To address the above issues, in this article, we propose a novel model termed deep autoencoder-like NMF for MRL (DANMF-MRL), which obtains the representation ...

[21] proposed a deep AE-like nonnegative matrix factorization for multiview representation learning (DANMF-MRL), which cascades multiple NMF layers to build a ...

This architecture empowers DANMF to learn the hierarchical mappings between the original network and the final community assignment with implicit low-to-high ...

Comprehensive Multiview Representation Learning via Deep Autoencoder-Like Nonnegative Matrix Factorization ... representation learning via deep autoencoder ...

Comprehensive multiview representation learning via deep autoencoder-like nonnegative matrix factorization. H Huang, G Zhou, Q Zhao, L He, S Xie. IEEE ...

... Robust Structured Nonnegative Matrix Factorization (RSNMF) [42] is another semi-supervised NMF method that attempts to learn representation using a ...

Comprehensive Multiview Representation Learning via Deep Autoencoder-Like Nonnegative Matrix Factorization. IEEE Trans. Neural Networks Learn. Syst. 35(5) ...

H. Huang, G. Zhou, Q. Zhao, L. He and S. Xie, "Comprehensive Multi-view Representation Learning via Deep Autoencoder-like Nonnegative Matrix Factorization ...

Typically, NMF-based clustering involves two steps. Firstly, NMF is used to learn low-dimensional representations of data [23], [24]. Then an additional post- ...

In this paper, we present a deep matrix factorization framework for MVC, where semi-nonnegative matrix factorization is adopted to learn the hierarchical ...