RMFRASL: Robust Matrix Factorization with Robust Adaptive Structure Learning for Feature Selection

• Published in: Algorithms Vol. 16; no. 1; p. 14
• Main Authors: Lai, Shumin, Huang, Longjun, Li, Ping, Luo, Zhenzhen, Wang, Jianzhong, Yi, Yugen
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2023
• Subjects: adaptive structure learning; Algorithms; Clustering; Factorization; Feature selection; Internet of Things; Iterative methods; Learning; matrix factorization; Methods; Multimedia; Optimization; Optimization algorithms; Regularization; Robustness; Smart structures; structure regularization

In this paper, we present a novel unsupervised feature selection method termed robust matrix factorization with robust adaptive structure learning (RMFRASL), which can select discriminative features from a large amount of multimedia data to improve the performance of classification and clustering ta...