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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	Convergence Analysis of Single Latent Factor-Dependent, Nonnegative, and Multiplicative Update-Based Nonnegative Latent Factor Models 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 4, 页码: 1737-1749 作者:  Liu, Zhigang;  Luo, Xin;  Wang, Zidong 收藏  |  浏览/下载：151/0  |  提交时间：2021/05/17 Manganese  Convergence  Computational modeling  Learning systems  Analytical models  Sparse matrices  Big Data  Big data  convergence  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  learning system  neural networks  nonnegative LF (NLF) analysis  single LF-dependent nonnegative and multiplicative update (SLF-NMU)
	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 Adobe PDF(805Kb)  |  收藏  |  浏览/下载：414/0  |  提交时间：2019/06/26
	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：426/0  |  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
	Regularizaed extraction of non-negative latent factors from high-dimensional sparse matrices 会议论文 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, October 9, 2016 - October 12, 2016 作者:  Luo, Xin;  Li, Shuai;  Zhou, Mengchu Adobe PDF(764Kb)  |  收藏  |  浏览/下载：89/0  |  提交时间：2018/03/16