A Robust Sparse Nonnegative Matrix Factorization with Low Rank representation for clustering
Author:
Affiliation:
1. School of Computer Science and Technology, Anhui University of Technology, China
2. Data Communication Product Line, Huawei Technologies Co.,Ltd, China
3. College of Science, Mathematics and Technology, Wenzhou-Kean University, China
Funder
The Natural Science Foundation of Anhui Province, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3650215.3650242
Reference33 articles.
1. NMF with feature relationship preservation penalty term for clustering problems [J];Hedjam Rachid;Pattern Recognition,2021
2. Dual graph-regularized sparse concept factorization for clustering
3. Two-dimensional semi-nonnegative matrix factorization for clustering
4. Multi-layer manifold learning for deep non-negative matrix factorization-based multi-view clustering [J];Luong Khanh;Pattern Recognition,2022
5. Hyperspectral Unmixing Using Higher-Order Graph Regularized NMF With Adaptive Feature Selection[J];Kewen Qu;IEEE Transactions on Geoscience and Remote Sensing,2023
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