tang, Yihao Feng, Lihong Li, Dengyong Zhou, Qiang Liu
http://arxiv.org/abs/1910.07186v1
• [cs.LG]Embodiment dictates learnability in neural controllers
Joshua Powers, Ryan Grindle, Sam Kriegman, Lapo Frati, Nick Cheney, Josh Bongard
http://arxiv.org/abs/1910.07487v1
• [cs.LG]Explaining with Impact: A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms
Zhong Qiu Lin, Mohammad Javad Shafiee, Stanislav Bochkarev, Michael St. Jules, Xiao Yu Wang, Alexander Wong
http://arxiv.org/abs/1910.07387v1
• [cs.LG]FISHDBC: Flexible, Incremental, Scalable, Hierarchical Density-Based Clustering for Arbitrary Data and Distance
Matteo Dell’Amico
http://arxiv.org/abs/1910.07283v1
• [cs.LG]HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories
Yu Zhang, Frank F. Xu, Sha Li, Yu Meng, Xuan Wang, Qi Li, Jiawei Han
http://arxiv.org/abs/1910.07115v1
• [cs.LG]Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation
Elisa Oostwal, Michiel Straat, Michael Biehl
http://arxiv.org/abs/1910.07476v1
• [cs.LG]How a minimal learning agent can infer the existence of unobserved variables in a complex environment
Katja Ried, Benjamin Eva, Thomas Müller, Hans J. Briegel
http://arxiv.org/abs/1910.06985v1
• [cs.LG]MAVEN: Multi-Agent Variational Exploration
Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan, Shimon Whiteson
http://arxiv.org/abs/1910.07483v1
• [cs.LG]MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design
Mayoore S. Jaiswal, Bumboo Kang, Jinho Lee, Minsik Cho
http://arxiv.org/abs/1910.07042v1
• [cs.LG]Model-Agnostic Meta-Learning using Runge-Kutta Methods
Daniel Jiwoong Im, Yibo Jiang, Nakul Verma
http://arxiv.org/abs/1910.07368v1
• [cs.LG]Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Hiteshi Sharma, Rahul Jain
http://arxiv.org/abs/1910.07072v1
• [cs.LG]Multiclass spectral feature scaling method for dimensionality reduction
Momo Matsuda, Keiichi Morikuni, Akira Imakura, Xiucai Ye, Tetsuya Sakurai
http://arxiv.org/abs/1910.07174v1
• [cs.LG]On Learning Paradigms for the Travelling Salesman Problem
Chaitanya K. Joshi, Thomas Laurent, Xavier Bresson
http://arxiv.org/abs/1910.07210v1
• [cs.LG]On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
Yuanhao Wang, Guodong Zhang, Jimmy Ba
http://arxiv.org/abs/1910.07512v1
• [cs.LG]On the Global Optima of Kernelized Adversarial Representation Learning
Bashir Sadeghi, Runyi Yu, Vishnu Naresh Boddeti
http://arxiv.org/abs/1910.07423v1
• [cs.LG]Optimising Individual-Treatment-Effect Using Bandits
Jeroen Berrevoets, Sam Verboven, Wouter Verbeke
http://arxiv.org/abs/1910.07265v1
• [cs.LG]Orthogonal Gradient Descent for Continual Learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li
http://arxiv.org/abs/1910.07104v1
• [cs.LG]Reduced-Order Modeling of Deep Neural Networks
Talgat Daulbaev, Julia Gusak, Evgeny Ponomarev, Andrzej Cichocki, Ivan Oseledets
http://arxiv.org/abs/1910.06995v1
• [cs.LG]Reinforcement Learning for Robotic Manipulation using Simulated Locomotion Demonstrations
Ozsel Kilinc, Yang Hu, Giovanni Montana
http://arxiv.org/abs/1910.07294v1
• [cs.LG]Root Mean Square Layer Normalization
Biao Zhang, Rico Sennrich
http://arxiv.org/abs/1910.07467v1
• [cs.LG]Rugby-Bot: Utilizing Multi-Task Learning & Fine-Grained Features for Rugby League Analysis
Matthew Holbrook, Jennifer Hobbs, Patrick Lucey
http://arxiv.org/abs/1910.07410v1
• [cs.LG]SGD Learns One-Layer Networks in WGANs
Qi Lei, Jason D. Lee, Alexandros G. Dimakis, Constantinos Daskalakis
http://arxiv.org/abs/1910.07030v1
• [cs.LG]Soft Actor-Critic for Discrete Action Settings
Petros Christodoulou
http://arxiv.org/abs/1910.07207v1
• [cs.LG]Solving Rubik’s Cube with a Robot Hand
OpenAI, Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, Jonas Schneider, Nikolas Tezak, Jerry Tworek, Peter Welinder, Lilian Weng, Qiming Yuan, Wojciech Zaremba, Lei Zhang
http://arxiv.org/abs/1910.07113v1
• [cs.LG]Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments
Rémy Portelas, Cédric Colas, Katja Hofmann, Pierre-Yves Oudeyer
http://arxiv.org/abs/1910.07224v1
• [cs.LG]Transfer Learning for Algorithm Recommendation
Gean Trindade Pereira, Moisés dos Santos, Edesio Alcobaça, Rafael Mantovani, André Carvalho
http://arxiv.org/abs/1910.07012v1
• [cs.LG]Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs
Robert Walecki, Kostis Gourgoulias, Adam Baker, Chris Hart, Chris Lucas, Max Zwiessele, Albert Buchard, Maria Lomeli, Yura Perov, Saurabh Johri
http://arxiv.org/abs/1910.07474v1
• [cs.MM]A Study of Annotation and Alignment Accuracy for Performance Comparison in Complex Orchestral Music
Thassilo Gadermaier, Gerhard Widmer
http://arxiv.org/abs/1910.07394v1
• [cs.NE]AREA: Adaptive Reference-set Based Evolutionary Algorithm for Multiobjective Optimisation
Shouyong Jiang, Hongru Li, Jinglei Guo, Mingjun Zhong, Shengxiang Yang, Marcus Kaiser, Natalio Krasnogor
http://arxiv.org/abs/1910.07491v1
• [cs.NE]Negatively Correlated Search as a Parallel Exploration Search Strategy
Peng Yang, Ke Tang, Xin Yao
http://arxiv.org/abs/1910.07151v1
• [cs.NE]On-chip Few-shot Learning with Surrogate Gradient Descent on a Neuromorphic Processor
Kenneth Stewart, Emre Neftci, Garrick Orchard, Sumit Bam Shrestha
http://arxiv.org/abs/1910.04972v4
• [cs.NE]Structural Analysis of Sparse Neural Networks
Julian Stier, Michael Granitzer
http://arxiv.org/abs/1910.07225v1
• [cs.NE]The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks
Benjamin Cramer, Yannik Stradmann, Johannes Schemmel, Friedemann Zenke
http://arxiv.org/abs/1910.07407v1
• [cs.NI]Sub-Channel Allocation for Device-to-Device Underlaying Full-Duplex mmWave Small Cells using Coalition Formation Games
Yibing Wang, Yong Niu, Hao Wu, Zhu Han, Bo Ai, Qi Wang
http://arxiv.org/abs/1910.07187v1
• [cs.RO]Autonomous Aerial Cinematography In Unstructured Environments With Learned Artistic Decision-Making
Rogerio Bonatti, Wenshan Wang, Cherie Ho, Aayush Ahuja, Mirko Gschwindt, Efe Camci, Erdal Kayacan, Sanjiban Choudhury, Sebastian Scherer
http://arxiv.org/abs/1910.06988v1
• [cs.RO]Explainable Semantic Mapping for First Responders
Jean Oh, Martial Hebert, Hae-Gon Jeon, Xavier Perez, Chia Dai, Yeeho Song
http://arxiv.org/abs/1910.07093v1
• [cs.RO]FlowNorm: A Learning-based Method for Increasing Convergence Range of Direct Alignment
Ke Wang, Kaixuan Wang, Shaojie Shen
http://arxiv.org/abs/1910.07217v1
• [cs.RO]Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation
Ran Tian, Nan Li, Ilya Kolmanovsky, Yildiray Yildiz, Anouck Girard
http://arxiv.org/abs/1910.07141v1
• [cs.SI]Beyond Fortune 500: Women in a Global Network of Directors
Anna Evtushenko, Michael Gastner
http://arxiv.org/abs/1910.07441v1
• [cs.SI]Design method of Temporary Horizontal Visibility Graph for information sources impact network
D. V. Lande, A. M. Soboliev
http://arxiv.org/abs/1910.07340v1
• [cs.SI]Eva: Attribute-Aware Network Segmentation
Salvatore Citraro, Giulio Rossetti
http://arxiv.org/abs/1910.06599v2
• [cs.SI]SGP: Spotting Groups Polluting the Online Political Discourse
Junhao Wang, Sacha Levy, Ren Wang, Aayushi Kulshrestha, Reihaneh Rabbany
http://arxiv.org/abs/1910.07130v1
• [cs.SI]Tutorial on NLP-Inspired Network Embedding
Boaz Shmueli
http://arxiv.org/abs/1910.07212v1
• [econ.EM]Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition
Aureo de Paula, Imran Rasul, Pedro Souza
http://arxiv.org/abs/1910.07452v1
• [eess.AS]Analyzing Large Receptive Field Convolutional Networks for Distant Speech Recognition
Salar Jafarlou, Soheil Khorram, Vinay Kothapally, John H. L. Hansen
http://arxiv.org/abs/1910.07047v1
• [eess.AS]MIMO-SPEECH: End-to-End Multi-Channel Multi-Speaker Speech Recognition
Xuankai Chang, Wangyou Zhang, Yanmin Qian, Jonathan Le Roux, Shinji Watanabe
http://arxiv.org/abs/1910.06522v2
• [eess.AS]Transformer ASR with Contextual Block Processing
Emiru Tsunoo, Yosuke Kashiwagi, Toshiyuki Kumakura, Shinji Watanabe
http://arxiv.org/abs/1910.07204v1
• [eess.IV]A Survey on Recent Advancements for AI Enabled Radiomics in Neuro-Oncology
Syed Muhammad Anwar, Tooba Altaf, Khola Rafique, Harish RaviPrakash, Hassan Mohy-ud-Din, Ulas Bagci
http://arxiv.org/abs/1910.07470v1
• [eess.IV]Wasserstein GANs for MR Imaging: from Paired to Unpaired Training
Ke Lei, Morteza Mardani, John M. Pauly, Shreyas S. Vasawanala
http://arxiv.org/abs/1910.07048v1
• [eess.SP]Joint Transmit and Reflective Beamforming Design for IRS-Assisted Multiuser MISO SWIPT Systems
Yizheng Tang, Ganggang Ma, Hailiang Xie, Jie Xu, Xiao Han
http://arxiv.org/abs/1910.07156v1
• [eess.SP]Neural Network Design for Energy-Autonomous AI Applications using Temporal Encoding
Sergey Mileiko, Thanasin Bunnam, Fei Xia, Rishad Shafik, Alex Yakovlev, Shidhartha Das
http://arxiv.org/abs/1910.07492v1
• [eess.SP]Reconfigurable Intelligent Surface Empowered Downlink Non-Orthogonal Multiple Access
Min Fu, Yong Zhou, Yuanming Shi
http://arxiv.org/abs/1910.07361v1
• [eess.SP]Self-supervised Learning for ECG-based Emotion Recognition
Pritam Sarkar, Ali Etemad
http://arxiv.org/abs/1910.07497v1
• [eess.SP]Variance State Propagation for Structured Sparse Bayesian Learning
Mingchen Zhang, Xiaojun Yuan, Zhen-Qing He
http://arxiv.org/abs/1910.07352v1
• [eess.SY]Decentralized Heading Control with Rate Constraints using Pulse-Coupled Oscillators
Timothy Anglea, Yongqiang Wang
http://arxiv.org/abs/1910.07442v1
• [math.OC]Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games
Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang
http://arxiv.org/abs/1910.07498v1
• [math.OC]Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize
Youngsuk Park, Sauptik Dhar, Stephen Boyd, Mohak Shah
http://arxiv.org/abs/1910.07056v1
• [math.PR]Representations of Hermite processes using local time of intersecting stationary stable regenerative sets
Shuyang Bai
http://arxiv.org/abs/1910.07120v1
• [math.ST]Alternatives of the EM Algorithm for Estimating the Parameters of the Student-t Distribution
Marzieh Hasannasab, Johannes Hertrich, Friederike Laus, Gabriele Steidl
http://arxiv.org/abs/1910.06623v1
• [math.ST]Bayesian Inverse Problems with Heterogeneous Variance
Natalia Bochkina, Jenovah Rodrigues
http://arxiv.org/abs/1910.06914v2
• [math.ST]Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem
Matteo Giordano, Richard Nickl
http://arxiv.org/abs/1910.07343v1
• [math.ST]IRLS for Sparse Recovery Revisited: Examples of Failure and a Remedy
Aleksandr Y. Aravkin, James V. Burke, Daiwei He
http://arxiv.org/abs/1910.07095v1
• [math.ST]Lomax distribution and asymptotical ML estimations based on record values for probability density function and cumulative distribution function
Saman Hosseini, Dler Hussein Kadir
http://arxiv.org/abs/1910.07200v1
• [math.ST]Matrix Means and a Novel High-Dimensional Shrinkage Phenomenon
Asad Lodhia, Keith Levin, Elizaveta Levina
http://arxiv.org/abs/1910.07434v1
• [math.ST]Splinets — efficient orthonormalization of the B-splines
Xijia Liu, Hiba Nassar, Krzysztof PodgÓrski
http://arxiv.org/abs/1910.07341v1
• [math.ST]Stochastic Orderings of Multivariate Elliptical Distributions
Chuancun Yin
http://arxiv.org/abs/1910.07158v1
• [q-bio.QM]Automated Detection of Left Ventricle in Arterial Input Function Images for Inline Perfusion Mapping using Deep Learning: A study of 15,000 Patients
Hui Xue, Ethan Tseng, Kristopher D Knott, Tushar Kotecha, Louise Brown, Sven Plein, Marianna Fontana, James C Moon, Peter Kellman
http://arxiv.org/abs/1910.07122v1
• [quant-ph]Modeling Sequences with Quantum States: A Look Under the Hood
Tai-Danae Bradley, E. Miles Stoudenmire, John Terilla
http://arxiv.org/abs/1910.07425v1
• [stat.AP]Estimating FARIMA models with uncorrelated but non-independent error terms
Yacouba Boubacar Maïnassara, Youssef Esstafa, Bruno Saussereau
http://arxiv.org/abs/1910.07213v1
• [stat.AP]Identifying relationships between cognitive processes across tasks, contexts, and time
Laura Wall, David Gunawan, Scott D. Brown, Minh-Ngoc Tran, Robert Kohn, Guy E. Hawkins
http://arxiv.org/abs/1910.07185v1
• [stat.AP]Lurking Inferential Monsters? Quantifying bias in non-experimental evaluations of school programs
Ben Weidmann, Luke Miratrix
http://arxiv.org/abs/1910.07091v1
• [stat.AP]Psychometric Analysis of Forensic Examiner Behavior
Amanda Luby, Anjali Mazumder, Brian Junker
http://arxiv.org/abs/1910.07447v1
• [stat.AP]Sampling by Reversing The Landmarking Process
C. K. Lee
http://arxiv.org/abs/1910.07121v1
• [stat.ME]A Semi-Parametric Estimation Method for the Quantile Spectrum with an Application to Earthquake Classification Using Convolutional Neural Network
Tianbo Chen, Ying Sun, Ta-Hsin Li
http://arxiv.org/abs/1910.07155v1
• [stat.ME]A new INARMA(1, 1) model with Poisson marginals
Johannes Bracher
http://arxiv.org/abs/1910.07244v1
• [stat.ME]An Instrumental Variable Estimator for Mixed Indicators: Analytic Derivatives and Alternative Parameterizations
Zachary F. Fisher, Kenneth A. Bollen
http://arxiv.org/abs/1910.07393v1
• [stat.ME]Bayesian variable selection in hierarchical difference-in-differences models
James Normington, Eric F. Lock, Thomas A. Murray, Caroline S. Carlin
http://arxiv.org/abs/1910.07017v1
• [stat.ME]Conjugate Bayesian Unit-level Modeling of Count Data Under Informative Sampling Designs
Paul A. Parker, Scott H. Holan, Ryan Janicki
http://arxiv.org/abs/1910.07074v1
• [stat.ME]Discussion of “The Blessings of Multiple Causes” by Wang and Blei
Kosuke Imai, Zhichao Jiang
http://arxiv.org/abs/1910.06991v1
• [stat.ME]Multivariate Forecasting Evaluation: On Sensitive and Strictly Proper Scoring Rules
Florian Ziel, Kevin Berk
http://arxiv.org/abs/1910.07325v1
• [stat.ME]On the Interplay Between Exposure Misclassification and Informative Cluster Size
Glen McGee, Marianthi-Anna Kioumourtzoglou, Marc G. Weisskopf, Sebastien Haneuse, Brent A. Coull
http://arxiv.org/abs/1910.07438v1
• [stat.ML]Constrained Bayesian Optimization with Max-Value Entropy Search
Valerio Perrone, Iaroslav Shcherbatyi, Rodolphe Jenatton, Cedric Archambeau, Matthias Seeger
http://arxiv.org/abs/1910.07003v1
• [stat.ML]Excess risk bounds in robust empirical risk minimization
Stanislav Minsker, Timothée Mathieu
http://arxiv.org/abs/1910.07485v1
• [stat.ML]Generative Learning of Counterfactual for Synthetic Control Applications in Econometrics
Chirag Modi, Uros Seljak
http://arxiv.org/abs/1910.07178v1
• [stat.ML]Sparse Gaussian Process Regression Beyond Variational Inference
Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner
http://arxiv.org/abs/1910.07123v1
• [stat.ML]The Blessings of Multiple Causes: A Reply to Ogburn et al. (2019)
Yixin Wang, David M. Blei
http://arxiv.org/abs/1910.07320v1
• [stat.ML]The Rényi Gaussian Process
Raed Kontar, Xubo Yue
http://arxiv.org/abs/1910.06990v1
• [stat.ML]Unsupervised Domain Adaptation Meets Offline Recommender Learning
Yuta Saito
http://arxiv.org/abs/1910.07295v1
• [stat.OT]\texttt{code::proof}: Prepare for \emph{most} weather conditions
Charles T. Gray
http://arxiv.org/abs/1910.06964v1