cs.CV - 机器视觉与模式识别
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.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.ET - 新兴技术 cs.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.ST - 统计理论 physics.ins-det - 仪器和探测器 physics.soc-ph - 物理学与社会 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 • [ 76f cs.CV]Action Localization through Continual Predictive Learning • [cs.AI]Adversarial System Variant Approximation to Quantify Process Model Generalization • [cs.AI]End-to-End Entity Classification on Multimodal Knowledge Graphs • [cs.AI]Generation of Consistent Sets of Multi-Label Classification Rules with a Multi-Objective Evolutionary Algorithm • [cs.AI]Identification of Choquet capacity in multicriteria sorting problems through stochastic inverse analysis • [cs.AI]Rolling Horizon Evolutionary Algorithms for General Video Game Playing • [cs.CL]Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision • [cs.CL]FFR V1.0: Fon-French Neural Machine Translation • [cs.CL]Information-Theoretic Probing with Minimum Description Length • [cs.CL]Integrating Crowdsourcing and Active Learning for Classification of Work-Life Events from Tweets • [cs.CL]Semantic Enrichment of Nigerian Pidgin English for Contextual Sentiment Classification • [cs.CR]To Tweet or Not to Tweet: Covertly Manipulating a Twitter Debate on Vaccines Using Malware-Induced Misperceptions • [cs.CV]An Investigation into the Stochasticity of Batch Whitening • [cs.CV]Assessing Image Quality Issues for Real-World Problem • [cs.CV]Controllable Person Image Synthesis with Attribute-Decomposed GAN • [cs.CV]Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction • [cs.CV]CurlingNet: Compositional Learning between Images and Text for Fashion IQ Data • [cs.CV]DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search • [cs.CV]Dynamic Region-Aware Convolution • [cs.CV]Enhanced Self-Perception in Mixed Reality: Egocentric Arm Segmentation and Database with Automatic Labelling • [cs.CV]Generalizable Semantic Segmentation via Model-agnostic Learning and Target-specific Normalization • [cs.CV]HERS: Homomorphically Encrypted Representation Search • [cs.CV]Hybrid Models for Open Set Recognition • [cs.CV]Learning Implicit Surface Light Fields • [cs.CV]Learning to Optimize Non-Rigid Tracking • [cs.CV]Lightweight Photometric Stereo for Facial Details Recovery • [cs.CV]Local Facial Makeup Transfer via Disentangled Representation • [cs.CV]Modeling 3D Shapes by Reinforcement Learning • [cs.CV]Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification • [cs.CV]One-Shot GAN Generated Fake Face Detection • [cs.CV]ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds • [cs.CV]Probabilistic Regression for Visual Tracking • [cs.CV]Tackling Two Challenges of 6D Object Pose Estimation: Lack of Real Annotated RGB Images and Scalability to Number of Objects • [cs.CV]Towards Accurate Scene Text Recognition with Semantic Reasoning Networks • [cs.CV]Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations • [cs.CV]Weakly Supervised Dataset Collection for Robust Person Detection • [cs.CV]Weakly-Supervised Action Localization by Generative Attention Modeling • [cs.CY]A Liquid Perspective on Democratic Choice • [cs.CY]Democratic Value and Money for Decentralized Digital Society • [cs.CY]Mobile phone data and COVID-19: Missing an opportunity? • [cs.CY]On the Emerging Area of Biocybersecurity and Relevant Considerations • [cs.DC]AI on the Edge: Rethinking AI-based IoT Applications Using Specialized Edge Architectures • [cs.DC]Algorithm-Based Fault Tolerance for Convolutional Neural Networks • [cs.DC]Enabling Efficient and Flexible FPGA Virtualization for Deep Learning in the Cloud • [cs.DC]Online and Real-time Object Tracking Algorithm with Extremely Small Matrices • [cs.ET]IMAC: In-memory multi-bit Multiplication andACcumulation in 6T SRAM Array • [cs.IT]A PHY Layer Security Analysis of a Hybrid High Throughput Satellite with an Optical Feeder Link • [cs.IT]Asymptotically Secure Network Code for Active Attacks and its Application to Network Quantum Key Distribution • [cs.IT]Bayes-Optimal Convolutional AMP • [cs.IT]Non-linearity of the Carlet-Feng function, and repartition of Gauss sums • [cs.IT]On design-theoretic aspects of Boolean and vectorial bent functions • [cs.IT]RANSAC-Based Signal Denoising Using Compressive Sensing • [cs.IT]Secure network code over one-hop relay network • [cs.LG]A Collective Learning Framework to Boost GNN Expressiveness • [cs.LG]A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms • [cs.LG]A Hybrid-Order Distributed SGD Method for Non-Convex Optimization to Balance Communication Overhead, Computational Complexity, and Convergence Rate • [cs.LG]A Principled Approach to Learning Stochastic Representations for Privacy in Deep Neural Inference • [cs.LG]A copula-based visualization technique for a neural network • [cs.LG]A light neural network for modulation detection under impairments • [cs.LG]ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series • [cs.LG]AirRL: A Reinforcement Learning Approach to Urban Air Quality Inference • [cs.LG]Distributed Kernel Ridge Regression with Communications • [cs.LG]Financial Time Series Representation Learning • [cs.LG]Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program) • [cs.LG]Incorporating Expert Prior in Bayesian Optimisation via Space Warping • [cs.LG]LIMP: Learning Latent Shape Representations with Metric Preservation Priors • [cs.LG]Learning To Solve Differential Equations Across Initial Conditions • [cs.LG]Learning representations in Bayesian Confidence Propagation neural networks • [cs.LG]Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment • [cs.LG]MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation • [cs.LG]On a minimum enclosing ball of a collection of linear subspaces • [cs.LG]On the Optimization Dynamics of Wide Hypernetworks • [cs.LG]Optimization of genomic classifiers for clinical deployment: evaluation of Bayesian optimization for identification of predictive models of acute infection and in-hospital mortality • [cs.LG]Piecewise linear activations substantially shape the loss surfaces of neural networks • [cs.LG]Progressive Graph Convolutional Networks for Semi-Supervised Node Classification • [cs.LG]Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning • [cs.LG]Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks • [cs.MM]Unsupervised Cross-Modal Audio Representation Learning from Unstructured Multilingual Text • [cs.NE]Bayesian Hierarchical Multi-Objective Optimization for Vehicle Parking Route Discovery • [cs.NE]Boolean learning under noise-perturbations in hardware neural networks • [cs.NI]A Survey on Edge Intelligence • [cs.RO]Implementation of Survivor Detection Strategies Using Drones • [cs.RO]Metrics and Optimization of Internal Poses for Highly Redundant Truss-Like Serialized Parallel Manipulators • [cs.RO]Representing Multi-Robot Structure through Multimodal Graph Embedding for the Selection of Robot Teams • [cs.RO]Towards Autonomous Industrial-Scale Bathymetric Surveying • [cs.SI]$α$-Satellite: An AI-driven System and Benchmark Datasets for Hierarchical Community-level Risk Assessment to Help Combat COVID-19 • [cs.SI]Coronavirus on Social Media: Analyzing Misinformation in Twitter Conversations • [cs.SI]Shortest Paths in Complex Networks: Structure and Optimization • [econ.EM]Sequential monitoring for cointegrating regressions • [eess.AS]Can you hear me $\textit{now}$? Sensitive comparisons of human and machine perception • [eess.AS]Mic2Mic: Using Cycle-Consistent Generative Adversarial Networks to Overcome Microphone Variability in Speech Systems • [eess.AS]Separating Varying Numbers of Sources with Auxiliary Autoencoding Loss • [eess.IV]A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks • [eess.IV]Augmenting Colonoscopy using Extended and Directional CycleGAN for Lossy Image Translation • [eess.IV]COVID-19 Screening on Chest X-ray Images Using Deep Learning based Anomaly Detection • [eess.SP]Bayesian Sequential Joint Detection and Estimation under Multiple Hypotheses • [eess.SP]Distributed Caching for Data Dissemination in the Downlink of Heterogeneous Networks • [eess.SY]Closed-loop Parameter Identification of Linear Dynamical Systems through the Lens of Feedback Channel Coding Theory • [math.ST]Quantifying deviations from separability in space-time functional processes • [math.ST]Seemingly unrelated and fixed-effect panel regressions: collinearity and singular dispersion • [math.ST]Tests and estimation strategies associated to some loss functions • [physics.ins-det]Using Machine Learning to Speed Up and Improve Calorimeter R&D • [physics.soc-ph]The Network Dynamics of Social and Technological Conventions • [stat.AP]Separable and Semiparametric Network-based Counting Processes applied to the International Combat Aircraft Trades • [stat.CO]Online Smoothing for Diffusion Processes Observed with Noise • [stat.ME]A super scalable algorithm for short segment detection • [stat.ME]Data Integration by combining big data and survey sample data for finite population inference • [stat.ME]Enriched Pitman-Yor processes • [stat.ME]Post-sampling crowdsourced data to allow reliable statistical inference: the case of food price indices in Nigeria • [stat.ME]Robust Q-learning • [stat.ME]Transition Models for Count Data: a Flexible Alternative to Fixed Distribution Models • [stat.ML]Gaussian-Dirichlet Random Fields for Inference over High Dimensional Categorical Observations • [stat.ML]Gryffin: An algorithm for Bayesian optimization for categorical variables informed by physical intuition with applications to chemistry • [stat.ML]On the role of surrogates in the efficient estimation of treatment effects with limited outcome data • [stat.ML]Sorting Big Data by Revealed Preference with Application to College Ranking ····································· • [ 76f cs.CV]Action Localization through Continual Predictive Learning Sathyanarayanan N. Aakur, Sudeep Sarkar http://arxiv.org/abs/2003.12185v1 • [cs.AI]Adversarial System Variant Approximation to Quantify Process Model Generalization Julian Theis, Houshang Darabi http://arxiv.org/abs/2003.12168v1 • [cs.AI]End-to-End Entity Classification on Multimodal Knowledge Graphs W. X. Wilcke, P. Bloem, V. de Boer, R. H. van t Veer, F. A. H. van Harmelen http://arxiv.org/abs/2003.12383v1 • [cs.AI]Generation of Consistent Sets of Multi-Label Classification Rules with a Multi-Objective Evolutionary Algorithm Thiago Zafalon Miranda, Diorge Brognara Sardinha, Márcio Porto Basgalupp, Yaochu Jin, Ricardo Cerri http://arxiv.org/abs/2003.12526v1 • [cs.AI]Identification of Choquet capacity in multicriteria sorting problems through stochastic inverse analysis Renata Pelissari, Leonardo Tomazeli Duarte http://arxiv.org/abs/2003.12530v1 • [cs.AI]Rolling Horizon Evolutionary Algorithms for General Video Game Playing Raluca D. Gaina, Sam Devlin, Simon M. Lucas, Diego Perez-Liebana http://arxiv.org/abs/2003.12331v1 • [cs.CL]Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision Xuan Wang, Xiangchen Song, Yingjun Guan, Bangzheng Li, Jiawei Han http://arxiv.org/abs/2003.12218v1 • [cs.CL]FFR V1.0: Fon-French Neural Machine Translation Bonaventure F. P. Dossou, Chris C. Emezue http://arxiv.org/abs/2003.12111v1 • [cs.CL]Information-Theoretic Probing with Minimum Description Length Elena Voita, Ivan Titov http://arxiv.org/abs/2003.12298v1 • [cs.CL]Integrating Crowdsourcing and Active Learning for Classification of Work-Life Events from Tweets Yunpeng Zhao, Mattia Prosperi, Tianchen Lyu, Yi Guo, Jing Bian http://arxiv.org/abs/2003.12139v1 • [cs.CL]Semantic Enrichment of Nigerian Pidgin English for Contextual Sentiment Classification Wuraola Fisayo Oyewusi, Olubayo Adekanmbi, Olalekan Akinsande http://arxiv.org/abs/2003.12450v1 • [cs.CR]To Tweet or Not to Tweet: Covertly Manipulating a Twitter Debate on Vaccines Using Malware-Induced Misperceptions Filipo Sharevski, Peter Jachim, Kevin Florek http://arxiv.org/abs/2003.12093v1 • [cs.CV]An Investigation into the Stochasticity of Batch Whitening Lei Huang, Lei Zhao, Yi Zhou, Fan Zhu, Li Liu, Ling Shao http://arxiv.org/abs/2003.12327v1 • [cs.CV]Assessing Image Quality Issues for Real-World Problem Tai-Yin Chiu, Yinan Zhao, Danna Gurari http://arxiv.org/abs/2003.12511v1 • [cs.CV]Controllable Person Image Synthesis with Attribute-Decomposed GAN Yifang Men, Yiming Mao, Yuning Jiang, Wei-Ying Ma, Zhouhui Lian http://arxiv.org/abs/2003.12267v1 • [cs.CV]Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction Ali Samadzadeh, Fatemeh Sadat Tabatabaei Far, Ali Javadi, Ahmad Nickabadi, Morteza Haghir Chehreghani http://arxiv.org/abs/2003.12346v1 • [cs.CV]CurlingNet: Compositional Learning between Images and Text for Fashion IQ Data Youngjae Yu, Seunghwan Lee, Yuncheol Choi, Yuncheol Choi, Gunhee Kim http://arxiv.org/abs/2003.12299v1 • [cs.CV]DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search Xiyang Dai, Dongdong Chen, Mengchen Liu, Yinpeng Chen, Lu Yuan http://arxiv.org/abs/2003.12563v1 • [cs.CV]Dynamic Region-Aware Convolution Jin Chen, Xijun Wang, Zichao Guo, Xiangyu Zhang, Jian Sun http://arxiv.org/abs/2003.12243v1 • [cs.CV]Enhanced Self-Perception in Mixed Reality: Egocentric Arm Segmentation and Database with Automatic Labelling Ester Gonzalez-Sosa, Pablo Perez, Ruben Tolosana, Redouane Kachach, Alvaro Villegas http://arxiv.org/abs/2003.12352v1 • [cs.CV]Generalizable Semantic Segmentation via Model-agnostic Learning and Target-specific Normalization Jian Zhang, Lei Qi, Yinghuan Shi, Yang Gao http://arxiv.org/abs/2003.12296v1 • [cs.CV]HERS: Homomorphically Encrypted Representation Search Joshua J. Engelsma, Anil K. Jain, Vishnu Naresh Boddeti http://arxiv.org/abs/2003.12197v1 • [cs.CV]Hybrid Models for Open Set Recognition Hongjie Zhang, Ang Li, Jie Guo, Yanwen Guo http://arxiv.org/abs/2003.12506v1 • [cs.CV]Learning Implicit Surface Light Fields Michael Oechsle, Michael Niemeyer, Lars Mescheder, Thilo Strauss, Andreas Geiger http://arxiv.org/abs/2003.12406v1 • [cs.CV]Learning to Optimize Non-Rigid Tracking Yang Li, Aljaž Božič, Tianwei Zhang, Yanli Ji, Tatsuya Harada, Matthias Nießner http://arxiv.org/abs/2003.12230v1 • [cs.CV]Lightweight Photometric Stereo for Facial Details Recovery Xueying Wang, Yudong Guo, Bailin Deng, Juyong Zhang http://arxiv.org/abs/2003.12307v1 • [cs.CV]Local Facial Makeup Transfer via Disentangled Representation Zhaoyang Sun, Wenxuan Liu, Feng Liu, Ryan Wen Liu, Shengwu Xiong http://arxiv.org/abs/2003.12065v1 • [cs.CV]Modeling 3D Shapes by Reinforcement Learning Cheng Lin, Tingxiang Fan, Wenping Wang, Matthias Nießner http://arxiv.org/abs/2003.12397v1 • [cs.CV]Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification Zhizheng Zhang, Cuiling Lan, Wenjun Zeng, Zhibo Chen http://arxiv.org/abs/2003.12224v1 • [cs.CV]One-Shot GAN Generated Fake Face Detection Hadi Mansourifar, Weidong Shi http://arxiv.org/abs/2003.12244v1 • [cs.CV]ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds Gopal Sharma, Difan Liu, Evangelos Kalogerakis, Subhransu Maji, Siddhartha Chaudhuri, Radomir Měch http://arxiv.org/abs/2003.12181v1 • [cs.CV]Probabilistic Regression for Visual Tracking Martin Danelljan, Luc Van Gool, Radu Timofte http://arxiv.org/abs/2003.12565v1 • [cs.CV]Tackling Two Challenges of 6D Object Pose Estimation: Lack of Real Annotated RGB Images and Scalability to Number of Objects Juil Sock, Pedro Castro, Anil Armagan, Guillermo Garcia-Hernando, Tae-Kyun Kim http://arxiv.org/abs/2003.12344v1 • [cs.CV]Towards Accurate Scene Text Recognition with Semantic Reasoning Networks Deli Yu, Xuan Li, Chengquan Zhang, Junyu Han, Jingtuo Liu, Errui Ding http://arxiv.org/abs/2003.12294v1 • [cs.CV]Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations Shuhao Cui, Shuhui Wang, Junbao Zhuo, Liang Li, Qingming Huang, Qi Tian http://arxiv.org/abs/2003.12237v1 • [cs.CV]Weakly Supervised Dataset Collection for Robust Person Detection Munetaka Minoguchi, Ken Okayama, Yutaka Satoh, Hirokatsu Kataoka http://arxiv.org/abs/2003.12263v1 • [cs.CV]Weakly-Supervised Action Localization by Generative Attention Modeling Baifeng Shi, Qi Dai, Yadong Mu, Jingdong Wang http://arxiv.org/abs/2003.12424v1 • [cs.CY]A Liquid Perspective on Democratic Choice Bryan Ford http://arxiv.org/abs/2003.12393v1 • [cs.CY]Democratic Value and Money for Decentralized Digital Society Bryan Ford http://arxiv.org/abs/2003.12375v1 • [cs.CY]Mobile phone data and COVID-19: Missing an opportunity? Nuria Oliver, Emmanuel Letouzé, Harald Sterly, Sébastien Delataille, Marco De Nadai, Bruno Lepri, Renaud Lambiotte, Richard Benjamins, Ciro Cattuto, Vittoria Colizza, Nicolas de Cordes, Samuel P. Fraiberger, Till Koebe, Sune Lehmann, Juan Murillo, Alex Pentland, Phuong N Pham, Frédéric Pivetta, Albert Ali Salah, Jari Saramäki, Samuel V. Scarpino, Michele Tizzoni, Stefaan Verhulst, Patrick Vinck http://arxiv.org/abs/2003.12347v1 • [cs.CY]On the Emerging Area of Biocybersecurity and Relevant Considerations Xavier-Lewis Palmer, Lucas Potter, Saltuk Karahan http://arxiv.org/abs/2003.12132v1 • [cs.DC]AI on the Edge: Rethinking AI-based IoT Applications Using Specialized Edge Architectures Qianlin Liang, Prashant Shenoy, David Irwin http://arxiv.org/abs/2003.12488v1 • [cs.DC]Algorithm-Based Fault Tolerance for Convolutional Neural Networks Kai Zhao, Sheng Di, Sihuan Li, Xin Liang, Yujia Zhai, Jieyang Chen, Kaiming Ouyang, Franck Cappello, Zizhong Chen http://arxiv.org/abs/2003.12203v1 • [cs.DC]Enabling Efficient and Flexible FPGA Virtualization for Deep Learning in the Cloud Shulin Zeng, Guohao Dai, Hanbo Sun, Kai Zhong, Guangjun Ge, Kaiyuan Guo, Yu Wang, Huazhong Yang http://arxiv.org/abs/2003.12101v1 • [cs.DC]Online and Real-time Object Tracking Algorithm with Extremely Small Matrices Jesmin Jahan Tithi, Sriram Aananthakrishnan, Fabrizio Petrini http://arxiv.org/abs/2003.12091v1 • [cs.ET]IMAC: In-memory multi-bit Multiplication andACcumulation in 6T SRAM Array Mustafa Ali, Akhilesh Jaiswal, Sangamesh Kodge, Amogh Agrawal, Indranil Chakraborty, Kaushik Roy http://arxiv.org/abs/2003.12558v1 • [cs.IT]A PHY Layer Security Analysis of a Hybrid High Throughput Satellite with an Optical Feeder Link Elmehdi Illi, Faissal El Bouanani, Fouad Ayoub, Mohamed-Slim Alouini http://arxiv.org/abs/2003.12358v1 • [cs.IT]Asymptotically Secure Network Code for Active Attacks and its Application to Network Quantum Key Distribution Masahito Hayashi, Ning Cai http://arxiv.org/abs/2003.12225v1 • [cs.IT]Bayes-Optimal Convolutional AMP Keigo Takeuchi http://arxiv.org/abs/2003.12245v1 • [cs.IT]Non-linearity of the Carlet-Feng function, and repartition of Gauss sums François Rodier http://arxiv.org/abs/2003.12491v1 • [cs.IT]On design-theoretic aspects of Boolean and vectorial bent functions Alexandr Polujan, Alexander Pott http://arxiv.org/abs/2003.12308v1 • [cs.IT]RANSAC-Based Signal Denoising Using Compressive Sensing Ljubisa Stankovic, Milos Brajovic, Isidora Stankovic, Jonatan Lerga, Milos Dakovic http://arxiv.org/abs/2003.12289v1 • [cs.IT]Secure network code over one-hop relay network Masahito Hayashi, Ning Cai http://arxiv.org/abs/2003.12223v1 • [cs.LG]A Collective Learning Framework to Boost GNN Expressiveness Mengyue Hang, Jennifer Neville, Bruno Ribeiro http://arxiv.org/abs/2003.12169v1 • [cs.LG]A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms Philip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare http://arxiv.org/abs/2003.12239v1 • [cs.LG]A Hybrid-Order Distributed SGD Method for Non-Convex Optimization to Balance Communication Overhead, Computational Complexity, and Convergence Rate Naeimeh Omidvar, Mohammad Ali Maddah-Ali, Hamed Mahdavi http://arxiv.org/abs/2003.12423v1 • [cs.LG]A Principled Approach to Learning Stochastic Representations for Privacy in Deep Neural Inference Fatemehsadat Mireshghallah, Mohammadkazem Taram, Ali Jalali, Ahmed Taha Elthakeb, Dean Tullsen, Hadi Esmaeilzadeh http://arxiv.org/abs/2003.12154v1 • [cs.LG]A copula-based visualization technique for a neural network Yusuke Kubo, Yuto Komori, Toyonobu Okuyama, Hiroshi Tokieda http://arxiv.org/abs/2003.12317v1 • [cs.LG]A light neural network for modulation detection under impairments Thomas Courtat, Hélion du Mas des Bourboux http://arxiv.org/abs/2003.12260v1 • [cs.LG]ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series Steven Elsworth, Stefan Güttel http://arxiv.org/abs/2003.12469v1 • [cs.LG]AirRL: A Reinforcement Learning Approach to Urban Air Quality Inference Huiqiang Zhong, Cunxiang Yin, Xiaohui Wu, Jinchang Luo, JiaWei He http://arxiv.org/abs/2003.12205v1 • [cs.LG]Distributed Kernel Ridge Regression with Communications Shao-Bo Lin, Di Wang, Ding-Xuan Zhou http://arxiv.org/abs/2003.12210v1 • [cs.LG]Financial Time Series Representation Learning Philippe Chatigny, Jean-Marc Patenaude, Shengrui Wang http://arxiv.org/abs/2003.12194v1 • [cs.LG]Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program) Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d’Alché-Buc, Emily Fox, Hugo Larochelle http://arxiv.org/abs/2003.12206v1 • [cs.LG]Incorporating Expert Prior in Bayesian Optimisation via Space Warping Anil Ramachandran, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh http://arxiv.org/abs/2003.12250v1 • [cs.LG]LIMP: Learning Latent Shape Representations with Metric Preservation Priors Luca Cosmo, Antonio Norelli, Oshri Halimi, Ron Kimmel, Emanuele Rodolà http://arxiv.org/abs/2003.12283v1 • [cs.LG]Learning To Solve Differential Equations Across Initial Conditions Shehryar Malik, Usman Anwar, Ali Ahmed, Alireza Aghasi http://arxiv.org/abs/2003.12159v1 • [cs.LG]Learning representations in Bayesian Confidence Propagation neural networks Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman http://arxiv.org/abs/2003.12415v1 • [cs.LG]Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment Ben Usman, Nick Dufour, Avneesh Sud, Kate Saenko http://arxiv.org/abs/2003.12170v1 • [cs.LG]MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation Chaoyang He, Haishan Ye, Li Shen, Tong Zhang http://arxiv.org/abs/2003.12238v1 • [cs.LG]On a minimum enclosing ball of a collection of linear subspaces Timothy Marrinan, P. -A. Absil, Nicolas Gillis http://arxiv.org/abs/2003.12455v1 • [cs.LG]On the Optimization Dynamics of Wide Hypernetworks Etai Littwin, Tomer Galanti, Lior Wolf http://arxiv.org/abs/2003.12193v1 • [cs.LG]Optimization of genomic classifiers for clinical deployment: evaluation of Bayesian optimization for identification of predictive models of acute infection and in-hospital mortality Michael B. Mayhew, Elizabeth Tran, Kirindi Choi, Uros Midic, Roland Luethy, Nandita Damaraju, Ljubomir Buturovic http://arxiv.org/abs/2003.12310v1 • [cs.LG]Piecewise linear activations substantially shape the loss surfaces of neural networks Fengxiang He, Bohan Wang, Dacheng Tao http://arxiv.org/abs/2003.12236v1 • [cs.LG]Progressive Graph Convolutional Networks for Semi-Supervised Node Classification Negar Heidari, Alexandros Iosifidis http://arxiv.org/abs/2003.12277v1 • [cs.LG]Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning Andreas Kirsch, Clare Lyle, Yarin Gal http://arxiv.org/abs/2003.12537v1 • [cs.LG]Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks Bernardo Pérez Orozco, Stephen J Roberts http://arxiv.org/abs/2003.12162v1 • [cs.MM]Unsupervised Cross-Modal Audio Representation Learning from Unstructured Multilingual Text Alexander Schindler, Sergiu Gordea, Peter Knees http://arxiv.org/abs/2003.12265v1 • [cs.NE]Bayesian Hierarchical Multi-Objective Optimization for Vehicle Parking Route Discovery Romit S Beed, Sunita Sarkar, Arindam Roy http://arxiv.org/abs/2003.12508v1 • [cs.NE]Boolean learning under noise-perturbations in hardware neural networks Louis Andreoli, Xavier Porte, Stéphane Chrétien, Maxime Jacquot, Laurent Larger, Daniel Brunner http://arxiv.org/abs/2003.12319v1 • [cs.NI]A Survey on Edge Intelligence Dianlei Xu, Tong Li, Yong Li, Xiang Su, Sasu Tarkoma, Pan Hui http://arxiv.org/abs/2003.12172v1 • [cs.RO]Implementation of Survivor Detection Strategies Using Drones Sarthak J. Shetty, Rahul Ravichandran, Lima Agnel Tony, N. Sai Abhinay, Kaushik Das, Debasish Ghose http://arxiv.org/abs/2003.12559v1 • [cs.RO]Metrics and Optimization of Internal Poses for Highly Redundant Truss-Like Serialized Parallel Manipulators William Chapin, Erik Komendera http://arxiv.org/abs/2003.12144v1 • [cs.RO]Representing Multi-Robot Structure through Multimodal Graph Embedding for the Selection of Robot Teams Brian Reily, Christopher Reardon, Hao Zhang http://arxiv.org/abs/2003.12164v1 • [cs.RO]Towards Autonomous Industrial-Scale Bathymetric Surveying Ignacio Torrobam Nils Bore, John Folkesson http://arxiv.org/abs/2003.12471v1 • [cs.SI]$α$-Satellite: An AI-driven System and Benchmark Datasets for Hierarchical Community-level Risk Assessment to Help Combat COVID-19 Yanfang Ye, Shifu Hou, Yujie Fan, Yiyue Qian, Yiming Zhang, Shiyu Sun, Qian Peng, Kenneth Laparo http://arxiv.org/abs/2003.12232v1 • [cs.SI]Coronavirus on Social Media: Analyzing Misinformation in Twitter Conversations Karishma Sharma, Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Aastha Dua, Yan Liu http://arxiv.org/abs/2003.12309v1 • [cs.SI]Shortest Paths in Complex Networks: Structure and Optimization Guilherme S. Domingues, Cesar H. Comin, Luciano da F. Costa http://arxiv.org/abs/2003.12180v1 • [econ.EM]Sequential monitoring for cointegrating regressions Lorenzo Trapani, Emily Whitehouse http://arxiv.org/abs/2003.12182v1 • [eess.AS]Can you hear me $\textit{now}$? Sensitive comparisons of human and machine perception Michael A Lepori, Chaz Firestone http://arxiv.org/abs/2003.12362v1 • [eess.AS]Mic2Mic: Using Cycle-Consistent Generative Adversarial Networks to Overcome Microphone Variability in Speech Systems Akhil Mathur, Anton Isopoussu, Fahim Kawsar, Nadia Berthouze, Nicholas D. Lane http://arxiv.org/abs/2003.12425v1 • [eess.AS]Separating Varying Numbers of Sources with Auxiliary Autoencoding Loss Yi Luo, Nima Mesgarani http://arxiv.org/abs/2003.12326v1 • [eess.IV]A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks Xiaomin Zhou, Chen Li, Md Mamunur Rahaman, Yudong Yao, Shiliang Ai, Changhao Sun, Xiaoyan Li, Qian Wang, Tao Jiang http://arxiv.org/abs/2003.12255v1 • [eess.IV]Augmenting Colonoscopy using Extended and Directional CycleGAN for Lossy Image Translation Shawn Mathew, Saad Nadeem, Arie Kaufman http://arxiv.org/abs/2003.12473v1 • [eess.IV]COVID-19 Screening on Chest X-ray Images Using Deep Learning based Anomaly Detection Jianpeng Zhang, Yutong Xie, Yi Li, Chunhua Shen, Yong Xia http://arxiv.org/abs/2003.12338v1 • [eess.SP]Bayesian Sequential Joint Detection and Estimation under Multiple Hypotheses Dominik Reinhard, Michael Fauß, Abdelhak M. Zoubir http://arxiv.org/abs/2003.12405v1 • [eess.SP]Distributed Caching for Data Dissemination in the Downlink of Heterogeneous Networks Jun Li, Youjia Chen, Zihuai Lin, Wen Chen, Branka Vucetic, Lajos Hanzo http://arxiv.org/abs/2003.12215v1 • [eess.SY]Closed-loop Parameter Identification of Linear Dynamical Systems through the Lens of Feedback Channel Coding Theory Ali Reza Pedram, Takashi Tanaka http://arxiv.org/abs/2003.12548v1 • [math.ST]Quantifying deviations from separability in space-time functional processes Holger Dette, Gauthier Dierickx, Tim Kutta http://arxiv.org/abs/2003.12126v1 • [math.ST]Seemingly unrelated and fixed-effect panel regressions: collinearity and singular dispersion Harry Haupt http://arxiv.org/abs/2003.12321v1 • [math.ST]Tests and estimation strategies associated to some loss functions Yannick Baraud http://arxiv.org/abs/2003.12544v1 • [physics.ins-det]Using Machine Learning to Speed Up and Improve Calorimeter R&D Fedor Ratnikov http://arxiv.org/abs/2003.12440v1 • [physics.soc-ph]The Network Dynamics of Social and Technological Conventions Joshua Becker http://arxiv.org/abs/2003.12112v1 • [stat.AP]Separable and Semiparametric Network-based Counting Processes applied to the International Combat Aircraft Trades Cornelius Fritz, Paul W. Thurner, Göran Kauermann http://arxiv.org/abs/2003.12178v1 • [stat.CO]Online Smoothing for Diffusion Processes Observed with Noise Shouto Yonekura, Alexandros Beskos http://arxiv.org/abs/2003.12247v1 • [stat.ME]A super scalable algorithm for short segment detection Ning Hao, Yue Selena Niu, Feifei Xiao, Heping Zhang http://arxiv.org/abs/2003.12540v1 • [stat.ME]Data Integration by combining big data and survey sample data for finite population inference Jae-kwang Kim, Siu-Ming Tam http://arxiv.org/abs/2003.12156v1 • [stat.ME]Enriched Pitman-Yor processes Tommaso Rigon, Bruno Scarpa, Sonia Petrone http://arxiv.org/abs/2003.12200v1 • [stat.ME]Post-sampling crowdsourced data to allow reliable statistical inference: the case of food price indices in Nigeria Giuseppe Arbia, Gloria Solano-Hermosilla, Fabio Micale, Vincenzo Nardelli, Giampiero Genovese http://arxiv.org/abs/2003.12542v1 • [stat.ME]Robust Q-learning Ashkan Ertefaie, James R. McKay, David Oslin, Robert L. Strawderman http://arxiv.org/abs/2003.12427v1 • [stat.ME]Transition Models for Count Data: a Flexible Alternative to Fixed Distribution Models Moritz Berger, Gerhard Tutz http://arxiv.org/abs/2003.12411v1 • [stat.ML]Gaussian-Dirichlet Random Fields for Inference over High Dimensional Categorical Observations John E. San Soucie, Heidi M. Sosik, Yogesh Girdhar http://arxiv.org/abs/2003.12120v1 • [stat.ML]Gryffin: An algorithm for Bayesian optimization for categorical variables informed by physical intuition with applications to chemistry Florian Häse, Loïc M. Roch, Alán Aspuru-Guzik http://arxiv.org/abs/2003.12127v1 • [stat.ML]On the role of surrogates in the efficient estimation of treatment effects with limited outcome data Nathan Kallus, Xiaojie Mao http://arxiv.org/abs/2003.12408v1 • [stat.ML]Sorting Big Data by Revealed Preference with Application to College Ranking Xingwei Hu http://arxiv.org/abs/2003.12198v1
若有收获，就点个赞吧
0 人点赞
