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An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 5, 页码: 2011-2022
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Shang, MingSheng
收藏  |  浏览/下载:508/0  |  提交时间:2018/07/02
Big data  high-dimensional and sparse matrix  learning algorithms  missing-data estimation  nonnegative latent factor analysis  optimization methods recommender system  
Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 卷号: 48, 期号: 4, 页码: 1216-1228
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Xia, Yunni;  You, Zhu-Hong;  Zhu, QingSheng;  Leung, Hareton
收藏  |  浏览/下载:518/0  |  提交时间:2018/06/04
Big data  latent factor model  missing data prediction  quality-of-service (QoS)  second-order solver  service computing sparse matrices  Web service  
Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 卷号: 13, 期号: 6, 页码: 3098-3107
作者:  Luo, Xin;  Sun, Jianpei;  Wang, Zidong;  Li, Shuai;  Shang, Mingsheng
Adobe PDF(803Kb)  |  收藏  |  浏览/下载:427/0  |  提交时间:2018/03/05
Big data application  high-dimensional, and sparse (SHiDS) matrix  nonnegative latent factor (NLF) model  symmetry  undirected HiDS network