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An Alternating-Direction-Method of Multipliers-Incorporated Approach to Symmetric Non-Negative Latent Factor Analysis 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:  Luo, Xin;  Zhong, Yurong;  Wang, Zidong;  Li, Maozhen
收藏  |  浏览/下载:56/0  |  提交时间:2022/08/22
Symmetric matrices  Computational modeling  Data models  Analytical models  Training  Learning systems  Convergence  Alternating-direction-method of multipliers (ADMM)  learning system  missing data  non-negative latent factor analysis (NLFA)  symmetric high-dimensional and incomplete matrix (SHDI)  undirected weighted network  
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:43/0  |  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)  
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:153/0  |  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:146/0  |  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  
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:53/0  |  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:67/0  |  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:100/0  |  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