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Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 2, 页码: 420-431
作者:  Shi, Xiaoyu;  He, Qiang;  Luo, Xin;  Bai, Yanan;  Shang, Mingsheng
收藏  |  浏览/下载:72/0  |  提交时间:2022/08/22
Recommender systems  Training  Optimization  Big Data  Cloud computing  Computational modeling  Sparse matrices  Recommender system  latent factor analysis  high-dimensional and sparse matrices  alternative stochastic gradient descent  distributed computing  
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  
Popularity and Novelty Dynamics in Evolving Networks 期刊论文
SCIENTIFIC REPORTS, 2018, 卷号: 8, 页码: 10
作者:  Abbas, Khushnood;  Shang, Mingsheng;  Abbasi, Alireza;  Luo, Xin;  Xu, Jian Jun;  Zhang, Yu-Xia
Adobe PDF(2105Kb)  |  收藏  |  浏览/下载:266/0  |  提交时间:2018/06/04