Dual semi-supervised convex nonnegative matrix factorization for data representation

Dual semi-supervised convex nonnegative matrix factorization for data representation

Semi-supervised nonnegative matrix factorization (NMF) has received considerable attention in machine learning and data mining. A new semi-supervised NMF method, called dual semi-supervised convex nonnegative matrix factorization (DCNMF), is proposed in this paper for fully using the limited label i...

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書目詳細資料
Main Authors:	Peng, Siyuan, Yang, Zhijing, Ling, Bingo Wing-Kuen, Chen, Badong, Lin, Zhiping
其他作者:	School of Electrical and Electronic Engineering
格式:	Article
語言:	English
出版:	2022
主題:	Engineering::Electrical and electronic engineering Semi-Supervised Learning Data Representation
在線閱讀:	https://hdl.handle.net/10356/161773
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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