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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：55/0  |  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：44/0  |  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  
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：130/0  |  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  
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：204/0  |  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 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：82/0  |  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  
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：82/0  |  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  
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：55/0  |  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)  
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：68/0  |  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  
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：102/0  |  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  
Improved Symmetric and Nonnegative Matrix Factorization Models for Undirected, Sparse and Large-Scaled Networks: A Triple Factorization-Based Approach 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 卷号: 16, 期号: 5, 页码: 3006-3017
作者:  Song, Yan;  Li, Ming;  Luo, Xin;  Yang, Guisong;  Wang, Chongjing
收藏  |  浏览/下载：116/0  |  提交时间：2020/08/24
Computational modeling  Sparse matrices  Biological system modeling  Symmetric matrices  Matrix decomposition  Linear programming  Convergence  Big data  data analysis  latent factor  nonnegativity  sparse and large-scaled network  symmetry  triple-factorization  undirected