Deep asymmetric nonnegative matrix factorization for graph clustering
Graph clustering is a fundamental technique in machine learning that has widespread
applications in various fields. Deep Nonnegative Matrix Factorization (DNMF) was recently …
applications in various fields. Deep Nonnegative Matrix Factorization (DNMF) was recently …
[HTML][HTML] Non-Negative Matrix Factorization with Averaged Kurtosis and Manifold Constraints for Blind Hyperspectral Unmixing
C Song, L Lu, C Zeng - Symmetry, 2024 - mdpi.com
The Nonnegative Matrix Factorization (NMF) algorithm and its variants have gained
widespread popularity across various domains, including neural networks, text clustering …
widespread popularity across various domains, including neural networks, text clustering …
Hierarchical Object Part Learning Using Deep Lp Smooth Symmetric Non-Negative Matrix Factorization
S Li, C Song, L Lu, Z Chen - Symmetry, 2024 - mdpi.com
Nowadays, deep representations have gained significant attention due to their outstanding
performance in a wide range of tasks. However, the interpretability of deep representations …
performance in a wide range of tasks. However, the interpretability of deep representations …