A generalized deep learning clustering algorithm based on non-negative matrix factorization
Clustering is a popular research topic in the field of data mining, in which the clustering
method based on non-negative matrix factorization (NMF) has been widely employed …
method based on non-negative matrix factorization (NMF) has been widely employed …
Auto-weighted collective matrix factorization with graph dual regularization for multi-view clustering
M Liu, Z Yang, L Li, Z Li, S **e - Knowledge-Based Systems, 2023 - Elsevier
Multi-view clustering (MVC) is an attractive clustering paradigm that can incorporate
comprehensive information from multiple views. Among the MVC schemes, collective matrix …
comprehensive information from multiple views. Among the MVC schemes, collective matrix …
A core space gradient projection-based continual learning framework for remaining useful life prediction of machinery under variable operating conditions
X Ren, Y Qin, B Li, B Wang, X Yi, L Jia - Reliability Engineering & System …, 2024 - Elsevier
Recently, continual learning has received particular attention in machinery remaining useful
life (RUL) prediction, which enables prognostics networks to gradually improve performance …
life (RUL) prediction, which enables prognostics networks to gradually improve performance …
Progressive deep non-negative matrix factorization architecture with graph convolution-based basis image reorganization
Deep non-negative matrix factorization is committed to using multi-layer structure to extract
underlying parts-based representation. However, the basis images obtained by continuous …
underlying parts-based representation. However, the basis images obtained by continuous …
Robust dual-graph discriminative NMF for data classification
In this paper, we propose a new supervised non-negative matrix factorization algorithm,
named Robust Dual-graph Discriminative Non-negative Matrix Factorization (RDGDNMF) …
named Robust Dual-graph Discriminative Non-negative Matrix Factorization (RDGDNMF) …
Auto-weighted Multi-view Deep Non-negative Matrix Factorization with Multi-kernel Learning
Deep matrix factorization (DMF) has the capability to discover hierarchical structures within
raw data by factorizing matrices layer by layer, allowing it to utilize latent information for …
raw data by factorizing matrices layer by layer, allowing it to utilize latent information for …
[PDF][PDF] Modified nonmonotonic projection Barzilai-Borwein gradient method for nonnegative matrix factorization
X Xu, J Liu, W Li, Y Xu, F Li - AIMS Mathematics, 2024 - aimspress.com
In this paper, an active set recognition technique is suggested, and then a modified
nonmonotonic line search rule is presented to enhance the efficiency of the nonmonotonic …
nonmonotonic line search rule is presented to enhance the efficiency of the nonmonotonic …