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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：239/0  |  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：59/0  |  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)  
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：72/0  |  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)  
Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 2, 页码: 402-411
作者:  Luo, Xin;  Qin, Wen;  Dong, Ani;  Sedraoui, Khaled;  Zhou, MengChu
收藏  |  浏览/下载：117/0  |  提交时间：2021/03/17
Big data  industrial application  industrial data  latent factor analysis  machine learning  parallel algorithm  recommender system (RS)  stochastic gradient descent (SGD)