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.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.MA - 多代理系统 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SE - 软件工程 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 math.OC - 优化与控制 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 q-bio.NC - 神经元与认知 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]Anticipation in collaborative music performance using fuzzy systems: a case study
• [cs.AI]Balanced Ranking with Diversity Constraints
• [cs.AI]Blackbox meets blackbox: Representational Similarity and Stability Analysis of Neural Language Models and Brains
• [cs.AI]Building a Computer Mahjong Player via Deep Convolutional Neural Networks
• [cs.AI]Deep learning based unsupervised concept unification in the embedding space
• [cs.AI]Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning
• [cs.AI]OpenEI: An Open Framework for Edge Intelligence
• [cs.AI]Risks from Learned Optimization in Advanced Machine Learning Systems
• [cs.AI]The Stanford Acuity Test: A Probabilistic Approach for Precise Visual Acuity Testing
• [cs.CL]A Hierarchical Reinforced Sequence Operation Method for Unsupervised Text Style Transfer
• [cs.CL]A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity
• [cs.CL]Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization
• [cs.CL]Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts
• [cs.CL]Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation
• [cs.CL]DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
• [cs.CL]Detecting Ghostwriters in High Schools
• [cs.CL]Detecting Syntactic Change Using a Neural Part-of-Speech Tagger
• [cs.CL]Entity-Centric Contextual Affective Analysis
• [cs.CL]Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings
• [cs.CL]From Balustrades to Pierre Vinken: Looking for Syntax in Transformer Self-Attentions
• [cs.CL]Generating Multi-Sentence Abstractive Summaries of Interleaved Texts
• [cs.CL]Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection
• [cs.CL]Imitation Learning for Non-Autoregressive Neural Machine Translation
• [cs.CL]Improving Neural Language Models by Segmenting, Attending, and Predicting the Future
• [cs.CL]Improving Textual Network Embedding with Global Attention via Optimal Transport
• [cs.CL]KAS-term: Extracting Slovene Terms from Doctoral Theses via Supervised Machine Learning
• [cs.CL]Learning Bilingual Sentence Embeddings via Autoencoding and Computing Similarities with a Multilayer Perceptron
• [cs.CL]Learning Deep Transformer Models for Machine Translation
• [cs.CL]Learning to Rank for Plausible Plausibility
• [cs.CL]Memory Consolidation for Contextual Spoken Language Understanding with Dialogue Logistic Inference
• [cs.CL]Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model
• [cs.CL]Neural Legal Judgment Prediction in English
• [cs.CL]On the Realization of Compositionality in Neural Networks
• [cs.CL]Open Sesame: Getting Inside BERT’s Linguistic Knowledge
• [cs.CL]Post-editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domain
• [cs.CL]Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution
• [cs.CL]Sequential Neural Networks as Automata
• [cs.CL]Terminology-based Text Embedding for Computing Document Similarities on Technical Content
• [cs.CL]The Computational Structure of Unintentional Meaning
• [cs.CL]The FRENK Datasets of Socially Unacceptable Discourse in Slovene and English
• [cs.CL]The Unreasonable Effectiveness of Transformer Language Models in Grammatical Error Correction
• [cs.CL]Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change
• [cs.CL]Towards Lossless Encoding of Sentences
• [cs.CL]Towards Multimodal Sarcasm Detection (An Obviously Perfect Paper)
• [cs.CL]Visual Story Post-Editing
• [cs.CV]4-D Scene Alignment in Surveillance Video
• [cs.CV]A Feature Transfer Enabled Multi-Task Deep Learning Model on Medical Imaging
• [cs.CV]A GLCM Embedded CNN Strategy for Computer-aided Diagnosis in Intracerebral Hemorrhage
• [cs.CV]AI-Skin : Skin Disease Recognition based on Self-learning and Wide Data Collection through a Closed Loop Framework
• [cs.CV]An Introduction to Deep Morphological Networks
• [cs.CV]Baby steps towards few-shot learning with multiple semantics
• [cs.CV]Compact Approximation for Polynomial of Covariance Feature
• [cs.CV]Consistency regularization and CutMix for semi-supervised semantic segmentation
• [cs.CV]Corn leaf detection using Region based convolutional neural network
• [cs.CV]Detecting Kissing Scenes in a Database of Hollywood Films
• [cs.CV]Efficient Codebook and Factorization for Second Order Representation Learning
• [cs.CV]Efficient, Lexicon-Free OCR using Deep Learning
• [cs.CV]Farm land weed detection with region-based deep convolutional neural networks
• [cs.CV]Fully Automated Pancreas Segmentation with Two-stage 3D Convolutional Neural Networks
• [cs.CV]Geo-Aware Networks for Fine Grained Recognition
• [cs.CV]Infant Contact-less Non-Nutritive Sucking Pattern Quantification via Facial Gesture Analysis
• [cs.CV]Invariant Tensor Feature Coding
• [cs.CV]Learning to Compose and Reason with Language Tree Structures for Visual Grounding
• [cs.CV]Multi-way Encoding for Robustness
• [cs.CV]One-pass Multi-task Networks with Cross-task Guided Attention for Brain Tumor Segmentation
• [cs.CV]PAC-GAN: An Effective Pose Augmentation Scheme for Unsupervised Cross-View Person Re-identification
• [cs.CV]PI-Net: A Deep Learning Approach to Extract Topological Persistence Images
• [cs.CV]Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion
• [cs.CV]StarNet: Pedestrian Trajectory Prediction using Deep Neural Network in Star Topology
• [cs.CV]Towards Document Image Quality Assessment: A Text Line Based Framework and A Synthetic Text Line Image Dataset
• [cs.CV]Visual Confusion Label Tree For Image Classification
• [cs.CV]Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks
• [cs.CY]A Differentially Private Incentive Design for Traffic Offload to Public Transportation
• [cs.CY]Artificial Intelligence in Clinical Health Care Applications: Viewpoint
• [cs.CY]David and Goliath: Privacy Lobbying in the European Union
• [cs.CY]The Language of Dialogue Is Complex
• [cs.DB]An Effective Algorithm for Learning Single Occurrence Regular Expressions with Interleaving
• [cs.DB]Enhancing interoperable datasets with virtual links
• [cs.DC]Distributed Weighted Matching via Randomized Composable Coresets
• [cs.DC]Performance Modelling of Deep Learning on Intel Many Integrated Core Architectures
• [cs.DC]pCAMP: Performance Comparison of Machine Learning Packages on the Edges
• [cs.DS]Fair Near Neighbor Search: Independent Range Sampling in High Dimensions
• [cs.GT]Power Law Public Goods Game for Personal Information Sharing in News Comments
• [cs.HC]Visual Fixations Duration as an Indicator of Skill Level in eSports
• [cs.IR]A Passage-Based Approach to Learning to Rank Documents
• [cs.IR]Binarized Collaborative Filtering with Distilling Graph Convolutional Networks
• [cs.IR]Collaborative Translational Metric Learning
• [cs.IR]Evaluation and Improvement of Chatbot Text Classification Data Quality Using Plausible Negative Examples
• [cs.IR]The FacT: Taming Latent Factor Models for Explainability with Factorization Trees
• [cs.IT]5G Downlink Multi-Beam Signal Design for LOS Positioning
• [cs.IT]A Dynamical System-based Key Equation for Decoding One-Point Algebraic-Geometry Codes
• [cs.IT]Memory-assisted Statistically-ranked RF Beam Training Algorithm for Sparse MIMO
• [cs.IT]Modern Random Access for Beyond-5G Systems: a Multiple-Relay ALOHA Perspective
• [cs.IT]On General Lattice Quantization Noise
• [cs.IT]On Low Complexity RLL Code for Visible Light Communication
• [cs.IT]On the Fairness Performance of NOMA-based Wireless Powered Communication Networks
• [cs.IT]RIP-based performance guarantee for low-tubal-rank tensor recovery
• [cs.IT]Spectral Efficiency Analysis in Dense Massive MIMO Networks
• [cs.LG]A meta-learning recommender system for hyperparameter tuning: predicting when tuning improves SVM classifiers
• [cs.LG]A systematic framework for natural perturbations from videos
• [cs.LG]Assessing the Robustness of Bayesian Dark Knowledge to Posterior Uncertainty
• [cs.LG]Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
• [cs.LG]CCMI : Classifier based Conditional Mutual Information Estimation
• [cs.LG]Can Graph Neural Networks Help Logic Reasoning?
• [cs.LG]Combining Physics-Based Domain Knowledge and Machine Learning using Variational Gaussian Processes with Explicit Linear Prior
• [cs.LG]Data Sketching for Faster Training of Machine Learning Models
• [cs.LG]Diameter-based Interactive Structure Search
• [cs.LG]Discriminative Few-Shot Learning Based on Directional Statistics
• [cs.LG]Distributed Training with Heterogeneous Data: Bridging Median and Mean Based Algorithms
• [cs.LG]Don’t Paint It Black: White-Box Explanations for Deep Learning in Computer Security
• [cs.LG]Empirical Risk Minimization under Random Censorship: Theory and Practice
• [cs.LG]Enumeration of Distinct Support Vectors for Interactive Decision Making
• [cs.LG]Estimating Feature-Label Dependence Using Gini Distance Statistics
• [cs.LG]Evaluating Explainers via Perturbation
• [cs.LG]Fair Distributions from Biased Samples: A Maximum Entropy Optimization Framework
• [cs.LG]GOT: An Optimal Transport framework for Graph comparison
• [cs.LG]GRAM: Scalable Generative Models for Graphs with Graph Attention Mechanism
• [cs.LG]Generalized Linear Rule Models
• [cs.LG]Global Optimality Guarantees For Policy Gradient Methods
• [cs.LG]Human Activity Recognition with Convolutional Neural Netowrks
• [cs.LG]Interpretable and Differentially Private Predictions
• [cs.LG]Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization
• [cs.LG]Learning dynamic polynomial proofs
• [cs.LG]Lifelong Learning with a Changing Action Set
• [cs.LG]Machine Learning and System Identification for Estimation in Physical Systems
• [cs.LG]Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning
• [cs.LG]Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
• [cs.LG]On the use of Pairwise Distance Learning for Brain Signal Classification with Limited Observations
• [cs.LG]Optimized Score Transformation for Fair Classification
• [cs.LG]Reinforcement Learning When All Actions are Not Always Available
• [cs.LG]Reinforcement Learning with Low-Complexity Liquid State Machines
• [cs.LG]The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis
• [cs.LG]Variational Spectral Graph Convolutional Networks
• [cs.MA]Maximizing Energy Battery Efficiency in Swarm Robotics
• [cs.NE]Genetic Random Weight Change Algorithm for the Learning of Multilayer Neural Networks
• [cs.RO]A Model-Based Balance Stabilization System for Biped Robot
• [cs.RO]A Robust Roll Angle Estimation Algorithm Based on Gradient Descent
• [cs.RO]A Survey of Behavior Learning Applications in Robotics — State of the Art and Perspectives
• [cs.RO]BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators
• [cs.RO]Comparison Study of Well-Known Inverted Pendulum Models for Balance Recovery in Humanoid Robot
• [cs.SE]Architectural Middleware that Supports Building High-performance, Scalable, Ubiquitous, Intelligent Personal Assistants
• [cs.SI]A Just and Comprehensive Strategy for Using NLP to Address Online Abuse
• [cs.SI]Legislative effectiveness hangs in the balance: Studying balance and polarization through partitioning signed networks
• [econ.EM]Bayesian nonparametric graphical models for time-varying parameters VAR
• [eess.AS]Investigating the Lombard Effect Influence on End-to-End Audio-Visual Speech Recognition
• [eess.IV]Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
• [eess.IV]AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation
• [eess.IV]OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images
• [eess.SP]Data-driven Thresholding in Denoising with Spectral Graph Wavelet Transform
• [eess.SP]Expectation Propagation Detector for Extra-Large Scale Massive MIMO
• [eess.SP]Monopulse-based THz Beam Tracking for Indoor Virtual Reality Applications
• [eess.SP]Opportunistic NOMA-based Low-Latency Uplink Transmissions
• [eess.SP]Relay-Aided Channel Estimation for mmWave Systems with Imperfect Antenna Arrays
• [math.OC]Scenario approach for minmax optimization with emphasis on the nonconvex case: positive results and caveats
• [math.ST]Locally optimal designs for generalized linear models within the family of Kiefer $Φ_k$-criteria
• [math.ST]On Testing Marginal versus Conditional Independence
• [physics.ao-ph]Combining crowd-sourcing and deep learning to understand meso-scale organization of shallow convection
• [q-bio.NC]Learning to solve the credit assignment problem
• [stat.AP]Going Deep: Models for Continuous-TimeWithin-Play Valuation of Game Outcomesin American Football with Tracking Data
• [stat.AP]High-resolution estimates of the foreign-born population and international migration for the United States
• [stat.AP]Stress Testing Network Reconstruction via Graphical Causal Model
• [stat.CO]Ensemble MCMC: Accelerating Pseudo-Marginal MCMC for State Space Models using the Ensemble Kalman Filter
• [stat.ME]A Model-free Approach to Linear Least Squares Regression with Exact Probabilities and Applications to Covariate Selection
• [stat.ME]Detecting linear trend changes and point anomalies in data sequences
• [stat.ME]Measurement errors in the binary instrumental variable model
• [stat.ME]On Benjamini-Hochberg procedure applied to mid p-values
• [stat.ME]Spatial automatic subgroup analysis for areal data with repeated measures
• [stat.ML]Adapting Neural Networks for the Estimation of Treatment Effects
• [stat.ML]Approximate Inference Turns Deep Networks into Gaussian Processes
• [stat.ML]Cubic-Spline Flows
• [stat.ML]Fréchet random forests
• [stat.ML]Probabilistic hypergraph grammars for efficient molecular optimization
• [stat.ML]Stochastic Gradients for Large-Scale Tensor Decomposition
• [stat.ML]Unbiased estimators for the variance of MMD estimators
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• [cs.AI]Anticipation in collaborative music performance using fuzzy systems: a case study
Oscar Thörn, Peter Fögel, Peter Knudsen, Luis de Miranda, Alessandro Saffiotti
http://arxiv.org/abs/1906.02155v1
• [cs.AI]Balanced Ranking with Diversity Constraints
Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich
http://arxiv.org/abs/1906.01747v1
• [cs.AI]Blackbox meets blackbox: Representational Similarity and Stability Analysis of Neural Language Models and Brains
Samira Abnar, Lisa Beinborn, Rochelle Choenni, Willem Zuidema
http://arxiv.org/abs/1906.01539v2
• [cs.AI]Building a Computer Mahjong Player via Deep Convolutional Neural Networks
Shiqi Gao, Fuminori Okuya, Yoshihiro Kawahara, Yoshimasa Tsuruoka
http://arxiv.org/abs/1906.02146v1
• [cs.AI]Deep learning based unsupervised concept unification in the embedding space
Luka Nenadović, Vladimir Prelovac
http://arxiv.org/abs/1906.01873v1
• [cs.AI]Exploration with Unreliable Intrinsic Reward in Multi-Agent Reinforcement Learning
Wendelin Böhmer, Tabish Rashid, Shimon Whiteson
http://arxiv.org/abs/1906.02138v1
• [cs.AI]OpenEI: An Open Framework for Edge Intelligence
Xingzhou Zhang, Yifan Wang, Sidi Lu, Liangkai Liu, Lanyu Xu, Weisong Shi
http://arxiv.org/abs/1906.01864v1
• [cs.AI]Risks from Learned Optimization in Advanced Machine Learning Systems
Evan Hubinger, Chris van Merwijk, Vladimir Mikulik, Joar Skalse, Scott Garrabrant
http://arxiv.org/abs/1906.01820v1
• [cs.AI]The Stanford Acuity Test: A Probabilistic Approach for Precise Visual Acuity Testing
Chris Piech, Ali Malik, Laura M Scott, Robert T Chang, Charles Lin
http://arxiv.org/abs/1906.01811v1
• [cs.CL]A Hierarchical Reinforced Sequence Operation Method for Unsupervised Text Style Transfer
Chen Wu, Xuancheng Ren, Fuli Luo, Xu Sun
http://arxiv.org/abs/1906.01833v1
• [cs.CL]A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity
Yoshinari Fujinuma, Jordan Boyd-Graber, Michael J. Paul
http://arxiv.org/abs/1906.01926v1
• [cs.CL]Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization
Mozhi Zhang, Keyulu Xu, Ken-ichi Kawarabayashi, Stefanie Jegelka, Jordan Boyd-Graber
http://arxiv.org/abs/1906.01622v2
• [cs.CL]Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts
Joseph Bullock, Miguel Luengo-Oroz
http://arxiv.org/abs/1906.01946v1
• [cs.CL]Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation
Masashi Yoshikawa, Hiroshi Noji, Koji Mineshima, Daisuke Bekki
http://arxiv.org/abs/1906.01834v1
• [cs.CL]DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
Huaishao Luo, Tianrui Li, Bing Liu, Junbo Zhang
http://arxiv.org/abs/1906.01794v1
• [cs.CL]Detecting Ghostwriters in High Schools
Magnus Stavngaard, August Sørensen, Stephan Lorenzen, Niklas Hjuler, Stephen Alstrup
http://arxiv.org/abs/1906.01635v1
• [cs.CL]Detecting Syntactic Change Using a Neural Part-of-Speech Tagger
William Merrill, Gigi Felice Stark, Robert Frank
http://arxiv.org/abs/1906.01661v1
• [cs.CL]Entity-Centric Contextual Affective Analysis
Anjalie Field, Yulia Tsvetkov
http://arxiv.org/abs/1906.01762v1
• [cs.CL]Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings
Rami Aly, Shantanu Acharya, Alexander Ossa, Arne Köhn, Chris Biemann, Alexander Panchenko
http://arxiv.org/abs/1906.02002v1
• [cs.CL]From Balustrades to Pierre Vinken: Looking for Syntax in Transformer Self-Attentions
David Mareček, Rudolf Rosa
http://arxiv.org/abs/1906.01958v1
• [cs.CL]Generating Multi-Sentence Abstractive Summaries of Interleaved Texts
Sanjeev Kumar Karn, Francine Chen, Yan-Ying Chen, Ulli Waltinger, Hinrich Schütze
http://arxiv.org/abs/1906.01973v1
• [cs.CL]Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection
Chaotao Chen, Jinhua Peng, Fan Wang, Jun Xu, Hua Wu
http://arxiv.org/abs/1906.01781v1
• [cs.CL]Imitation Learning for Non-Autoregressive Neural Machine Translation
Bingzhen Wei, Mingxuan Wang, Hao Zhou, Junyang Lin, Xu Sun
http://arxiv.org/abs/1906.02041v1
• [cs.CL]Improving Neural Language Models by Segmenting, Attending, and Predicting the Future
Hongyin Luo, Lan Jiang, Yonatan Belinkov, James Glass
http://arxiv.org/abs/1906.01702v1
• [cs.CL]Improving Textual Network Embedding with Global Attention via Optimal Transport
Liqun Chen, Guoyin Wang, Chenyang Tao, Dinghan Shen, Pengyu Cheng, Xinyuan Zhang, Wenlin Wang, Yizhe Zhang, Lawrence Carin
http://arxiv.org/abs/1906.01840v1
• [cs.CL]KAS-term: Extracting Slovene Terms from Doctoral Theses via Supervised Machine Learning
Nikola Ljubešić, Darja Fišer, Tomaž Erjavec
http://arxiv.org/abs/1906.02053v1
• [cs.CL]Learning Bilingual Sentence Embeddings via Autoencoding and Computing Similarities with a Multilayer Perceptron
Yunsu Kim, Hendrik Rosendahl, Nick Rossenbach, Jan Rosendahl, Shahram Khadivi, Hermann Ney
http://arxiv.org/abs/1906.01942v1
• [cs.CL]Learning Deep Transformer Models for Machine Translation
Qiang Wang, Bei Li, Tong Xiao, Jingbo Zhu, Changliang Li, Derek F. Wong, Lidia S. Chao
http://arxiv.org/abs/1906.01787v1
• [cs.CL]Learning to Rank for Plausible Plausibility
Zhongyang Li, Tongfei Chen, Benjamin Van Durme
http://arxiv.org/abs/1906.02079v1
• [cs.CL]Memory Consolidation for Contextual Spoken Language Understanding with Dialogue Logistic Inference
He Bai, Yu Zhou, Jiajun Zhang, Chengqing Zong
http://arxiv.org/abs/1906.01788v1
• [cs.CL]Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model
Alexander R. Fabbri, Irene Li, Tianwei She, Suyi Li, Dragomir R. Radev
http://arxiv.org/abs/1906.01749v1
• [cs.CL]Neural Legal Judgment Prediction in English
Ilias Chalkidis, Ion Androutsopoulos, Nikolaos Aletras
http://arxiv.org/abs/1906.02059v1
• [cs.CL]On the Realization of Compositionality in Neural Networks
Joris Baan, Jana Leible, Mitja Nikolaus, David Rau, Dennis Ulmer, Tim Baumgärtner, Dieuwke Hupkes, Elia Bruni
http://arxiv.org/abs/1906.01634v1
• [cs.CL]Open Sesame: Getting Inside BERT’s Linguistic Knowledge
Yongjie Lin, Yi Chern Tan, Robert Frank
http://arxiv.org/abs/1906.01698v1
• [cs.CL]Post-editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domain
Samuel Läubli, Chantal Amrhein, Patrick Düggelin, Beatriz Gonzalez, Alena Zwahlen, Martin Volk
http://arxiv.org/abs/1906.01685v1
• [cs.CL]Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution
Shany Barhom, Vered Shwartz, Alon Eirew, Michael Bugert, Nils Reimers, Ido Dagan
http://arxiv.org/abs/1906.01753v1
• [cs.CL]Sequential Neural Networks as Automata
William Merrill
http://arxiv.org/abs/1906.01615v2
• [cs.CL]Terminology-based Text Embedding for Computing Document Similarities on Technical Content
Hamid Mirisaee, Eric Gaussier, Cedric Lagnier, Agnes Guerraz
http://arxiv.org/abs/1906.01874v1
• [cs.CL]The Computational Structure of Unintentional Meaning
Mark K. Ho, Joanna Korman, Thomas L. Griffiths
http://arxiv.org/abs/1906.01983v1
• [cs.CL]The FRENK Datasets of Socially Unacceptable Discourse in Slovene and English
Nikola Ljubešić, Darja Fišer, Tomaž Erjavec
http://arxiv.org/abs/1906.02045v1
• [cs.CL]The Unreasonable Effectiveness of Transformer Language Models in Grammatical Error Correction
Dimitrios Alikaniotis, Vipul Raheja
http://arxiv.org/abs/1906.01733v1
• [cs.CL]Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change
Haim Dubossarsky, Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg
http://arxiv.org/abs/1906.01688v1
• [cs.CL]Towards Lossless Encoding of Sentences
Gabriele Prato, Mathieu Duchesneau, Sarath Chandar, Alain Tapp
http://arxiv.org/abs/1906.01659v1
• [cs.CL]Towards Multimodal Sarcasm Detection (An Obviously Perfect Paper)
Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, Roger Zimmermann, Rada Mihalcea, Soujanya Poria
http://arxiv.org/abs/1906.01815v1
• [cs.CL]Visual Story Post-Editing
Ting-Yao Hsu, Chieh-Yang Huang, Yen-Chia Hsu, Ting-Hao ‘Kenneth’ Huang
http://arxiv.org/abs/1906.01764v1
• [cs.CV]4-D Scene Alignment in Surveillance Video
Robert Wagner, Daniel Crispell, Patrick Feeney, Joe Mundy
http://arxiv.org/abs/1906.01675v1
• [cs.CV]A Feature Transfer Enabled Multi-Task Deep Learning Model on Medical Imaging
Fei Gao, Hyunsoo Yoon, Teresa Wu, Xianghua Chu
http://arxiv.org/abs/1906.01828v1
• [cs.CV]A GLCM Embedded CNN Strategy for Computer-aided Diagnosis in Intracerebral Hemorrhage
Yifan Hu, Yefeng Zheng
http://arxiv.org/abs/1906.02040v1
• [cs.CV]AI-Skin : Skin Disease Recognition based on Self-learning and Wide Data Collection through a Closed Loop Framework
Min Chen, Ping Zhou, Di Wu, Long Hu, Mohammad Mehedi Hassan, Atif Alamri
http://arxiv.org/abs/1906.01895v1
• [cs.CV]An Introduction to Deep Morphological Networks
Keiller Nogueira, Jocelyn Chanussot, Mauro Dalla Mura, William Robson Schwartz, Jefersson A. dos Santos
http://arxiv.org/abs/1906.01751v1
• [cs.CV]Baby steps towards few-shot learning with multiple semantics
Eli Schwartz, Leonid Karlinsky, Rogerio Feris, Raja Giryes, Alex M. Bronstein
http://arxiv.org/abs/1906.01905v1
• [cs.CV]Compact Approximation for Polynomial of Covariance Feature
Yusuke Mukuta, Tatsuaki Machida, Tatsuya Harada
http://arxiv.org/abs/1906.01851v1
• [cs.CV]Consistency regularization and CutMix for semi-supervised semantic segmentation
Geoff French, Timo Aila, Samuli Laine, Michal Mackiewicz, Graham Finlayson
http://arxiv.org/abs/1906.01916v1
• [cs.CV]Corn leaf detection using Region based convolutional neural network
Mohammad Ibrahim Sarker, Heechan Yang, Hyongsuk Kim
http://arxiv.org/abs/1906.01900v1
• [cs.CV]Detecting Kissing Scenes in a Database of Hollywood Films
Amir Ziai
http://arxiv.org/abs/1906.01843v1
• [cs.CV]Efficient Codebook and Factorization for Second Order Representation Learning
Pierre Jacob, David Picard, Aymeric Histace, Edouard Klein
http://arxiv.org/abs/1906.01972v1
• [cs.CV]Efficient, Lexicon-Free OCR using Deep Learning
Marcin Namysl, Iuliu Konya
http://arxiv.org/abs/1906.01969v1
• [cs.CV]Farm land weed detection with region-based deep convolutional neural networks
Mohammad Ibrahim Sarker, Hyongsuk Kim
http://arxiv.org/abs/1906.01885v1
• [cs.CV]Fully Automated Pancreas Segmentation with Two-stage 3D Convolutional Neural Networks
Ningning Zhao, Nuo Tong, Dan Ruan, Ke Sheng
http://arxiv.org/abs/1906.01795v1
• [cs.CV]Geo-Aware Networks for Fine Grained Recognition
Grace Chu, Brian Potetz, Weijun Wang, Andrew Howard, Yang Song, Fernando Brucher, Thomas Leung, Hartwig Adam
http://arxiv.org/abs/1906.01737v1
• [cs.CV]Infant Contact-less Non-Nutritive Sucking Pattern Quantification via Facial Gesture Analysis
Xiaofei Huang, Alaina Martens, Emily Zimmerman, Sarah Ostadabbas
http://arxiv.org/abs/1906.01821v1
• [cs.CV]Invariant Tensor Feature Coding
Yusuke Mukuta, Tatsuya Harada
http://arxiv.org/abs/1906.01857v1
• [cs.CV]Learning to Compose and Reason with Language Tree Structures for Visual Grounding
Richang Hong, Daqing Liu, Xiaoyu Mo, Xiangnan He, Hanwang Zhang
http://arxiv.org/abs/1906.01784v1
• [cs.CV]Multi-way Encoding for Robustness
Donghyun Kim, Sarah Adel Bargal, Jianming Zhang, Stan Sclaroff
http://arxiv.org/abs/1906.02033v1
• [cs.CV]One-pass Multi-task Networks with Cross-task Guided Attention for Brain Tumor Segmentation
Chenhong Zhou, Changxing Ding, Xinchao Wang, Zhentai Lu, Dacheng Tao
http://arxiv.org/abs/1906.01796v1
• [cs.CV]PAC-GAN: An Effective Pose Augmentation Scheme for Unsupervised Cross-View Person Re-identification
Chengyuan Zhang, Lei Zhu, Shichao Zhang
http://arxiv.org/abs/1906.01792v1
• [cs.CV]PI-Net: A Deep Learning Approach to Extract Topological Persistence Images
Anirudh Som, Hongjun Choi, Karthikeyan Natesan Ramamurthy, Matthew Buman, Pavan Turaga
http://arxiv.org/abs/1906.01769v1
• [cs.CV]Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion
Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro
http://arxiv.org/abs/1906.02042v1
• [cs.CV]StarNet: Pedestrian Trajectory Prediction using Deep Neural Network in Star Topology
Yanliang Zhu, Deheng Qian, Dongchun Ren, Huaxia Xia
http://arxiv.org/abs/1906.01797v1
• [cs.CV]Towards Document Image Quality Assessment: A Text Line Based Framework and A Synthetic Text Line Image Dataset
Hongyu Li, Fan Zhu, Junhua Qiu
http://arxiv.org/abs/1906.01907v1
• [cs.CV]Visual Confusion Label Tree For Image Classification
Yuntao Liu, Yong Dou, Ruochun Jin, Rongchun Li
http://arxiv.org/abs/1906.02012v1
• [cs.CV]Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks
Florian Dubost, Hieab Adams, Pinar Yilmaz, Gerda Bortsova, Gijs van Tulder, M. Arfan Ikram, Wiro Niessen, Meike Vernooij, Marleen de Bruijne
http://arxiv.org/abs/1906.01891v1
• [cs.CY]A Differentially Private Incentive Design for Traffic Offload to Public Transportation
Luyao Niu, Andrew Clark
http://arxiv.org/abs/1906.01683v1
• [cs.CY]Artificial Intelligence in Clinical Health Care Applications: Viewpoint
Michael van Hartskamp, Sergio Consoli, Wim Verhaegh, Milan Petković, Anja van de Stolpe
http://arxiv.org/abs/1906.02090v1
• [cs.CY]David and Goliath: Privacy Lobbying in the European Union
Jukka Ruohonen
http://arxiv.org/abs/1906.01883v1
• [cs.CY]The Language of Dialogue Is Complex
Alexander Robertson, Luca Maria Aiello, Daniele Quercia
http://arxiv.org/abs/1906.02057v1
• [cs.DB]An Effective Algorithm for Learning Single Occurrence Regular Expressions with Interleaving
Yeting Li, Haiming Chen, Xiaolan Zhang, Lingqi Zhang
http://arxiv.org/abs/1906.02074v1
• [cs.DB]Enhancing interoperable datasets with virtual links
Tarcisio Mendes de Farias, Christophe Dessimoz
http://arxiv.org/abs/1906.01950v1
• [cs.DC]Distributed Weighted Matching via Randomized Composable Coresets
Sepehr Assadi, MohammadHossein Bateni, Vahab Mirrokni
http://arxiv.org/abs/1906.01993v1
• [cs.DC]Performance Modelling of Deep Learning on Intel Many Integrated Core Architectures
Andre Viebke, Sabri Pllana, Suejb Memeti, Joanna Kolodziej
http://arxiv.org/abs/1906.01992v1
• [cs.DC]pCAMP: Performance Comparison of Machine Learning Packages on the Edges
Xingzhou Zhang, Yifan Wang, Weisong Shi
http://arxiv.org/abs/1906.01878v1
• [cs.DS]Fair Near Neighbor Search: Independent Range Sampling in High Dimensions
Martin Aumüller, Rasmus Pagh, Francesco Silvestri
http://arxiv.org/abs/1906.01859v1
• [cs.GT]Power Law Public Goods Game for Personal Information Sharing in News Comments
Christopher Griffin, Sarah Rajtmajer Anna Squicciarini Prasana Umar
http://arxiv.org/abs/1906.01677v1
• [cs.HC]Visual Fixations Duration as an Indicator of Skill Level in eSports
Boris B. Velichkovsky, Nikita Khromov, Alexander Korotin, Evgeny Burnaev, Andrey Somov
http://arxiv.org/abs/1906.01699v1
• [cs.IR]A Passage-Based Approach to Learning to Rank Documents
Eilon Sheetrit, Anna Shtok, Oren Kurland
http://arxiv.org/abs/1906.02083v1
• [cs.IR]Binarized Collaborative Filtering with Distilling Graph Convolutional Networks
Haoyu Wang, Defu Lian, Yong Ge
http://arxiv.org/abs/1906.01829v1
• [cs.IR]Collaborative Translational Metric Learning
Chanyoung Park, Donghyun Kim, Xing Xie, Hwanjo Yu
http://arxiv.org/abs/1906.01637v1
• [cs.IR]Evaluation and Improvement of Chatbot Text Classification Data Quality Using Plausible Negative Examples
Kit Kuksenok, Andriy Martyniv
http://arxiv.org/abs/1906.01910v1
• [cs.IR]The FacT: Taming Latent Factor Models for Explainability with Factorization Trees
Yiyi Tao, Yiling Jia, Nan Wang, Hongning Wang
http://arxiv.org/abs/1906.02037v1
• [cs.IT]5G Downlink Multi-Beam Signal Design for LOS Positioning
Anastasios Kakkavas, Gonzalo Seco-Granados, Henk Wymeersch, Mario H. Castañeda García, Richard A. Stirling-Gallacher, Josef A. Nossek
http://arxiv.org/abs/1906.01671v1
• [cs.IT]A Dynamical System-based Key Equation for Decoding One-Point Algebraic-Geometry Codes
Ramamonjy Andriamifidisoa, Rufine Marius Lalasoa, Toussaint Joseph Rabeherimanana
http://arxiv.org/abs/1906.01428v1
• [cs.IT]Memory-assisted Statistically-ranked RF Beam Training Algorithm for Sparse MIMO
Krishan K. Tiwari, Eckhard Grass, John S. Thompson, Rolf Kraemer
http://arxiv.org/abs/1906.01719v1
• [cs.IT]Modern Random Access for Beyond-5G Systems: a Multiple-Relay ALOHA Perspective
Andrea Munari, Federico Clazzer
http://arxiv.org/abs/1906.02054v1
• [cs.IT]On General Lattice Quantization Noise
Tal Gariby, Uri Erez
http://arxiv.org/abs/1906.01680v1
• [cs.IT]On Low Complexity RLL Code for Visible Light Communication
Nitin Jain, Adrish Banerjee
http://arxiv.org/abs/1906.02075v1
• [cs.IT]On the Fairness Performance of NOMA-based Wireless Powered Communication Networks
Yong Liu, Xuehan Chen, Lin X. Cai, Qingchun Chen, Ruoting Gong, Dong Tang
http://arxiv.org/abs/1906.00186v1
• [cs.IT]RIP-based performance guarantee for low-tubal-rank tensor recovery
Feng Zhang, Wendong Wang, Jianwen Huang, Yao Wang, Jianjun Wang
http://arxiv.org/abs/1906.01774v1
• [cs.IT]Spectral Efficiency Analysis in Dense Massive MIMO Networks
Fahime Sadat Mirhosseini, Andrea Pizzo, Luca Sanguinetti, Aliakbar Tadaion
http://arxiv.org/abs/1906.00053v1
• [cs.LG]A meta-learning recommender system for hyperparameter tuning: predicting when tuning improves SVM classifiers
Rafael Gomes Mantovani, André Luis Debiaso Rossi, Edésio Alcobaça, Joaquin Vanschoren, André Carlos Ponce de Leon Ferreira de Carvalho
http://arxiv.org/abs/1906.01684v1
• [cs.LG]A systematic framework for natural perturbations from videos
Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt
http://arxiv.org/abs/1906.02168v1
• [cs.LG]Assessing the Robustness of Bayesian Dark Knowledge to Posterior Uncertainty
Meet P. Vadera, Benjamin M. Marlin
http://arxiv.org/abs/1906.01724v1
• [cs.LG]Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Sitao Luan, Mingde Zhao, Xiao-Wen Chang, Doina Precup
http://arxiv.org/abs/1906.02174v1
• [cs.LG]CCMI : Classifier based Conditional Mutual Information Estimation
Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan
http://arxiv.org/abs/1906.01824v1
• [cs.LG]Can Graph Neural Networks Help Logic Reasoning?
Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song
http://arxiv.org/abs/1906.02111v1
• [cs.LG]Combining Physics-Based Domain Knowledge and Machine Learning using Variational Gaussian Processes with Explicit Linear Prior
Daniel L. Marino, Milos Manic
http://arxiv.org/abs/1906.02160v1
• [cs.LG]Data Sketching for Faster Training of Machine Learning Models
Baharan Mirzasoleiman, Jeff Bilmes, Jure Leskovec
http://arxiv.org/abs/1906.01827v1
• [cs.LG]Diameter-based Interactive Structure Search
Christopher Tosh, Daniel Hsu
http://arxiv.org/abs/1906.02101v1
• [cs.LG]Discriminative Few-Shot Learning Based on Directional Statistics
Junyoung Park, Subin Yi, Yongseok Choi, Dong-Yeon Cho, Jiwon Kim
http://arxiv.org/abs/1906.01819v1
• [cs.LG]Distributed Training with Heterogeneous Data: Bridging Median and Mean Based Algorithms
Xiangyi Chen, Tiancong Chen, Haoran Sun, Zhiwei Steven Wu, Mingyi Hong
http://arxiv.org/abs/1906.01736v1
• [cs.LG]Don’t Paint It Black: White-Box Explanations for Deep Learning in Computer Security
Alexander Warnecke, Daniel Arp, Christian Wressnegger, Konrad Rieck
http://arxiv.org/abs/1906.02108v1
• [cs.LG]Empirical Risk Minimization under Random Censorship: Theory and Practice
Guillaume Ausset, Stéphan Clémençon, François Portier
http://arxiv.org/abs/1906.01908v1
• [cs.LG]Enumeration of Distinct Support Vectors for Interactive Decision Making
Kentaro Kanamori, Satoshi Hara, Masakazu Ishihata, Hiroki Arimura
http://arxiv.org/abs/1906.01876v1
• [cs.LG]Estimating Feature-Label Dependence Using Gini Distance Statistics
Silu Zhang, Xin Dang, Dao Nguyen, Dawn Wilkins, Yixin Chen
http://arxiv.org/abs/1906.02171v1
• [cs.LG]Evaluating Explainers via Perturbation
Minh N. Vu, Truc D. Nguyen, NhatHai Phan, Ralucca Gera, My T. Thai
http://arxiv.org/abs/1906.02032v1
• [cs.LG]Fair Distributions from Biased Samples: A Maximum Entropy Optimization Framework
L. Elisa Celis, Vijay Keswani, Ozan Yildiz, Nisheeth K. Vishnoi
http://arxiv.org/abs/1906.02164v1
• [cs.LG]GOT: An Optimal Transport framework for Graph comparison
Hermina Petric Maretic, Mireille EL Gheche, Giovanni Chierchia, Pascal Frossard
http://arxiv.org/abs/1906.02085v1
• [cs.LG]GRAM: Scalable Generative Models for Graphs with Graph Attention Mechanism
Wataru Kawai, Yusuke Mukuta, Tatsuya Harada
http://arxiv.org/abs/1906.01861v1
• [cs.LG]Generalized Linear Rule Models
Dennis Wei, Sanjeeb Dash, Tian Gao, Oktay Günlük
http://arxiv.org/abs/1906.01761v1
• [cs.LG]Global Optimality Guarantees For Policy Gradient Methods
Jalaj Bhandari, Daniel Russo
http://arxiv.org/abs/1906.01786v1
• [cs.LG]Human Activity Recognition with Convolutional Neural Netowrks
Antonio Bevilacqua, Kyle MacDonald, Aamina Rangarej, Venessa Widjaya, Brian Caulfield, Tahar Kechadi
http://arxiv.org/abs/1906.01935v1
• [cs.LG]Interpretable and Differentially Private Predictions
Frederik Harder, Matthias Bauer, Mijung Park
http://arxiv.org/abs/1906.02004v1
• [cs.LG]Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization
Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder
http://arxiv.org/abs/1906.02107v1
• [cs.LG]Learning dynamic polynomial proofs
Alhussein Fawzi, Mateusz Malinowski, Hamza Fawzi, Omar Fawzi
http://arxiv.org/abs/1906.01681v1
• [cs.LG]Lifelong Learning with a Changing Action Set
Yash Chandak, Georgios Theocharous, Chris Nota, Philip S. Thomas
http://arxiv.org/abs/1906.01770v1
• [cs.LG]Machine Learning and System Identification for Estimation in Physical Systems
Fredrik Bagge Carlson
http://arxiv.org/abs/1906.02003v1
• [cs.LG]Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash
http://arxiv.org/abs/1906.01668v1
• [cs.LG]Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
Ruibo Tu, Kun Zhang, Bo Christer Bertilson, Hedvig Kjellstöm, Cheng Zhang
http://arxiv.org/abs/1906.01732v1
• [cs.LG]On the use of Pairwise Distance Learning for Brain Signal Classification with Limited Observations
David Calhas, Enrique Romero, Rui Henriques
http://arxiv.org/abs/1906.02076v1
• [cs.LG]Optimized Score Transformation for Fair Classification
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flavio du Pin Calmon
http://arxiv.org/abs/1906.00066v1
• [cs.LG]Reinforcement Learning When All Actions are Not Always Available
Yash Chandak, Georgios Theocharous, Blossom Metevier, Philip S. Thomas
http://arxiv.org/abs/1906.01772v1
• [cs.LG]Reinforcement Learning with Low-Complexity Liquid State Machines
Wachirawit Ponghiran, Gopalakrishnan Srinivasan, Kaushik Roy
http://arxiv.org/abs/1906.01695v1
• [cs.LG]The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis
Cynthia Rudin, David Carlson
http://arxiv.org/abs/1906.01998v1
• [cs.LG]Variational Spectral Graph Convolutional Networks
Louis Tiao, Pantelis Elinas, Harrison Nguyen, Edwin V. Bonilla
http://arxiv.org/abs/1906.01852v1
• [cs.MA]Maximizing Energy Battery Efficiency in Swarm Robotics
Anthony Chen, John Harwell, Maria Gini
http://arxiv.org/abs/1906.01957v1
• [cs.NE]Genetic Random Weight Change Algorithm for the Learning of Multilayer Neural Networks
Mohammad Ibraim Sarker, Yali Nie, Hong Yongki, Hyongsuk Kim
http://arxiv.org/abs/1906.01892v1
• [cs.RO]A Model-Based Balance Stabilization System for Biped Robot
Mohammadreza Kasaei, Nuno Lau, Artur Pereira
http://arxiv.org/abs/1906.02017v1
• [cs.RO]A Robust Roll Angle Estimation Algorithm Based on Gradient Descent
Rui Fan, Lujia Wang, Ming Liu, Ioannis Pitas
http://arxiv.org/abs/1906.01894v1
• [cs.RO]A Survey of Behavior Learning Applications in Robotics — State of the Art and Perspectives
Alexander Fabisch, Christoph Petzoldt, Marc Otto, Frank Kirchner
http://arxiv.org/abs/1906.01868v1
• [cs.RO]BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators
Fabio Ramos, Rafael Carvalhaes Possas, Dieter Fox
http://arxiv.org/abs/1906.01728v1
• [cs.RO]Comparison Study of Well-Known Inverted Pendulum Models for Balance Recovery in Humanoid Robot
Mohammadreza Kasaei, Nuno Lau, Artur Pereira
http://arxiv.org/abs/1906.01936v1
• [cs.SE]Architectural Middleware that Supports Building High-performance, Scalable, Ubiquitous, Intelligent Personal Assistants
Oscar J. Romero
http://arxiv.org/abs/1906.02068v1
• [cs.SI]A Just and Comprehensive Strategy for Using NLP to Address Online Abuse
David Jurgens, Eshwar Chandrasekharan, Libby Hemphill
http://arxiv.org/abs/1906.01738v1
• [cs.SI]Legislative effectiveness hangs in the balance: Studying balance and polarization through partitioning signed networks
Samin Aref, Zachary Neal
http://arxiv.org/abs/1906.01696v1
• [econ.EM]Bayesian nonparametric graphical models for time-varying parameters VAR
Matteo Iacopini, Luca Rossini
http://arxiv.org/abs/1906.02140v1
• [eess.AS]Investigating the Lombard Effect Influence on End-to-End Audio-Visual Speech Recognition
Pingchuan Ma, Stavros Petridis, Maja Pantic
http://arxiv.org/abs/1906.02112v1
• [eess.IV]Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Haofu Liao, Wei-An Lin, S. Kevin Zhou, Jiebo Luo
http://arxiv.org/abs/1906.01806v1
• [eess.IV]AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation
Pierrick Coupé, Boris Mansencal, Michaël Clément, Rémi Giraud, Baudouin Denis de Senneville, Vinh-Thong Ta, Vincent Lepetit, José V. Manjon
http://arxiv.org/abs/1906.01862v1
• [eess.IV]OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images
Yu Chen, Yuexiang Li, Jiawei Chen, Yefeng Zheng
http://arxiv.org/abs/1906.02031v1
• [eess.SP]Data-driven Thresholding in Denoising with Spectral Graph Wavelet Transform
Basile de Loynes, Fabien Navarro, Baptiste Olivier
http://arxiv.org/abs/1906.01882v1
• [eess.SP]Expectation Propagation Detector for Extra-Large Scale Massive MIMO
Hanqing Wang, Alva Kosasih, Chao-Kai Wen, Shi Jin, Wibowo Hardjawana
http://arxiv.org/abs/1906.01921v1
• [eess.SP]Monopulse-based THz Beam Tracking for Indoor Virtual Reality Applications
Krishan Kumar Tiwari, Vladica Sark, Eckhard Grass, Rolf Kraemer
http://arxiv.org/abs/1906.01722v1
• [eess.SP]Opportunistic NOMA-based Low-Latency Uplink Transmissions
Jinho Choi
http://arxiv.org/abs/1906.01818v1
• [eess.SP]Relay-Aided Channel Estimation for mmWave Systems with Imperfect Antenna Arrays
Mohammed E. Eltayeb
http://arxiv.org/abs/1906.00183v1
• [math.OC]Scenario approach for minmax optimization with emphasis on the nonconvex case: positive results and caveats
Mishal Assif P K, Debasish Chatterjee, Ravi Banavar
http://arxiv.org/abs/1906.01476v2
• [math.ST]Locally optimal designs for generalized linear models within the family of Kiefer $Φ_k$-criteria
Osama Idais
http://arxiv.org/abs/1906.02158v1
• [math.ST]On Testing Marginal versus Conditional Independence
Fangjian Guo, Thomas S. Richardson
http://arxiv.org/abs/1906.01850v1
• [physics.ao-ph]Combining crowd-sourcing and deep learning to understand meso-scale organization of shallow convection
Stephan Rasp, Hauke Schulz, Sandrine Bony, Bjorn Stevens
http://arxiv.org/abs/1906.01906v1
• [q-bio.NC]Learning to solve the credit assignment problem
Benjamin James Lansdell, Prashanth Ravi Prakash, Konrad Paul Kording
http://arxiv.org/abs/1906.00889v2
• [stat.AP]Going Deep: Models for Continuous-TimeWithin-Play Valuation of Game Outcomesin American Football with Tracking Data
Ronald Yurko, Francesca Matano, Lee F. Richardson, Nicholas Granered, Taylor Pospisil, Konstantinos Pelechrinis, Samuel L. Ventura
http://arxiv.org/abs/1906.01760v1
• [stat.AP]High-resolution estimates of the foreign-born population and international migration for the United States
Nicolas A Menzies
http://arxiv.org/abs/1906.01716v1
• [stat.AP]Stress Testing Network Reconstruction via Graphical Causal Model
Helder Rojas, David Dias
http://arxiv.org/abs/1906.01468v2
• [stat.CO]Ensemble MCMC: Accelerating Pseudo-Marginal MCMC for State Space Models using the Ensemble Kalman Filter
Christopher Drovandi, Richard G Everitt, Andrew Golightly, Dennis Prangle
http://arxiv.org/abs/1906.02014v1
• [stat.ME]A Model-free Approach to Linear Least Squares Regression with Exact Probabilities and Applications to Covariate Selection
Laurie Davies, Lutz Dümbgen
http://arxiv.org/abs/1906.01990v1
• [stat.ME]Detecting linear trend changes and point anomalies in data sequences
Hyeyoung Maeng, Piotr Fryzlewicz
http://arxiv.org/abs/1906.01939v1
• [stat.ME]Measurement errors in the binary instrumental variable model
Zhichao Jiang, Peng Ding
http://arxiv.org/abs/1906.02030v1
• [stat.ME]On Benjamini-Hochberg procedure applied to mid p-values
Xiongzhi Chen, Sanat K. Sarkar
http://arxiv.org/abs/1906.01701v1
• [stat.ME]Spatial automatic subgroup analysis for areal data with repeated measures
Xin Wang, Zhengyuan Zhu, Hao Helen Zhang
http://arxiv.org/abs/1906.01853v1
• [stat.ML]Adapting Neural Networks for the Estimation of Treatment Effects
Claudia Shi, David M. Blei, Victor Veitch
http://arxiv.org/abs/1906.02120v1
• [stat.ML]Approximate Inference Turns Deep Networks into Gaussian Processes
Mohammad Emtiyaz Khan, Alexander Immer, Ehsan Abedi, Maciej Korzepa
http://arxiv.org/abs/1906.01930v1
• [stat.ML]Cubic-Spline Flows
Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios
http://arxiv.org/abs/1906.02145v1
• [stat.ML]Fréchet random forests
Louis Capitaine, Robin Genuer, Rodolphe Thiébaut
http://arxiv.org/abs/1906.01741v1
• [stat.ML]Probabilistic hypergraph grammars for efficient molecular optimization
Egor Kraev, Mark Harley
http://arxiv.org/abs/1906.01845v1
• [stat.ML]Stochastic Gradients for Large-Scale Tensor Decomposition
Tamara G. Kolda, David Hong
http://arxiv.org/abs/1906.01687v1
• [stat.ML]Unbiased estimators for the variance of MMD estimators
Dougal J. Sutherland
http://arxiv.org/abs/1906.02104v1