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Rixin Tang

2 accepted papers

2019

Joint Structured Graph Learning and Clustering Based on Concept Factorization

ICASSP 2019accepted

As one of the matrix factorization models, concept factorization (CF) achieved promising performance in learning data representation in both original feature space and reproducible kernel Hilbert space (RKHS). Based on the consensuses that 1) learning performance of models can be enhanced by exploit…

Cited by 0SourceScholar
2018

Parallel Vector Field Regularized Non-Negative Matrix Factorization for Image Representation

ICASSP 2018accepted

Non-negative Matrix Factorization (NMF) is a popular model in machine learning, which can learn parts-based representation by seeking for two non-negative matrices whose product can best approximate the original matrix. However, the manifold structure is not considered by NMF and many of the existin…

Cited by 0SourceScholar