Open access
Jul 2026
Robust Semi-Supervised Deep Autoencoder-like Nonnegative Matrix Factorization for Multi-View Clustering
This paper introduces the correntropy-based semi-supervised multi-view deep autoencoder-like NMF (CSDANMF) framework, and provides comprehensive algorithmic evaluations, including a formal robustness analysis on corrupted datasets and a computational complexity analysis.
Meilin Wang, Luoming Xu, Shuzhao Xu et al.
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