中国科学院重庆绿色智能技术研究院机构知识库

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限定条件	作者：罗辛    第一作者    作者：尚明生

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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：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)
	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：55/0  |  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)
	Highly-Accurate Community Detection via Pointwise Mutual Information-Incorporated Symmetric Non-Negative Matrix Factorization 期刊论文 IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2021, 卷号: 8, 期号: 1, 页码: 463-476 作者:  Luo, Xin;  Liu, Zhigang;  Shang, Mingsheng;  Lou, Jungang;  Zhou, MengChu 收藏  |  浏览/下载：145/0  |  提交时间：2021/04/20 Detectors  Symmetric matrices  Image edge detection  Social networking (online)  Topology  Measurement  Knowledge engineering  Computational Intelligence  Social Network  Network Representation  Community Detection  Pointwise Mutual Information  Symmetric and Non-negative Matrix Factorization  Graph-regularization
	Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1844-1855 作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Hu, Lun;  Shang, Mingsheng 收藏  |  浏览/下载：124/0  |  提交时间：2020/08/24 Computational modeling  Data models  Sparse matrices  Linear programming  Training  Convergence  Analytical models  Alternating-direction-method of multipliers  high-dimensional and sparse matrix  industrial application  non-negative latent factor analysis  recommender system
	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