cs.AI - 人工智能

    cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.DC - 分布式、并行与集群计算 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SD - 声音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 q-bio.QM - 定量方法 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习 stat.OT - 其他统计学

    • [cs.AI]AIBA: An AI Model for Behavior Arbitration in Autonomous Driving
    • [cs.AI]Experimenting with Constraint Programming on GPU
    • [cs.AI]Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message-Passing
    • [cs.AI]Intelligent Policing Strategy for Traffic Violation Prevention
    • [cs.AI]Repositioning Bikes with Carrier Vehicles and Bike Trailers in Bike Sharing Systems
    • [cs.CL]A Critical Analysis of Biased Parsers in Unsupervised Parsing
    • [cs.CL]AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models
    • [cs.CL]BERT Meets Chinese Word Segmentation
    • [cs.CL]Creative GANs for generating poems, lyrics, and metaphors
    • [cs.CL]Cross-lingual Dependency Parsing with Unlabeled Auxiliary Languages
    • [cs.CL]Designing dialogue systems: A mean, grumpy, sarcastic chatbot in the browser
    • [cs.CL]Goal-Embedded Dual Hierarchical Model for Task-Oriented Dialogue Generation
    • [cs.CL]Improved Variational Neural Machine Translation by Promoting Mutual Information
    • [cs.CL]Jointly Learning Entity and Relation Representations for Entity Alignment
    • [cs.CL]Named Entity Recognition with Partially Annotated Training Data
    • [cs.CL]Pivot-based Transfer Learning for Neural Machine Translation between Non-English Languages
    • [cs.CL]Sampling Bias in Deep Active Classification: An Empirical Study
    • [cs.CL]Towards Neural Language Evaluators
    • [cs.CL]What’s Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering
    • [cs.CL]Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers
    • [cs.CR]Augmenting Encrypted Search: A Decentralized Service Realization with Enforced Execution
    • [cs.CV]A nonlocal feature-driven exemplar-based approach for image inpainting
    • [cs.CV]ACFNet: Attentional Class Feature Network for Semantic Segmentation
    • [cs.CV]Adversarial Learning with Margin-based Triplet Embedding Regularization
    • [cs.CV]CNN-based RGB-D Salient Object Detection: Learn, Select and Fuse
    • [cs.CV]Coupled Generative Adversarial Network for Continuous Fine-grained Action Segmentation
    • [cs.CV]Deep Aggregation of Regional Convolutional Activations for Content Based Image Retrieval
    • [cs.CV]Document Rectification and Illumination Correction using a Patch-based CNN
    • [cs.CV]EATEN: Entity-aware Attention for Single Shot Visual Text Extraction
    • [cs.CV]Fine-grained Action Segmentation using the Semi-Supervised Action GAN
    • [cs.CV]Forecasting Future Action Sequences with Neural Memory Networks
    • [cs.CV]Fourier-CPPNs for Image Synthesis
    • [cs.CV]Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks
    • [cs.CV]Learning Lightweight Pedestrian Detector with Hierarchical Knowledge Distillation
    • [cs.CV]Making the Invisible Visible: Action Recognition Through Walls and Occlusions
    • [cs.CV]Multi-user Augmented Reality Application for Video Communication in Virtual Space
    • [cs.CV]Retro-Actions: Learning ‘Close’ by Time-Reversing ‘Open’ Videos
    • [cs.CV]Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
    • [cs.CV]Target-Specific Action Classification for Automated Assessment of Human Motor Behavior from Video
    • [cs.CV]Weakly Supervised Semantic Segmentation Using Constrained Dominant Sets
    • [cs.DC]Cache Optimization for Sharing Intensive Workloads on Multi-socket Multi-core servers
    • [cs.DC]Locality, Statefulness, and Causality in Distributed Information Systems (Concerning the Scale Dependence Of System Promises)
    • [cs.DC]Multiprocessor Real-Time Locking Protocols: A Systematic Review
    • [cs.DC]Simultaneous Progressing Switching Protocols for Timing Predictable Real-Time Network-on-Chips
    • [cs.HC]Quantifying the Impact of Cognitive Biases in Question-Answering Systems
    • [cs.IR]Automatic Table completion using Knowledge Base
    • [cs.IR]Natural Language Processing via LDA Topic Model in Recommendation Systems
    • [cs.IT]Analysis and Optimization of Successful Symbol Transmission Rate for Grant-free Massive Access with Massive MIMO
    • [cs.IT]Dictionary Learning for Channel Estimation in Hybrid Frequency-Selective mmWave MIMO Systems
    • [cs.IT]The Max-Product Algorithm Viewed as Linear Data-Fusion: A Distributed Detection Scenario
    • [cs.LG]A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels
    • [cs.LG]Bayesian Optimization for Iterative Learning
    • [cs.LG]Causal Modeling for Fairness in Dynamical Systems
    • [cs.LG]Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias
    • [cs.LG]CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
    • [cs.LG]Deep Metric Learning using Similarities from Nonlinear Rank Approximations
    • [cs.LG]Defending Against Physically Realizable Attacks on Image Classification
    • [cs.LG]Detailed comparison of communication efficiency of split learning and federated learning
    • [cs.LG]FACE: Feasible and Actionable Counterfactual Explanations
    • [cs.LG]From feature selection to continues optimization
    • [cs.LG]Genetic Neural Architecture Search for automatic assessment of human sperm images
    • [cs.LG]HyperLearn: A Distributed Approach for Representation Learning in Datasets With Many Modalities
    • [cs.LG]Machine Learning for Clinical Predictive Analytics
    • [cs.LG]Meta-Inverse Reinforcement Learning with Probabilistic Context Variables
    • [cs.LG]On Recovering Latent Factors From Sampling And Firing Graph
    • [cs.LG]Reconnaissance and Planning algorithm for constrained MDP
    • [cs.LG]Redirection Controller Using Reinforcement Learning
    • [cs.LG]Representation Learning for Electronic Health Records
    • [cs.LG]Revisit Policy Optimization in Matrix Form
    • [cs.LG]Trivializations for Gradient-Based Optimization on Manifolds
    • [cs.LG]Understanding Architectures Learnt by Cell-based Neural Architecture Search
    • [cs.NE]2-D Cluster Variation Method Free Energy: Fundamentals and Pragmatics
    • [cs.NE]An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution
    • [cs.NE]An Introduction to Quaternion-Valued Recurrent Projection Neural Networks
    • [cs.RO]An Efficient Sampling-based Method for Online Informative Path Planning in Unknown Environments
    • [cs.RO]How Much Do Unstated Problem Constraints Limit Deep Robotic Reinforcement Learning?
    • [cs.RO]Hypermap Mapping Framework and its Application to Autonomous Semantic Exploration
    • [cs.RO]Impedance Control of a Transfemoral Prosthesis using Continuously Varying Ankle Impedances and Multiple Equilibria
    • [cs.RO]Inverse Kinematics for Serial Kinematic Chains via Sum of Squares Optimization
    • [cs.RO]Learning Your Way Without Map or Compass: Panoramic Target Driven Visual Navigation
    • [cs.RO]Object grasping planning for the situation when soft and rigid objects are mixed together
    • [cs.RO]Robot Sound Interpretation: Combining Sight and Sound in Learning-Based Control
    • [cs.RO]Robust Humanoid Contact Planning with Learned Zero- and One-Step Capturability Prediction
    • [cs.RO]The Colliding Reciprocal Dance Problem: A Mitigation Strategy with Application to Automotive Active Safety Systems
    • [cs.RO]Trunk Pitch Oscillations to Improve Energetics in Bipedal Running Birds and Robots
    • [cs.SD]MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection
    • [eess.IV]A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI
    • [eess.IV]Brain Tumor Segmentation and Survival Prediction
    • [eess.IV]Deep 3D-Zoom Net: Unsupervised Learning of Photo-Realistic 3D-Zoom
    • [eess.IV]Infusing Learned Priors into Model-Based Multispectral Imaging
    • [eess.IV]Underwater Image Super-Resolution using Deep Residual Multipliers
    • [eess.IV]Unsupervised Learning for Real-World Super-Resolution
    • [eess.SP]Secure Interference Exploitation Precoding in MISO Wiretap Channel: Destructive Region Redefinition with Efficient Solutions
    • [math.NA]A Multi-level procedure for enhancing accuracy of machine learning algorithms
    • [math.OC]A Two-Stage Stochastic Programming Model for Car-Sharing Problem using Kernel Density Estimation
    • [math.OC]Nonparametric learning for impulse control problems
    • [math.OC]Regularized Diffusion Adaptation via Conjugate Smoothing
    • [math.ST]Applications of Generalized Maximum Likelihood Estimators to stratified sampling and post-stratification with many unobserved strata
    • [math.ST]Multi-level Bayes and MAP monotonicity testing
    • [math.ST]On the structure of exchangeable extreme-value copulas
    • [math.ST]Robust Estimation and Shrinkage in Ultrahigh Dimensional Expectile Regression with Heavy Tails and Variance Heterogeneity
    • [q-bio.QM]Leveraging Implicit Expert Knowledge for Non-Circular Machine Learning in Sepsis Prediction
    • [stat.AP]Alternative Analysis Methods for Time to Event Endpoints under Non-proportional Hazards: A Comparative Analysis
    • [stat.AP]Application of Clustering Analysis for Investigation of Food Accessibility
    • [stat.AP]Biased Encouragements and Heterogeneous Effects in an Instrumental Variable Study of Emergency General Surgical Outcomes
    • [stat.AP]Consensual aggregation of clusters based on Bregman divergences to improve predictive models
    • [stat.AP]Forecasting Fertility with Parametric Mixture Models
    • [stat.AP]Posterior Contraction Rate of Sparse Latent Feature Models with Application to Proteomics
    • [stat.ME]Inference for the stochastic block model with unknown number of blocks and non-conjugate edge models
    • [stat.ME]Novel algorithm for confidence sub-contour box estimation: an alternative to traditional confidence intervals
    • [stat.ME]Sequential Ensemble Transform for Bayesian Inverse Problems
    • [stat.ML]Comparing distributions: $\ell_1$ geometry improves kernel two-sample testing
    • [stat.ML]Computing Full Conformal Prediction Set with Approximate Homotopy
    • [stat.ML]Does SLOPE outperform bridge regression?
    • [stat.ML]Non-Parametric Structure Learning on Hidden Tree-Shaped Distributions
    • [stat.ML]On the Convergence of Approximate and Regularized Policy Iteration Schemes
    • [stat.OT]Uncovering Sociological Effect Heterogeneity using Machine Learning

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    • [cs.AI]AIBA: An AI Model for Behavior Arbitration in Autonomous Driving
    Bogdan Trasnea, Claudiu pozna, Sorin Grigorescu
    http://arxiv.org/abs/1909.09418v1

    • [cs.AI]Experimenting with Constraint Programming on GPU
    Fabio Tardivo
    http://arxiv.org/abs/1909.09213v1

    • [cs.AI]Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message-Passing
    Zhe Zeng, Fanqi Yan, Paolo Morettin, Antonio Vergari, Guy Van den Broeck
    http://arxiv.org/abs/1909.09362v1

    • [cs.AI]Intelligent Policing Strategy for Traffic Violation Prevention
    Monireh Dabaghchian, Amir Alipour-Fanid, Kai Zeng
    http://arxiv.org/abs/1909.09291v1

    • [cs.AI]Repositioning Bikes with Carrier Vehicles and Bike Trailers in Bike Sharing Systems
    Xinghua Zheng, Ming Tang, Hankz Hankui Zhuo, Kevin X. Wen
    http://arxiv.org/abs/1909.09616v1

    • [cs.CL]A Critical Analysis of Biased Parsers in Unsupervised Parsing
    Chris Dyer, Gábor Melis, Phil Blunsom
    http://arxiv.org/abs/1909.09428v1

    • [cs.CL]AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models
    Eric Wallace, Jens Tuyls, Junlin Wang, Sanjay Subramanian, Matt Gardner, Sameer Singh
    http://arxiv.org/abs/1909.09251v1

    • [cs.CL]BERT Meets Chinese Word Segmentation
    Haiqin Yang
    http://arxiv.org/abs/1909.09292v1

    • [cs.CL]Creative GANs for generating poems, lyrics, and metaphors
    Asir Saeed, Suzana Ilić, Eva Zangerle
    http://arxiv.org/abs/1909.09534v1

    • [cs.CL]Cross-lingual Dependency Parsing with Unlabeled Auxiliary Languages
    Wasi Uddin Ahmad, Zhisong Zhang, Xuezhe Ma, Kai-Wei Chang, Nanyun Peng
    http://arxiv.org/abs/1909.09265v1

    • [cs.CL]Designing dialogue systems: A mean, grumpy, sarcastic chatbot in the browser
    Suzana Ilić, Reiichiro Nakano, Ivo Hajnal
    http://arxiv.org/abs/1909.09531v1

    • [cs.CL]Goal-Embedded Dual Hierarchical Model for Task-Oriented Dialogue Generation
    Yi-An Lai, Arshit Gupta, Yi Zhang
    http://arxiv.org/abs/1909.09220v1

    • [cs.CL]Improved Variational Neural Machine Translation by Promoting Mutual Information
    Arya D. McCarthy, Xian Li, Jiatao Gu, Ning Dong
    http://arxiv.org/abs/1909.09237v1

    • [cs.CL]Jointly Learning Entity and Relation Representations for Entity Alignment
    Yuting Wu, Xiao Liu, Yansong Feng, Zheng Wang, Dongyan Zhao
    http://arxiv.org/abs/1909.09317v1

    • [cs.CL]Named Entity Recognition with Partially Annotated Training Data
    Stephen Mayhew, Snigdha Chaturvedi, Chen-Tse Tsai, Dan Roth
    http://arxiv.org/abs/1909.09270v1

    • [cs.CL]Pivot-based Transfer Learning for Neural Machine Translation between Non-English Languages
    Yunsu Kim, Petre Petrov, Pavel Petrushkov, Shahram Khadivi, Hermann Ney
    http://arxiv.org/abs/1909.09524v1

    • [cs.CL]Sampling Bias in Deep Active Classification: An Empirical Study
    Ameya Prabhu, Charles Dognin, Maneesh Singh
    http://arxiv.org/abs/1909.09389v1

    • [cs.CL]Towards Neural Language Evaluators
    Hassan Kané, Yusuf Kocyigit, Pelkins Ajanoh, Ali Abdalla, Mohamed Coulibali
    http://arxiv.org/abs/1909.09268v1

    • [cs.CL]What’s Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering
    Tushar Khot, Ashish Sabharwal, Peter Clark
    http://arxiv.org/abs/1909.09253v1

    • [cs.CL]Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers
    Adam Fisch, Jiang Guo, Regina Barzilay
    http://arxiv.org/abs/1909.09279v1

    • [cs.CR]Augmenting Encrypted Search: A Decentralized Service Realization with Enforced Execution
    Shengshan Hu, Chengjun Cai, Qian Wang, Cong Wang, Minghui Li, Zhibo Wang, Dengpan Ye
    http://arxiv.org/abs/1909.09472v1

    • [cs.CV]A nonlocal feature-driven exemplar-based approach for image inpainting
    Viktor Reshniak, Jeremy Trageser, Clayton G. Webster
    http://arxiv.org/abs/1909.09301v1

    • [cs.CV]ACFNet: Attentional Class Feature Network for Semantic Segmentation
    Fan Zhang, Yanqin Chen, Zhihang Li, Zhibin Hong, Jingtuo Liu, Feifei Ma, Junyu Han, Errui Ding
    http://arxiv.org/abs/1909.09408v1

    • [cs.CV]Adversarial Learning with Margin-based Triplet Embedding Regularization
    Yaoyao Zhong, Weihong Deng
    http://arxiv.org/abs/1909.09481v1

    • [cs.CV]CNN-based RGB-D Salient Object Detection: Learn, Select and Fuse
    Hao Chen, Youfu Li
    http://arxiv.org/abs/1909.09309v1

    • [cs.CV]Coupled Generative Adversarial Network for Continuous Fine-grained Action Segmentation
    Harshala Gammulle, Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes
    http://arxiv.org/abs/1909.09283v1

    • [cs.CV]Deep Aggregation of Regional Convolutional Activations for Content Based Image Retrieval
    Konstantin Schall, Kai Uwe Barthel, Nico Hezel, Klaus Jung
    http://arxiv.org/abs/1909.09420v1

    • [cs.CV]Document Rectification and Illumination Correction using a Patch-based CNN
    Xiaoyu Li, Bo Zhang, Jing Liao, Pedro V. Sander
    http://arxiv.org/abs/1909.09470v1

    • [cs.CV]EATEN: Entity-aware Attention for Single Shot Visual Text Extraction
    He guo, Xiameng Qin, Jiaming Liu, Junyu Han, Jingtuo Liu, Errui Ding
    http://arxiv.org/abs/1909.09380v1

    • [cs.CV]Fine-grained Action Segmentation using the Semi-Supervised Action GAN
    Harshala Gammulle, Simon Denman, Sridha Sridharan, Clinton Fookes
    http://arxiv.org/abs/1909.09269v1

    • [cs.CV]Forecasting Future Action Sequences with Neural Memory Networks
    Harshala Gammulle, Simon Denman, Sridha Sridharan, Clinton Fookes
    http://arxiv.org/abs/1909.09278v1

    • [cs.CV]Fourier-CPPNs for Image Synthesis
    Mattie Tesfaldet, Xavier Snelgrove, David Vazquez
    http://arxiv.org/abs/1909.09273v1

    • [cs.CV]Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks
    Chengxi Li, Yue Meng, Stanley H. Chan, Yi-Ting Chen
    http://arxiv.org/abs/1909.09272v1

    • [cs.CV]Learning Lightweight Pedestrian Detector with Hierarchical Knowledge Distillation
    Rui Chen, Haizhou Ai, Chong Shang, Long Chen, Zijie Zhuang
    http://arxiv.org/abs/1909.09325v1

    • [cs.CV]Making the Invisible Visible: Action Recognition Through Walls and Occlusions
    Tianhong Li, Lijie Fan, Mingmin Zhao, Yingcheng Liu, Dina Katabi
    http://arxiv.org/abs/1909.09300v1

    • [cs.CV]Multi-user Augmented Reality Application for Video Communication in Virtual Space
    Kumar Mridul, M. Ramanathan, Kunal Ahirwar, Mansi Sharma
    http://arxiv.org/abs/1909.09529v1

    • [cs.CV]Retro-Actions: Learning ‘Close’ by Time-Reversing ‘Open’ Videos
    Will Price, Dima Damen
    http://arxiv.org/abs/1909.09422v1

    • [cs.CV]Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
    Huan Lei, Naveed Akhtar, Ajmal Mian
    http://arxiv.org/abs/1909.09287v1

    • [cs.CV]Target-Specific Action Classification for Automated Assessment of Human Motor Behavior from Video
    Behnaz Rezaei, Yiorgos Christakis, Bryan Ho, Kevin Thomas, Kelley Erb, Sarah Ostadabbas, Shyamal Patel
    http://arxiv.org/abs/1909.09566v1

    • [cs.CV]Weakly Supervised Semantic Segmentation Using Constrained Dominant Sets
    Sinem Aslan, Marcello Pelillo
    http://arxiv.org/abs/1909.09414v1

    • [cs.DC]Cache Optimization for Sharing Intensive Workloads on Multi-socket Multi-core servers
    Suryanarayana Murthy Durbhakula
    http://arxiv.org/abs/1909.09463v1

    • [cs.DC]Locality, Statefulness, and Causality in Distributed Information Systems (Concerning the Scale Dependence Of System Promises)
    Mark Burgess
    http://arxiv.org/abs/1909.09357v1

    • [cs.DC]Multiprocessor Real-Time Locking Protocols: A Systematic Review
    Björn B. Brandenburg
    http://arxiv.org/abs/1909.09600v1

    • [cs.DC]Simultaneous Progressing Switching Protocols for Timing Predictable Real-Time Network-on-Chips
    Niklas Ueter, Georg von der Brueggen, Jian-Jia Chen, Tulika Mitra, Vanchinathan Venkataramani
    http://arxiv.org/abs/1909.09457v1

    • [cs.HC]Quantifying the Impact of Cognitive Biases in Question-Answering Systems
    Keith Burghardt, Tad Hogg, Kristina Lerman
    http://arxiv.org/abs/1909.09633v1

    • [cs.IR]Automatic Table completion using Knowledge Base
    Bortik Bandyopadhyay, Xiang Deng, Goonmeet Bajaj, Huan Sun, Srinivasan Parthasarathy
    http://arxiv.org/abs/1909.09565v1

    • [cs.IR]Natural Language Processing via LDA Topic Model in Recommendation Systems
    Hamed Jelodar, Yongli Wang, Mahdi Rabbani, SeyedValyAllah Ayobi
    http://arxiv.org/abs/1909.09551v1

    • [cs.IT]Analysis and Optimization of Successful Symbol Transmission Rate for Grant-free Massive Access with Massive MIMO
    Gang Chen, Ying Cui, Hei Victor Cheng, Feng Yang, Lianghui Ding
    http://arxiv.org/abs/1909.09290v1

    • [cs.IT]Dictionary Learning for Channel Estimation in Hybrid Frequency-Selective mmWave MIMO Systems
    Hongxiang Xie, Javier Rodríguez-Fernández, Nuria González-Prelcic
    http://arxiv.org/abs/1909.09181v1

    • [cs.IT]The Max-Product Algorithm Viewed as Linear Data-Fusion: A Distributed Detection Scenario
    Younes Abdi, Tapani Ristaniemi
    http://arxiv.org/abs/1909.09402v1

    • [cs.LG]A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels
    Yucen Luo, Jun Zhu, Tomas Pfister
    http://arxiv.org/abs/1909.09338v1

    • [cs.LG]Bayesian Optimization for Iterative Learning
    Vu Nguyen, Sebastian Schulze, Michael A Osborne
    http://arxiv.org/abs/1909.09593v1

    • [cs.LG]Causal Modeling for Fairness in Dynamical Systems
    Elliot Creager, David Madras, Toniann Pitassi, Richard Zemel
    http://arxiv.org/abs/1909.09141v1

    • [cs.LG]Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias
    Asma Ghandeharioun, Brian Eoff, Brendan Jou, Rosalind W. Picard
    http://arxiv.org/abs/1909.09285v1

    • [cs.LG]CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
    Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, Marc Brockschmidt
    http://arxiv.org/abs/1909.09436v1

    • [cs.LG]Deep Metric Learning using Similarities from Nonlinear Rank Approximations
    Konstantin Schall, Kai Uwe Barthel, Nico Hezel, Klaus Jung
    http://arxiv.org/abs/1909.09427v1

    • [cs.LG]Defending Against Physically Realizable Attacks on Image Classification
    Tong Wu, Liang Tong, Yevgeniy Vorobeychik
    http://arxiv.org/abs/1909.09552v1

    • [cs.LG]Detailed comparison of communication efficiency of split learning and federated learning
    Abhishek Singh, Praneeth Vepakomma, Otkrist Gupta, Ramesh Raskar
    http://arxiv.org/abs/1909.09145v1

    • [cs.LG]FACE: Feasible and Actionable Counterfactual Explanations
    Rafael Poyiadzi, Kacper Sokol, Raul Santos-Rodriguez, Tijl De Bie, Peter Flach
    http://arxiv.org/abs/1909.09369v1

    • [cs.LG]From feature selection to continues optimization
    Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot, Mathieu Brevilliers
    http://arxiv.org/abs/1909.09444v1

    • [cs.LG]Genetic Neural Architecture Search for automatic assessment of human sperm images
    Erfan Miahi, Seyed Abolghasem Mirroshandel, Alexis Nasr
    http://arxiv.org/abs/1909.09432v1

    • [cs.LG]HyperLearn: A Distributed Approach for Representation Learning in Datasets With Many Modalities
    Devanshu Arya, Stevan Rudinac, Marcel Worring
    http://arxiv.org/abs/1909.09252v1

    • [cs.LG]Machine Learning for Clinical Predictive Analytics
    Wei-Hung Weng
    http://arxiv.org/abs/1909.09246v1

    • [cs.LG]Meta-Inverse Reinforcement Learning with Probabilistic Context Variables
    Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon
    http://arxiv.org/abs/1909.09314v1

    • [cs.LG]On Recovering Latent Factors From Sampling And Firing Graph
    Pierre Gouedard
    http://arxiv.org/abs/1909.09493v1

    • [cs.LG]Reconnaissance and Planning algorithm for constrained MDP
    Shin-ichi Maeda, Hayato Watahiki, Shintarou Okada, Masanori Koyama
    http://arxiv.org/abs/1909.09540v1

    • [cs.LG]Redirection Controller Using Reinforcement Learning
    Yuchen Chang, Keigo Matsumoto, Takuji Narumi, Tomohiro Tanikawa, Michitaka Hirose
    http://arxiv.org/abs/1909.09505v1

    • [cs.LG]Representation Learning for Electronic Health Records
    Wei-Hung Weng, Peter Szolovits
    http://arxiv.org/abs/1909.09248v1

    • [cs.LG]Revisit Policy Optimization in Matrix Form
    Sitao Luan, Xiao-Wen Chang, Doina Precup
    http://arxiv.org/abs/1909.09186v1

    • [cs.LG]Trivializations for Gradient-Based Optimization on Manifolds
    Mario Lezcano-Casado
    http://arxiv.org/abs/1909.09501v1

    • [cs.LG]Understanding Architectures Learnt by Cell-based Neural Architecture Search
    Yao Shu, Wei Wang, Shaofeng Cai
    http://arxiv.org/abs/1909.09569v1

    • [cs.NE]2-D Cluster Variation Method Free Energy: Fundamentals and Pragmatics
    Alianna J. Maren
    http://arxiv.org/abs/1909.09366v1

    • [cs.NE]An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution
    Travis J. Desell, AbdElRahman A. ElSaid, Alexander G. Ororbia
    http://arxiv.org/abs/1909.09502v1

    • [cs.NE]An Introduction to Quaternion-Valued Recurrent Projection Neural Networks
    Marcos Eduardo Valle, Rodolfo Anibal Lobo
    http://arxiv.org/abs/1909.09227v1

    • [cs.RO]An Efficient Sampling-based Method for Online Informative Path Planning in Unknown Environments
    Lukas Schmid, Michael Pantic, Raghav Khanna, Lionel Ott, Roland Siegwart, Juan Nieto
    http://arxiv.org/abs/1909.09548v1

    • [cs.RO]How Much Do Unstated Problem Constraints Limit Deep Robotic Reinforcement Learning?
    W. Cannon Lewis II, Mark Moll, Lydia E. Kavraki
    http://arxiv.org/abs/1909.09282v1

    • [cs.RO]Hypermap Mapping Framework and its Application to Autonomous Semantic Exploration
    Tobias Zaenker, Francesco Verdoja, Ville Kyrki
    http://arxiv.org/abs/1909.09526v1

    • [cs.RO]Impedance Control of a Transfemoral Prosthesis using Continuously Varying Ankle Impedances and Multiple Equilibria
    Namita Anil Kumar, Woolim Hong, Pilwon Hur
    http://arxiv.org/abs/1909.09299v1

    • [cs.RO]Inverse Kinematics for Serial Kinematic Chains via Sum of Squares Optimization
    Filip Maric, Matthew Giamou, Soroush Khoubyarian, Ivan Petrovic, Jonathan Kelly
    http://arxiv.org/abs/1909.09318v1

    • [cs.RO]Learning Your Way Without Map or Compass: Panoramic Target Driven Visual Navigation
    David Watkins-Valls, Jingxi Xu, Nicholas Waytowich, Peter Allen
    http://arxiv.org/abs/1909.09295v1

    • [cs.RO]Object grasping planning for the situation when soft and rigid objects are mixed together
    Xiaoman Wang, Xin Jiang, Jie Zhao, Shengfan Wang, Yunhui Liu
    http://arxiv.org/abs/1909.09536v1

    • [cs.RO]Robot Sound Interpretation: Combining Sight and Sound in Learning-Based Control
    Peixin Chang, Shuijing Liu, Haonan Chen, Katherine Driggs-Campbell
    http://arxiv.org/abs/1909.09172v1

    • [cs.RO]Robust Humanoid Contact Planning with Learned Zero- and One-Step Capturability Prediction
    Yu-Chi Lin, Ludovic Righetti, Dmitry Berenson
    http://arxiv.org/abs/1909.09233v1

    • [cs.RO]The Colliding Reciprocal Dance Problem: A Mitigation Strategy with Application to Automotive Active Safety Systems
    Jeffrey Kane Johnson
    http://arxiv.org/abs/1909.09224v1

    • [cs.RO]Trunk Pitch Oscillations to Improve Energetics in Bipedal Running Birds and Robots
    Özge Drama, Alexander Badri-Spröwitz
    http://arxiv.org/abs/1909.09378v1

    • [cs.SD]MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection
    Harsh Purohit, Ryo Tanabe, Kenji Ichige, Takashi Endo, Yuki Nikaido, Kaori Suefusa, Yohei Kawaguchi
    http://arxiv.org/abs/1909.09347v1

    • [eess.IV]A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI
    Saman Motamed, Isha Gujrathi, Dominik Deniffel, Anton Oentoro, Masoom A. Haider, Farzad Khalvati
    http://arxiv.org/abs/1909.09541v1

    • [eess.IV]Brain Tumor Segmentation and Survival Prediction
    Rupal Agravat, Mehul S Raval
    http://arxiv.org/abs/1909.09399v1

    • [eess.IV]Deep 3D-Zoom Net: Unsupervised Learning of Photo-Realistic 3D-Zoom
    Juan Luis Gonzalez Bello, Munchurl Kim
    http://arxiv.org/abs/1909.09349v1

    • [eess.IV]Infusing Learned Priors into Model-Based Multispectral Imaging
    Jiaming Liu, Yu Sun, Ulugbek S. Kamilov
    http://arxiv.org/abs/1909.09313v1

    • [eess.IV]Underwater Image Super-Resolution using Deep Residual Multipliers
    Md Jahidul Islam, Sadman Sakib Enan, Peigen Luo, Junaed Sattar
    http://arxiv.org/abs/1909.09437v1

    • [eess.IV]Unsupervised Learning for Real-World Super-Resolution
    Andreas Lugmayr, Martin Danelljan, Radu Timofte
    http://arxiv.org/abs/1909.09629v1

    • [eess.SP]Secure Interference Exploitation Precoding in MISO Wiretap Channel: Destructive Region Redefinition with Efficient Solutions
    Ye Fan, Xuewen Liao, Ang Li, Victor C. M. Leung
    http://arxiv.org/abs/1909.09339v1

    • [math.NA]A Multi-level procedure for enhancing accuracy of machine learning algorithms
    Kjetil O. Lye, Siddhartha Mishra, Roberto Molinaro
    http://arxiv.org/abs/1909.09448v1

    • [math.OC]A Two-Stage Stochastic Programming Model for Car-Sharing Problem using Kernel Density Estimation
    Xiaoming Li, Chun Wang, Xiao Huang
    http://arxiv.org/abs/1909.09293v1

    • [math.OC]Nonparametric learning for impulse control problems
    Sören Christensen, Claudia Strauch
    http://arxiv.org/abs/1909.09528v1

    • [math.OC]Regularized Diffusion Adaptation via Conjugate Smoothing
    Stefan Vlaski, Lieven Vandenberghe, Ali H. Sayed
    http://arxiv.org/abs/1909.09417v1

    • [math.ST]Applications of Generalized Maximum Likelihood Estimators to stratified sampling and post-stratification with many unobserved strata
    Eitan Greenshtein, Ya’acov Ritov
    http://arxiv.org/abs/1909.09336v1

    • [math.ST]Multi-level Bayes and MAP monotonicity testing
    Yuri Golubev, Christophe Pouet
    http://arxiv.org/abs/1909.09517v1

    • [math.ST]On the structure of exchangeable extreme-value copulas
    Jan-Frederik Mai, Matthias Scherer
    http://arxiv.org/abs/1909.09438v1

    • [math.ST]Robust Estimation and Shrinkage in Ultrahigh Dimensional Expectile Regression with Heavy Tails and Variance Heterogeneity
    Jun Zhao, Guan’ao Yan, Yi Zhang
    http://arxiv.org/abs/1909.09302v1

    • [q-bio.QM]Leveraging Implicit Expert Knowledge for Non-Circular Machine Learning in Sepsis Prediction
    Shigehiko Schamoni, Holger A. Lindner, Verena Schneider-Lindner, Manfred Thiel, Stefan Riezler
    http://arxiv.org/abs/1909.09557v1

    • [stat.AP]Alternative Analysis Methods for Time to Event Endpoints under Non-proportional Hazards: A Comparative Analysis
    Ray S. Lin, Ji Lin, Satrajit Roychoudhury, Keaven M. Anderson, Tianle Hu, Bo Huang, Larry F Leon, Jason JZ Liao, Rong Liu, Xiaodong Luo, Pralay Mukhopadhyay, Rui Qin, Kay Tatsuoka, Xuejing Wang, Yang Wang, Jian Zhu, Tai-Tsang Chen, Renee Iacona, Cross-Pharma Non-proportional Hazards Working Group
    http://arxiv.org/abs/1909.09467v1

    • [stat.AP]Application of Clustering Analysis for Investigation of Food Accessibility
    Rahul Srinivas Sucharitha, Seokcheon Lee
    http://arxiv.org/abs/1909.09453v1

    • [stat.AP]Biased Encouragements and Heterogeneous Effects in an Instrumental Variable Study of Emergency General Surgical Outcomes
    Colin B. Fogarty, Kwonsang Lee, Rachel R. Kelz, Luke J. Keele
    http://arxiv.org/abs/1909.09533v1

    • [stat.AP]Consensual aggregation of clusters based on Bregman divergences to improve predictive models
    Aurélie Fisher, Sothea Has, Mathilde Mougeot
    http://arxiv.org/abs/1909.09370v1

    • [stat.AP]Forecasting Fertility with Parametric Mixture Models
    Jason Hilton, Erengul Dodd, Jonathan J. Forster, Peter W. F. Smith, Jakub Bijak
    http://arxiv.org/abs/1909.09545v1

    • [stat.AP]Posterior Contraction Rate of Sparse Latent Feature Models with Application to Proteomics
    Tong Li, Tianjian Zhou, Kam-Wah Tsui, Lin Wei, Yuan Ji
    http://arxiv.org/abs/1909.09261v1

    • [stat.ME]Inference for the stochastic block model with unknown number of blocks and non-conjugate edge models
    Matthew Ludkin
    http://arxiv.org/abs/1909.09421v1

    • [stat.ME]Novel algorithm for confidence sub-contour box estimation: an alternative to traditional confidence intervals
    Daniel Rojas-Diaz, Alexandra Catano-Lopez, Carlos M. Velez-Sanchez
    http://arxiv.org/abs/1909.09603v1

    • [stat.ME]Sequential Ensemble Transform for Bayesian Inverse Problems
    Aaron Myers, Alexandre H. Thiery, Kainan Wang, Tan Bui-Thanh
    http://arxiv.org/abs/1909.09591v1

    • [stat.ML]Comparing distributions: $\ell_1$ geometry improves kernel two-sample testing
    M. Scetbon, G. Varoquaux
    http://arxiv.org/abs/1909.09264v1

    • [stat.ML]Computing Full Conformal Prediction Set with Approximate Homotopy
    Eugene Ndiaye, Ichiro Takeuchi
    http://arxiv.org/abs/1909.09365v1

    • [stat.ML]Does SLOPE outperform bridge regression?
    Shuaiwen Wang, Haolei Weng, Arian Maleki
    http://arxiv.org/abs/1909.09345v1

    • [stat.ML]Non-Parametric Structure Learning on Hidden Tree-Shaped Distributions
    Konstantinos E. Nikolakakis, Dionysios S. Kalogerias, Anand D. Sarwate
    http://arxiv.org/abs/1909.09596v1

    • [stat.ML]On the Convergence of Approximate and Regularized Policy Iteration Schemes
    Elena Smirnova, Elvis Dohmatob
    http://arxiv.org/abs/1909.09621v1

    • [stat.OT]Uncovering Sociological Effect Heterogeneity using Machine Learning
    Jennie E. Brand, Jiahui Xu, Bernard Koch, Pablo Geraldo
    http://arxiv.org/abs/1909.09138v1