Semi-Supervised Graph Regularized Deep NMF With Bi-Orthogonal Constraints for Data Representation
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DOI: 10.1109/tnnls.2019.2939637
Abstract: Semi-supervised non-negative matrix factorization (NMF) exploits the strengths of NMF in effectively learning local information contained in data and is also able to achieve effective learning when only a small fraction of data is labeled.… read more here.
Keywords: representation; graph regularized; semi supervised; supervised graph ... See more keywords