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A Double-Space and Double-Norm Ensembled Latent Factor Model for Highly Accurate Web Service QoS Prediction 期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2023, 卷号: 16, 期号: 2, 页码: 802-814
作者:  Wu, Di;  Zhang, Peng;  He, Yi;  Luo, Xin
收藏  |  浏览/下载：10/0  |  提交时间：2023/12/25
Web service  service selection  Quality-of-Service (QoS)  latent factor analysis  missing data prediction  big data  
Multi-Constrained Embedding for Accurate Community Detection on Undirected Networks 期刊论文
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2022, 卷号: 9, 期号: 5, 页码: 3675-3690
作者:  Wang, Qingxian;  Liu, Xinyu;  Shang, Tianqi;  Liu, Zhigang;  Yang, Han;  Luo, Xin
收藏  |  浏览/下载：50/0  |  提交时间：2022/10/14
Symmetric matrices  Symbols  Matrix decomposition  Context modeling  Task analysis  Periodic structures  Electronic mail  Community detection  network embedding  non-negative matrix factorization  non-negative model and alternating direction method of multipliers  
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 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 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  
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)  
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)  
Robust Latent Factor Analysis for Precise Representation of High-Dimensional and Sparse Data 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 4, 页码: 796-805
作者:  Wu, Di;  Luo, Xin
收藏  |  浏览/下载：78/0  |  提交时间：2021/05/17
High-dimensional and sparse matrix  L-1-norm  L-2-norm  latent factor model  recommender system  smooth L-1-norm  
Convergence Analysis of Single Latent Factor-Dependent, Nonnegative, and Multiplicative Update-Based Nonnegative Latent Factor Models 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 4, 页码: 1737-1749
作者:  Liu, Zhigang;  Luo, Xin;  Wang, Zidong
收藏  |  浏览/下载：151/0  |  提交时间：2021/05/17
Manganese  Convergence  Computational modeling  Learning systems  Analytical models  Sparse matrices  Big Data  Big data  convergence  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  learning system  neural networks  nonnegative LF (NLF) analysis  single LF-dependent nonnegative and multiplicative update (SLF-NMU)  
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