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
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• [
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