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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发表日期：2021

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	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：80/0  |  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
	Symmetric Nonnegative Matrix Factorization-Based Community Detection Models and Their Convergence Analysis 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13 作者:  Luo, Xin;  Liu, Zhigang;  Jin, Long;  Zhou, Yue;  Zhou, MengChu 收藏  |  浏览/下载：53/0  |  提交时间：2022/08/22 Detectors  Convergence  Symmetric matrices  Social networking (online)  Analytical models  Tuning  Computational modeling  Community detection  convergence analysis  graph regularization  nonnegative multiplicative update (NMU)  social network analysis  symmetric and nonnegative matrix factorization (SNMF)
	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