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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：129/0  |  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 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：94/0  |  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  
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)  
Hyper-parameter-evolutionary latent factor analysis for high-dimensional and sparse data from recommender systems 期刊论文
NEUROCOMPUTING, 2021, 卷号: 421, 页码: 316-328
作者:  Chen, Jiufang;  Yuan, Ye;  Ruan, Tao;  Chen, Jia;  Luo, Xin
收藏  |  浏览/下载：73/0  |  提交时间：2021/02/24
Big Data  Intelligent Computation  Latent Factor Analysis  Evolutionary Computing  Learning Algorithm  High-dimensional and Sparse Data  Parameter Free