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