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A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 3, 页码: 784-794
作者:  Yuan, Ye;  He, Qiang;  Luo, Xin;  Shang, Mingsheng
收藏  |  浏览/下载：74/0  |  提交时间：2022/08/22
Computational modeling  Sparse matrices  Big Data  Data models  Stochastic processes  Training  Software algorithms  Big data  latent factor analysis  generally multilayered structure  deep forest  multilayered extreme learning machine  randomized-learning  high-dimensional and sparse matrix  stochastic gradient descent  randomized model  
A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction 期刊论文
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 卷号: 34, 期号: 6, 页码: 2525-2538
作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Wu, Xindong
收藏  |  浏览/下载：64/0  |  提交时间：2022/08/22
Web Service  quality-of-service  QoS  latent factor analysis  density peak  data-characteristic-aware  missing data  big data  topological neighborhood  noise data  service selection  data science  
A Posterior-Neighborhood-Regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction 期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 卷号: 15, 期号: 2, 页码: 793-805
作者:  Wu, Di;  He, Qiang;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin
收藏  |  浏览/下载：48/0  |  提交时间：2022/08/22
Web service  quality-of-service  latent factor analysis  posterior-neighborhood  regularization  cloud computing  big data  
Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 2, 页码: 420-431
作者:  Shi, Xiaoyu;  He, Qiang;  Luo, Xin;  Bai, Yanan;  Shang, Mingsheng
收藏  |  浏览/下载：70/0  |  提交时间：2022/08/22
Recommender systems  Training  Optimization  Big Data  Cloud computing  Computational modeling  Sparse matrices  Recommender system  latent factor analysis  high-dimensional and sparse matrices  alternative stochastic gradient descent  distributed computing  
An L-1-and-L-2-Norm-Oriented Latent Factor Model for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14
作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Wang, Zidong
收藏  |  浏览/下载：40/0  |  提交时间：2022/08/22
High-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  L-1 norm  L-2 norm  recommender system (RS)  
An alpha -beta -Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 13
作者:  Shang, Mingsheng;  Yuan, Ye;  Luo, Xin;  Zhou, MengChu
收藏  |  浏览/下载：52/0  |  提交时间：2022/08/22
Computational modeling  Sparse matrices  Convergence  Data models  Predictive models  Linear programming  Euclidean distance  -divergence  big data  convergence analysis  high-dimensional and sparse (HiDS) data  momentum  machine learning  missing data estimation  non-negative latent factor analysis (NLFA)  recommender system (RS)  
A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 7, 页码: 4285-4296
作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Zhou, MengChu
收藏  |  浏览/下载：202/0  |  提交时间：2021/08/20
Big data  deep model  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  recommender system (RS)  
Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 8, 页码: 4612-4623
作者:  Xin, Luo;  Yuan, Ye;  Zhou, MengChu;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载：128/0  |  提交时间：2021/08/20
beta-divergence  big data  high-dimensional and sparse (HiDS) matrix  industrial application  learning algorithm  non-negative latent factor (NLF) analysis  recommender system  
An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 6, 页码: 3522-3532
作者:  Luo, Xin;  Wang, Zidong;  Shang, Mingsheng
收藏  |  浏览/下载：79/0  |  提交时间：2021/08/20
High-dimensional and sparse (HiDS) data  industrial application  instance-frequency  non-negative latent factor analysis (NLFA)  recommender system  regularization  
Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2021, 卷号: 7, 期号: 1, 页码: 227-240
作者:  Luo, Xin;  Zhou, Mengchu;  Li, Shuai;  Wu, Di;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载：142/0  |  提交时间：2021/05/17
Data models  Training  Sparse matrices  Recommender systems  Computational modeling  Big Data  Scalability  Non-negative latent factor analysis  non-negativity  latent factor analysis  unconstrained optimization  high-dimensional and sparse matrix  collaborative filtering  recommender system  big data  
Highly-Accurate Community Detection via Pointwise Mutual Information-Incorporated Symmetric Non-Negative Matrix Factorization 期刊论文
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2021, 卷号: 8, 期号: 1, 页码: 463-476
作者:  Luo, Xin;  Liu, Zhigang;  Shang, Mingsheng;  Lou, Jungang;  Zhou, MengChu
收藏  |  浏览/下载：143/0  |  提交时间：2021/04/20
Detectors  Symmetric matrices  Image edge detection  Social networking (online)  Topology  Measurement  Knowledge engineering  Computational Intelligence  Social Network  Network Representation  Community Detection  Pointwise Mutual Information  Symmetric and Non-negative Matrix Factorization  Graph-regularization  
A Fast Non-Negative Latent Factor Model Based on Generalized Momentum Method 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 1, 页码: 610-620
作者:  Luo, Xin;  Liu, Zhigang;  Li, Shuai;  Shang, Mingsheng;  Wang, Zidong
收藏  |  浏览/下载：99/0  |  提交时间：2021/03/17
Big data  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  missing data estimation  non-negative LF (NLF) model  recommender system  
Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1844-1855
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Hu, Lun;  Shang, Mingsheng
收藏  |  浏览/下载：121/0  |  提交时间：2020/08/24
Computational modeling  Data models  Sparse matrices  Linear programming  Training  Convergence  Analytical models  Alternating-direction-method of multipliers  high-dimensional and sparse matrix  industrial application  non-negative latent factor analysis  recommender system  
A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction 期刊论文
NEUROCOMPUTING, 2019, 卷号: 367, 页码: 299-307
作者:  Wang, Qingxian;  Chen, Minzhi;  Shang, Mingsheng;  Luo, Xin
收藏  |  浏览/下载：443/0  |  提交时间：2019/12/03
Big Data  QoS prediction  Temporal-aware QoS prediction  Stochastic gradient descent  Latent factorization of tensors  Momentum method  
An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 5, 页码: 2011-2022
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Shang, MingSheng
收藏  |  浏览/下载：505/0  |  提交时间：2018/07/02
Big data  high-dimensional and sparse matrix  learning algorithms  missing-data estimation  nonnegative latent factor analysis  optimization methods recommender system  
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 3, 页码: 909-920
作者:  Wu, Di;  Luo, Xin;  Wang, Guoyin;  Shang, Mingsheng;  Yuan, Ye;  Yan, Huyong
收藏  |  浏览/下载：211/0  |  提交时间：2018/06/04
Differential evolution (DE)  general framework  industrial application  positioning optimization  self-labeled  semi-supervised classification (SSC)