Aug 30, 2019 · The proposed model is capable of generating discriminable low-dimensional representations to improve clustering performance. Specifically, a ...
NMF model proposed by Jia et al. [36] uses two complementing dissimilarity and similarity regularizations on representations based on must-link and cannot-link ...
Jul 7, 2020 · The proposed model is capable of generating discriminable low-dimensional representations to improve clustering performance. Specifically, a ...
Feb 28, 2022 · Abstract—We propose new semi-supervised nonnegative ma- trix factorization (SSNMF) models for document classification.
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Contribute to jyh-learning/Semi-Supervised-Non-Negative-Matrix-Factorization-with-Dissimilarity-and-Similarity-Regularizations development by creating an ...
Jia et al. (2020) proposed semi-supervised nonnegative matrix factorization with dissimilarity and similarity regularization terms (SSNMF). In the SSNMF method, ...
Specifically, GSSNMF demonstrates an ability to produce topics with similar levels of coherence (as seen from the small variance in individual coherence scores ...
This method constructs similarity and dissimilarity graph structures through partial label information, which can accurately describe the spatial geometric ...
Available from 2012 volume: 23 issue: 1.
This work presents semi-supervised NMF (SSNMF), where they jointly incorporate the data matrix and the (partial) class label matrix into NMF, and develops ...
Missing: Dissimilarity | Show results with:Dissimilarity