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