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Parallel Adaptive Stochastic Gradient Descent Algorithms for Latent Factor Analysis of High-Dimensional and Incomplete Industrial Data 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 页码: 14
作者:  Qin, Wen;  Luo, Xin;  Li, Shuai;  Zhou, MengChu
收藏  |  浏览/下载：13/0  |  提交时间：2023/12/25
Adaptation models  Training  Data models  Convergence  Stochastic processes  Sparse matrices  Tuning  Big data  latent factor analysis  Index Terms  adaptive model  parallelization  machine learning  stochastic gradient descent  high-dimensional and incomplete matrix  
Hierarchical Particle Swarm Optimization-incorporated Latent Factor Analysis for Large-Scale Incomplete Matrices 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 6, 页码: 1524-1536
作者:  Chen, Jia;  Luo, Xin;  Zhou, Mengchu
收藏  |  浏览/下载：61/0  |  提交时间：2022/12/26
Adaptation models  Optimization  Convergence  Computational modeling  Sparse matrices  Particle swarm optimization  Big Data  Big data  latent factor analysis  particle swarm optimization  high-dimensional and sparse matrix  large-scale incomplete data  missing data estimation  industrial application  
Nonnegative Latent Factor Analysis-Incorporated and Feature-Weighted Fuzzy Double $c$-Means Clustering for Incomplete Data 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 卷号: 30, 期号: 10, 页码: 4165-4176
作者:  Song, Yan;  Li, Ming;  Zhu, Zhengyu;  Yang, Guisong;  Luo, Xin
收藏  |  浏览/下载：50/0  |  提交时间：2022/12/26
Big data  clustering  fuzzy double c-means  incomplete data  latent factor analysis  local feature weights.  
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 PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2022, 卷号: 9, 期号: 3, 页码: 533-546
作者:  Wu, Hao;  Luo, Xin;  Zhou, MengChu;  Rawa, Muhyaddin J.;  Sedraoui, Khaled;  Albeshri, Aiiad
收藏  |  浏览/下载：53/0  |  提交时间：2022/08/22
Big data  high dimensional and incomplete (HDI) tensor  latent factorization-of-tensors (LFT)  machine learning  missing data  optimization  proportional-integral-derivative (PID) controller  
A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 页码: 15
作者:  Wu, Di;  He, Yi;  Luo, Xin;  Zhou, MengChu
收藏  |  浏览/下载：40/0  |  提交时间：2022/08/22
Big data  computational intelligence  latent factor analysis (LFA)  missing data  online algorithm  online feature selection  sparse streaming feature  streaming feature  
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)  
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)  
A proportional-integral-derivative-incorporated stochastic gradient descent-based latent factor analysis model 期刊论文
NEUROCOMPUTING, 2021, 卷号: 427, 页码: 29-39
作者:  Li, Jinli;  Yuan, Ye;  Ruan, Tao;  Chen, Jia;  Luo, Xin
收藏  |  浏览/下载：93/0  |  提交时间：2021/03/17
Big data  Stochastic gradient descent  Proportional integral derivation  PID controller  High-dimensional and sparse matrix  Latent factor analysis  
Latent Factor-Based Recommenders Relying on Extended Stochastic Gradient Descent Algorithms 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 2, 页码: 916-926
作者:  Luo, Xin;  Wang, Dexian;  Zhou, MengChu;  Yuan, Huaqiang
收藏  |  浏览/下载：64/0  |  提交时间：2021/03/17
Big data  bi-linear  collaborative filtering (CF)  high-dimensional and sparse (HiDS) matrix  industry  latent factor (LF) analysis  missing data  recommender system