首页>外文会议>IEEE Data Science Workshop

IEEE Data Science Workshop

召开年：2019
召开地：Minneapolis(US)
出版时间：-

会议文集：-

会议论文

热门论文

全部论文

全选（0）

1.Graphical Models and Dynamic Latent Factors for Modeling Functional Brain Connectivity

机译：建模功能性大脑连接性的图形模型和动态潜在因素
- 作者：Andersen Chang;Tianyi Yao;Genevera I. Allen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- brain;
- Gaussian processes;
- neurophysiology;
2.Time-Varying Interaction Estimation Using Ensemble Methods

机译：集成方法的时变交互估计
- 作者：Brandon Oselio;Alfred Hero;Amir Sadeghian;Silvio Savarese
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data analysis;
- learning (artificial intelligence);
3.Clustered Gaussian Graphical Model Via Symmetric Convex Clustering

机译：通过对称凸聚类聚类高斯图形模型
- 作者：Tianyi Yao;Genevera I. Allen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- convex programming;
- Gaussian processes;
- medical computing;
- neurophysiology;
- optimisation;
- pattern clustering;
4.Simultaneous Multivariate Outlier and Trend Detection

机译：同时多元离群值和趋势检测
- 作者：Karl Pazdernik;Bryan Stanfill;Lisa Bramer;Kellie J. MacPhee
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data handling;
- matrix algebra;
- principal component analysis;
- regression analysis;
5.Learning to Regularize Using Neumann Networks

机译：学习使用Neumann网络进行正则化
- 作者：Davis Gilton;Greg Ongie;Rebecca Willett
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- image processing;
- inverse problems;
- learning (artificial intelligence);
6.Recovery of Missing Data in Correlated Smart Grid Datasets

机译：恢复相关智能电网数据集中的丢失数据
- 作者：Cristian Genes;Iñaki Esnaola;Samir M. Perlaza;Daniel Coca
- 会议名称：《IEEE Data Science Workshop》 | 2019年
7.GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized Optimization

机译：GNSD：用于分散优化的基于梯度跟踪的非凸随机算法
- 作者：Songtao Lu;Xinwei Zhang;Haoran Sun;Mingyi Hong
- 会议名称：《IEEE Data Science Workshop》 | 2019年
8.Enhancing Medical Imaging Semantic Segmentation Using the Digital Annealer

机译：使用数字退火仪增强医学成像语义分割
- 作者：Jiankun Wang;Shahrokh Valaee
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- computer vision;
- convolutional neural nets;
- image resolution;
- image segmentation;
- medical image processing;
- random processes;
9.A Convolutional Neural Network Approach to Automated Lung Bounding Box Estimation from Computed Tomography Scans

机译：卷积神经网络方法从计算机断层扫描中自动估计肺边界
- 作者：Charles R. Hatt;Sundaresh Ram;Craig J. Galban
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- computerised tomography;
- lung;
- medical image processing;
- neural nets;
10.Long-Range Dependence Parameter Estimation For Mixed Spectra Gaussian Processes

机译：混合谱高斯过程的远程相关参数估计
- 作者：Lenin Arango-Castillo;Glen Takahara
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- decomposition;
- Gaussian noise;
- harmonic analysis;
- iterative methods;
- parameter estimation;
- time series;
11.Structural Robustness for Deep Learning Architectures

机译：深度学习架构的结构稳健性
- 作者：Carlos Lassance;Vincent Gripon;Jian Tang;Antonio Ortega
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- learning (artificial intelligence);
12.Online selective training for faster neural network learning

机译：在线选择性训练可加快神经网络学习速度
- 作者：Sara Mourad;Haris Vikalo;Ahmed Tewfik
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data handling;
- learning (artificial intelligence);
- neural nets;
13.Online Tensor Decomposition and Imputation for Count Data

机译：在线张量分解和计数数据插补
- 作者：Chang Ye;Gonzalo Mateos
- 会议名称：《IEEE Data Science Workshop》 | 2019年
14.Introducing Graph Smoothness Loss for Training Deep Learning Architectures

机译：介绍图平滑度损失以训练深度学习架构
- 作者：Myriam Bontonou;Carlos Lassance;Ghouthi Boukli Hacene;Vincent Gripon;Jian Tang;Jian Tang
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- entropy;
- graph theory;
- learning (artificial intelligence);
- pattern classification;
15.Randomized Algorithms for Data-Driven Stabilization of Stochastic Linear Systems

机译：随机线性系统数据驱动镇定的随机算法
- 作者：Mohamad Kazem Shirani Faradonbeh;Ambuj Tewari;George Michailidis
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- control system synthesis;
- feedback;
- linear systems;
- probability;
- randomised algorithms;
- stability;
- stochastic processes;
- stochastic systems;
- uncertain systems;
16.Learning to Detect an Anomalous Target with Observations from an Exponential Family

机译：学习从指数家族的观察中检测异常目标
- 作者：Gayathri R Prabhu;Srikrishna Bhashyam;Aditya Gopalan;Rajesh Sundaresan
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- decision making;
- maximum likelihood estimation;
- statistical distributions;
17.Bayesian Multiple Hypothesis Testing For Distributed Detection In Sensor Networks

机译：传感器网络中分布式检测的贝叶斯多重假设检验
- 作者：Topi Halme;Martin Gölz;Visa Koivunen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- Bayes methods;
- statistical analysis;
- wireless sensor networks;
18.A Stochastic LBFGS Algorithm for Radio Interferometric Calibration

机译：用于无线电干涉校准的随机LBFGS算法
- 作者：Sarod Yatawatta;Lukas De Clercq;Hanno Spreeuw;Faruk Diblen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
19.Generalized Jordan Center: A Source Localization Heuristic For Noisy And Incomplete Observations

机译：广义约旦中心：噪声和不完整观测值的源本地化启发式方法
- 作者：Huozhi Zhou;Ashish Jagmohan;Lav R. Varshney
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- computational complexity;
- directed graphs;
- maximum likelihood estimation;
20.Data Driven Measurement Matrix Learning for Sparse Reconstruction

机译：稀疏重建的数据驱动测量矩阵学习
- 作者：Robiul Hossain Md. Rafi;Ali Cafer Gurbuz
- 会议名称：《IEEE Data Science Workshop》 | 2019年
21.Learning to Infer Voltage Stability Margin Using Transfer Learning

机译：学习使用转移学习来推断电压稳定裕度
- 作者：Jiaming Li;Yue Zhao;Young-hwan Lee;Seung-Jun Kim
- 会议名称：《IEEE Data Science Workshop》 | 2019年
22.Data-Driven Mean-Field Game Approximation for a Population of Electric Vehicles

机译：电动汽车的数据驱动平均场博弈近似
- 作者：D. Bauso;T. Namerikawa
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- electric vehicles;
- game theory;
- stochastic processes;
23.Stochastic Optimization for Coupled Tensor Decomposition with Applications in Statistical Learning

机译：张量分解的随机优化及其在统计学习中的应用
- 作者：Shahana Ibrahim;Xiao Fu
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data analysis;
- gradient methods;
- learning (artificial intelligence);
- matrix decomposition;
- optimisation;
- probability;
- statistical analysis;
- stochastic processes;
- tensors;
24.Recent Numerical and Conceptual Advances for Tensor Decompositions — A Preview of Tensorlab 4.0

机译：Tensor分解的最新数值和概念进展-Tensorlab 4.0的预览
- 作者：Nico Vervliet;Michiel Vandecappelle;Martijn Boussé;Rob Zink;Lieven De Lathauwer
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- graphical user interfaces;
- mathematics computing;
- Newton method;
- tensors;
25.Byzantine-Robust Stochastic Gradient Descent for Distributed Low-Rank Matrix Completion

机译：分布式低秩矩阵完成的拜占庭-鲁布斯随机梯度下降
- 作者：Xuechao He;Qing Ling;Tianyi Chen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data privacy;
- gradient methods;
- learning (artificial intelligence);
- matrix decomposition;
- recommender systems;
- stochastic processes;
26.Blind Ensemble Classification of Sequential Data

机译：序列数据的盲集合分类
- 作者：Panagiotis A. Traganitis
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- hidden Markov models;
- learning (artificial intelligence);
- pattern classification;
27.Online Topology Inference from Streaming Stationary Graph Signals

机译：流固定图信号的在线拓扑推断
- 作者：Rasoul Shafipour;Abolfazl Hashemi;Gonzalo Mateos;Haris Vikalo
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- eigenvalues and eigenfunctions;
- graph theory;
- inference mechanisms;
- iterative methods;
- matrix algebra;
- signal processing;
28.The Core Consistency of a Compressed Tensor

机译：压缩张量的核心一致性
- 作者：Georgios Tsitsikas;Evangelos E. Papalexakis
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data compression;
- matrix decomposition;
- sparse matrices;
- tensors;
29.Supervised Principal Component Analysis Via Manifold Optimization

机译：通过流形优化进行监督的主成分分析
- 作者：Alexander Ritchie;Clayton Scott;Laura Balzano;Daniel Kessler;Chandra S. Sripada
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- optimisation;
- pattern classification;
- principal component analysis;
- regression analysis;
30.Vertex-Frequency Clustering

机译：顶点频率聚类
- 作者：Daniel B. Burkhardt;Jay S. Stanley;Guy Wolf;Smita Krishnaswamy
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- graph theory;
- pattern clustering;
31.Sampling of Graph Signals with Blue Noise Dithering

机译：具有蓝噪声抖动的图形信号采样
- 作者：Alejandro Parada-Mayorga;Daniel L. Lau;Jhony H. Giraldo;Gonzalo R. Arce
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- graph theory;
- sampling methods;
- signal sampling;
32.Distance-Penalized Active Learning via Markov Decision Processes

机译：马尔可夫决策过程的距离惩罚主动学习
- 作者：Dingyu Wang;John Lipor;Gautam Dasarathy
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- learning (artificial intelligence);
- Markov processes;
- pattern classification;
- search problems;
33.Localization of Data Injection Attacks on Distributed M-Estimation

机译：分布式M估计的数据注入攻击的本地化
- 作者：Or Shalom;Amir Leshem;Anna Scaglione
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- estimation theory;
- security of data;
- statistical analysis;
34.Online Distributed Estimation of Principal Eigenspaces

机译：主特征空间的在线分布式估计
- 作者：Davoud Ataee Tarzanagh;Mohamad Kazem Shirani Faradonbeh;George Michailidis
- 会议名称：《IEEE Data Science Workshop》 | 2019年
35.Coke: Communication-Censored Kernel Learning Via Random Features

机译：可乐：通过随机特征进行通信审查的内核学习
- 作者：Ping Xu;Zhi Tian;Zhe Zhang;Yue Wang
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- approximation theory;
- learning (artificial intelligence);
- optimisation;
36.Distributed Training with Mobile Agents: Optimization Over Dynamic Directed Graphs

机译：使用移动代理进行分布式培训：动态有向图的优化
- 作者：Fakhteh Saadatniaki;Ran Xin;Usman A. Khan
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- convergence;
- convex programming;
- directed graphs;
- distributed algorithms;
- matrix algebra;
- mobile agents;
- telecommunication computing;
- wireless sensor networks;
37.Gradient Coding with Clustering and Multi-Message Communication

机译：聚类和多消息通信的梯度编码
- 作者：Emre Ozfatura;Deniz Gündüz;Sennur Ulukus
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- distributed processing;
- expectation-maximisation algorithm;
- gradient methods;
- iterative methods;
- pattern clustering;
38.Optimal Sampling Sets in Cographs

机译：Cograph中的最佳采样集
- 作者：Dominique Guillot;Alejandro Parada-Mayorga;Sebastian Cioaba;Gonzalo R. Arce
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- bandlimited signals;
- computational complexity;
- optimisation;
- signal reconstruction;
- signal sampling;
- trees (mathematics);
39.Multitaper Analysis of Evolutionary Spectral Density Matrix From Multivariate Spiking Observations

机译：基于多变量峰值观测的演化谱密度矩阵的多锥度分析
- 作者：Anuththara Rupasinghe;Behtash Babadi
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- brain;
- cognition;
- maximum likelihood estimation;
- neurophysiology;
- statistical analysis;
- stochastic processes;
- time series;
40.Graph Topology Learning and Signal Recovery Via Bayesian Inference

机译：通过贝叶斯推理进行图拓扑学习和信号恢复
- 作者：Mahmoud Ramezani-Mayiami;Mohammad Hajimirsadeghi;Karl Skretting;Rick S. Blum;H. Vincent Poor
- 会议名称：《IEEE Data Science Workshop》 | 2019年
41.Semi-Supervised Tracking of Dynamic Processes Over Switching Graphs

机译：切换图上动态过程的半监督跟踪
- 作者：Qin Lu;Vassilis N. Ioannidis;Georgios B. Giannakis
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- Bayes methods;
- brain;
- graph theory;
42.Kernel-Based Efficient Lifelong Learning Algorithm

机译：基于内核的高效终身学习算法
- 作者：Seung-Jun Kim;Rami Mowakeaa
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- Hilbert spaces;
- learning (artificial intelligence);
- pattern classification;
43.Non-Negative Matrix Factorization of Clustered Data with Missing Values

机译：缺失值的聚类数据的非负矩阵分解
- 作者：Rebecca Chen;Lav R. Varshney
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- approximation theory;
- matrix decomposition;
- pattern clustering;
44.Estimation of State-Space Models with Gaussian Mixture Process Noise

机译：高斯混合过程噪声的状态空间模型估计
- 作者：Sina Miran;Jonathan Z. Simon;Michael C. Fu;Steven I. Marcus;Behtash Babadi
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- expectation-maximisation algorithm;
- Gaussian processes;
- Monte Carlo methods;
- state-space methods;
45.Scalable Learning with Privacy Over Graphs

机译：通过图隐私实现可扩展的学习
- 作者：Yanning Shen;Geert Leus
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- cryptography;
- data privacy;
- graph theory;
- large-scale systems;
- learning (artificial intelligence);
- social networking (online);
46.Rumour Detection Via News Propagation Dynamics and User Representation Learning

机译：通过新闻传播动力学和用户表示学习进行谣言检测
- 作者：Tien Huu Do;Xiao Luo;Duc Minh Nguyen;Nikos Deligiannis
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- learning (artificial intelligence);
- social networking (online);
- social sciences computing;
47.Deep One-Class Classification Using Intra-Class Splitting

机译：使用类内分割进行深度一类分类
- 作者：Patrick Schlachter;Yiwen Liao;Bin Yang
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- image classification;
- learning (artificial intelligence);
- neural nets;
48.Lfinite Sample Bounds on the Performance of Weighted Linear Least Squares in Sub-Gaussian Correlated Noise

机译：次高斯相关噪声中加权线性最小二乘性能的有限样本界
- 作者：Michael Krikheli;Amir Leshem
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- convergence;
- Gaussian processes;
- least squares approximations;
- mean square error methods;
- probability;
49.Dynamic Functional Connectivity Using Heat Kernel

机译：使用热内核的动态功能连接
- 作者：Shih-Gu Huang;Moo K. Chung;Ian C. Carroll;H. Hill Goldsmith
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- biomedical MRI;
- brain;
- data acquisition;
- Gaussian processes;
- medical image processing;
50.Multispectral Snapshot Demosaicing Via Non-Convex Matrix Completion

机译：通过非凸矩阵完成的多光谱快照去马赛克
- 作者：Giancarlo A. Antonucci;Simon Vary;David Humphreys;Robert A. Lamb;Jonathan Piper;Jared Tanner
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- approximation theory;
- concave programming;
- image reconstruction;
- image resolution;
- image segmentation;
- image sensors;
- matrix algebra;
51.Classification of Hyperspectral Colon Cancer Images Using Convolutional Neural Networks

机译：利用卷积神经网络对高光谱结肠癌图像进行分类
- 作者：Sean Mobilia;Birsen Sirkeci-Mergen;Joshua Deal;Thomas C. Rich;Silas J. Leavesley
- 会议名称：《IEEE Data Science Workshop》 | 2019年
52.Online Sparse Subspace Clustering

机译：在线稀疏子空间聚类
- 作者：Liam Madden;Stephen Becker;Emiliano Dall’Anese
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- Internet;
- matrix algebra;
- optimisation;
- pattern clustering;
- time-varying systems;
53.Distribution System State Estimation Via Data-Driven and Physics-Aware Deep Neural Networks

机译：通过数据驱动和物理感知的深度神经网络进行配电系统状态估计
- 作者：Liang Zhang;Gang Wang;Georgios B. Giannakis
- 会议名称：《IEEE Data Science Workshop》 | 2019年
54.On Modeling Voltage Phasor Measurements as Graph Signals

机译：关于将电压相量测量建模为图形信号的研究
- 作者：Raksha Ramakrishna;Anna Scaglione
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- graph theory;
- low-pass filters;
- phasor measurement;
- power grids;
- signal processing;
- voltage measurement;
55.Assessing the Resilience of the Texas Power Grid Network

机译：评估德克萨斯电网的弹性
- 作者：Dorcas Ofori-Boateng;Asim Kumer Dey;Yulia R. Gel;Binghui Li;Jie Zhang;H. Vincent Poor
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data analysis;
- power engineering computing;
- power grids;
- power system management;
56.Statistical Learning Using Hierarchical Modeling of Probability Tensors

机译：使用概率张量的分层建模进行统计学习
- 作者：Magda Amiridi;Nikos Kargas;Nicholas D. Sidiropoulos
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data handling;
- learning (artificial intelligence);
- matrix decomposition;
- statistical distributions;
- tensors;
57.Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic Decomposition

机译：使用耦合规范多态分解学习部分可观察的马尔可夫决策过程
- 作者：Kejun Huang;Zhuoran Yang;Zhaoran Wang;Mingyi Hong
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- identification;
- learning (artificial intelligence);
- Markov processes;
- matrix decomposition;
- modelling;
- tensors;
58.Canonical Polyadic (CP) Decomposition of Structured Semi-Symmetric Fourth-Order Tensors

机译：结构化的半对称四阶张量的规范多峰（CP）分解
- 作者：Ali Koochakzadeh;Piya Pal
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- computational complexity;
- geometry;
- matrix algebra;
- tensors;
59.Deep Mimo Detection Using ADMM Unfolding

机译：使用ADMM展开进行深度Mimo检测
- 作者：Man-Wai Un;Mingjie Shao;Wing-Kin Ma;P. C. Ching
- 会议名称：《IEEE Data Science Workshop》 | 2019年
60.Comprehensive Personalized Ranking Using One-Bit Comparison Data

机译：使用一位比较数据进行全面的个性化排名
- 作者：Aria Ameri;Arindam Bose;Mojtaba Soltanalian
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- Bayes methods;
- learning (artificial intelligence);
- matrix decomposition;
- optimisation;
- recommender systems;
61.Asynchronous Distributed Edge-Variant Graph Filters

机译：异步分布式边变图滤波器
- 作者：Mario Coutino;Geert Leus
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- convergence of numerical methods;
- graph theory;
- wireless sensor networks;
62.A Hierarchical Approach for Timely Cyberbullying Detection

机译：实时网络欺凌检测的分层方法
- 作者：Imara Nazar;Daphney-Stavroula Zois;Mengfan Yao
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- Bayes methods;
- feature extraction;
- social networking (online);
63.Splitting Methods For Convex Bi-Clustering And Co-Clustering

机译：凸双聚类和共聚的拆分方法
- 作者：Michael Weylandt
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- convex programming;
- mathematical operators;
- pattern clustering;
- tensors;
64.Sparse and Functional Principal Components Analysis

机译：稀疏和功能主成分分析
- 作者：Genevera I. Allen;Michael Weylandt
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- brain;
- electroencephalography;
- principal component analysis;
65.Training Generative Networks Using Random Discriminators

机译：使用随机判别器训练生成网络
- 作者：Babak Barazandeh;Meisam Razaviyayn;Maziar Sanjabi
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- concave programming;
- game theory;
- learning (artificial intelligence);
- minimax techniques;
66.Learning to Regularize Using Neumann Networks

机译：学习使用Neumann网络进行规范
- 作者：Davis Gilton;Greg Ongie;Rebecca Willett
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- image processing;
- inverse problems;
- learning (artificial intelligence);
67.GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized Optimization

机译：GNSD：一种基于梯度跟踪的分散优化的非透视随机算法
- 作者：Songtao Lu;Xinwei Zhang;Haoran Sun;Mingyi Hong
- 会议名称：《IEEE Data Science Workshop》 | 2019年
68.Graphical Models and Dynamic Latent Factors for Modeling Functional Brain Connectivity

机译：用于建模功能性脑连接的图形模型和动态潜在因子
- 作者：Andersen Chang;Tianyi Yao;Genevera I. Allen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- brain;
- Gaussian processes;
- neurophysiology;
69.Enhancing Medical Imaging Semantic Segmentation Using the Digital Annealer

机译：使用Digital Innever增强医学成像语义分割
- 作者：Jiankun Wang;Shahrokh Valaee
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- computer vision;
- convolutional neural nets;
- image resolution;
- image segmentation;
- medical image processing;
- random processes;
70.MOTIFNET: A MOTIF-BASED GRAPH CONVOLUTIONAL NETWORK FOR DIRECTED GRAPHS

机译：Motifnet：基于主题的图形卷积网络，用于定向图
- 作者：Federico Monti;Karl Otness;Michael M. Bronstein
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Laplace equations;
- Machine learning;
- Symmetric matrices;
- Eigenvalues and eigenfunctions;
- Neural networks;
- Chebyshev approximation;
- Color;
71.RESTRICTED ISOMETRY PROPERTY FOR LOW-DIMENSIONAL SUBSPACES AND ITS APPLICATION IN COMPRESSED SUBSPACE CLUSTERING

机译：用于低维子空间的受限制的等距属性及其在压缩子空间聚类中的应用
- 作者：Gen Li;Qinghua Liu;Yuantao Gu
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Signal processing algorithms;
- Clustering algorithms;
- Solids;
- Clustering methods;
- Sparse matrices;
- Measurement;
- Signal processing;
72.LEARNING TO INFER POWER GRID TOPOLOGIES: PERFORMANCE AND SCALABILITY

机译：学习推断电网拓扑：性能和可扩展性
- 作者：Yue Zhao;Jianshu Chen;H. Vincent Poor
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Topology;
- Network topology;
- Real-time systems;
- Data models;
- Training;
- Voltage measurement;
- Power measurement;
73.DIVIDE-AND-CONQUER TOMOGRAPHY FOR LARGE-SCALE NETWORKS

机译：用于大型网络的分割和征服断层扫描
- 作者：Augusto Santos;Vincenzo Matta;Ali H. Sayed
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Tomography;
- Network topology;
- Topology;
- Peer-to-peer computing;
- Symmetric matrices;
- Neurons;
- Data mining;
74.SAVE - SPACE ALTERNATING VARIATIONAL ESTIMATION FOR SPARSE BAYESIAN LEARNING

机译：节省 - 稀疏贝叶斯学习的空间交替变分估计
- 作者：Christo Kurisummoottil Thomas;Dirk Slock
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Bayes methods;
- Approximation algorithms;
- Convergence;
- Message passing;
- Matching pursuit algorithms;
- Estimation;
75.PROFIT MAXIMIZING LOGISTIC REGRESSION MODELING FOR CREDIT SCORING

机译：利润最大化信用评分的逻辑回归建模
- 作者：Arnout Devos;Jakob Dhondt;Eugen Stripling;Bart Baesens;Seppe vanden Broucke;Gaurav Sukhatme
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Logistics;
- Computational modeling;
- Data models;
- Genetic algorithms;
- Measurement;
- Maximum likelihood estimation;
76.AN EXPONENTIALLY CONVERGENT ALGORITHM FOR LEARNING UNDER DISTRIBUTED FEATURES

机译：分布式特征下学习的指数收敛算法
- 作者：Bicheng Ying;Kun Yuan;Ali H. Sayed
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Heuristic algorithms;
- Indexes;
- Convergence;
- Pipelines;
- Optimization;
- Convex functions;
- Approximation algorithms;
77.ALTERNATING AUTOENCODERS FOR MATRIX COMPLETION

机译：用于矩阵完成的交替的AutoEncoders
- 作者：Kiwon Lee;Yong H. Lee;Changho Suh
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Decoding;
- Sparse matrices;
- Training;
- Collaboration;
- Heuristic algorithms;
- Machine learning;
- Estimation;
78.VECTOR COMPRESSION FOR SIMILARITY SEARCH USING MULTI-LAYER SPARSE TERNARY CODES

机译：使用多层稀疏三元代码的相似性搜索矢量压缩
- 作者：Sohrab Ferdowsi;Slava Voloshynovskiy;Dimche Kostadinov
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Distortion;
- Rate-distortion;
- Databases;
- Channel coding;
- Image coding;
- Image reconstruction;
79.MULTI-SCALE ALGORITHMS FOR OPTIMAL TRANSPORT

机译：用于最佳运输的多尺度算法
- 作者：Bernhard Schmitzer
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Robustness;
- Entropy;
- Measurement;
- Approximation algorithms;
- Machine learning algorithms;
- Tools;
- Image processing;
80.AIM: AN ABSTRACTION FOR IMPROVING MACHINE LEARNING PREDICTION

机译：目的：改进机器学习预测的抽象
- 作者：Victoria Stodden;Xiaomian Wu;Vanessa Sochat
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Pipelines;
- Feature extraction;
- Machine learning;
- Cancer;
- Containers;
- Predictive models;
- Data models;
81.ON GRAPH CONVOLUTION FOR GRAPH CNNS

机译：关于图表CNN的图表卷积
- 作者：Jian Du;John Shi;Soummya Kar;José M. F. Moura
- 会议名称：《IEEE Data Science Workshop》 | 2018年
82.COMPUTATIONAL STRATEGIES FOR STATISTICAL INFERENCE BASED ON EMPIRICAL OPTIMAL TRANSPORT

机译：基于经验最优运输的统计推理计算策略
- 作者：Carla Tameling;Axel Munk
- 会议名称：《IEEE Data Science Workshop》 | 2018年
- Limiting;
- Upper bound;
- Task analysis;
- Extraterrestrial measurements;
- Bridges;
- Computational modeling;
83.A Convolutional Neural Network Approach to Automated Lung Bounding Box Estimation from Computed Tomography Scans

机译：从计算机断层扫描扫描的自动肺边界折叠估算卷积神经网络方法
- 作者：Charles R. Hatt;Sundaresh Ram;Craig J. Galban
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- computerised tomography;
- lung;
- medical image processing;
- neural nets;
84.Online Tensor Decomposition and Imputation for Count Data

机译：在线张量分解和计数数据的归纳
- 作者：Chang Ye;Gonzalo Mateos
- 会议名称：《IEEE Data Science Workshop》 | 2019年
85.Randomized Algorithms for Data-Driven Stabilization of Stochastic Linear Systems

机译：随机线性系统数据驱动稳定的随机算法
- 作者：Mohamad Kazem Shirani Faradonbeh;Ambuj Tewari;George Michailidis
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- control system synthesis;
- feedback;
- linear systems;
- probability;
- randomised algorithms;
- stability;
- stochastic processes;
- stochastic systems;
- uncertain systems;
86.Data-Driven Mean-Field Game Approximation for a Population of Electric Vehicles

机译：电动汽车群体的数据驱动均值近似
- 作者：D. Bauso;T. Namerikawa
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- electric vehicles;
- game theory;
- stochastic processes;
87.Recent Numerical and Conceptual Advances for Tensor Decompositions — A Preview of Tensorlab 4.0

机译：张量分解的近期数值和概念前进 - Tensorlab 4.0的预览
- 作者：Nico Vervliet;Michiel Vandecappelle;Martijn Boussé;Rob Zink;Lieven De Lathauwer
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- graphical user interfaces;
- mathematics computing;
- Newton method;
- tensors;
88.Generalized Jordan Center: A Source Localization Heuristic For Noisy And Incomplete Observations

机译：广义乔丹中心：噪声和不完整观察的源头源众
- 作者：Huozhi Zhou;Ashish Jagmohan;Lav R. Varshney
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- computational complexity;
- directed graphs;
- maximum likelihood estimation;
89.Online selective training for faster neural network learning

机译：在线选择性培训更快的神经网络学习
- 作者：Sara Mourad;Haris Vikalo;Ahmed Tewfik
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data handling;
- learning (artificial intelligence);
- neural nets;
90.Bayesian Multiple Hypothesis Testing For Distributed Detection In Sensor Networks

机译：传感器网络中分布式检测的贝叶斯多假设检测
- 作者：Topi Halme;Martin G?lz;Visa Koivunen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- Bayes methods;
- statistical analysis;
- wireless sensor networks;
91.Long-Range Dependence Parameter Estimation For Mixed Spectra Gaussian Processes

机译：混合光谱高斯过程的远程依赖性参数估计
- 作者：Lenin Arango-Castillo;Glen Takahara
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- decomposition;
- Gaussian noise;
- harmonic analysis;
- iterative methods;
- parameter estimation;
- time series;
92.Structural Robustness for Deep Learning Architectures

机译：深度学习架构的结构鲁棒性
- 作者：Carlos Lassance;Vincent Gripon;Jian Tang;Antonio Ortega
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- learning (artificial intelligence);
93.Stochastic Optimization for Coupled Tensor Decomposition with Applications in Statistical Learning

机译：统计学习应用耦合张量分解的随机优化
- 作者：Shahana Ibrahim;Xiao Fu
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data analysis;
- gradient methods;
- learning (artificial intelligence);
- matrix decomposition;
- optimisation;
- probability;
- statistical analysis;
- stochastic processes;
- tensors;
94.Learning to Detect an Anomalous Target with Observations from an Exponential Family

机译：学习用指数家庭的观测检测异常目标
- 作者：Gayathri R Prabhu;Srikrishna Bhashyam;Aditya Gopalan;Rajesh Sundaresan
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- decision making;
- maximum likelihood estimation;
- statistical distributions;
95.Introducing Graph Smoothness Loss for Training Deep Learning Architectures

机译：介绍深度学习架构的图形平滑度损失
- 作者：Myriam Bontonou;Carlos Lassance;Ghouthi Boukli Hacene;Vincent Gripon;Jian Tang
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- entropy;
- graph theory;
- learning (artificial intelligence);
- pattern classification;
96.Data Driven Measurement Matrix Learning for Sparse Reconstruction

机译：稀疏重建的数据驱动测量矩阵学习
- 作者：Robiul Hossain Md. Rafi;Ali Cafer Gurbuz
- 会议名称：《IEEE Data Science Workshop》 | 2019年
97.Byzantine-Robust Stochastic Gradient Descent for Distributed Low-Rank Matrix Completion

机译：拜占亮 - 强大的随机梯度下降，用于分布式低级矩阵完成
- 作者：Xuechao He;Qing Ling;Tianyi Chen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
- data privacy;
- gradient methods;
- learning (artificial intelligence);
- matrix decomposition;
- recommender systems;
- stochastic processes;
98.A Stochastic LBFGS Algorithm for Radio Interferometric Calibration

机译：无线电干涉校准的随机LBFGS算法
- 作者：Sarod Yatawatta;Lukas De Clercq;Hanno Spreeuw;Faruk Diblen
- 会议名称：《IEEE Data Science Workshop》 | 2019年
99.Learning to Infer Voltage Stability Margin Using Transfer Learning

机译：使用转移学习学习推断电压稳定性边缘
- 作者：Jiaming Li;Yue Zhao;Young-hwan Lee;Seung-Jun Kim
- 会议名称：《IEEE Data Science Workshop》 | 2019年
100.Deep Mimo Detection Using ADMM Unfolding

机译：使用ADMM展开的深层MIMO检测
- 作者：Man-Wai Un;Mingjie Shao;Wing-Kin Ma;P. C. Ching
- 会议名称：《IEEE Data Science Workshop》 | 2019年