Oct 3, 2014 · In this paper, we propose a new decomposition method by maximizing the correntropy between the original and the product of two low-rank matrices ...
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In this paper, we propose a new decomposition method by maximizing the correntropy between the original and the product of two low-rank matrices for document ...
Mar 4, 2015 · In this paper, we propose a new decomposition method by maximizing the correntropy between the original and the product of two low-rank matrices ...
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[PDF] Document Clustering Based On Non-negative Matrix Factorization
people.eecs.berkeley.edu › NMF03
In this paper, we propose a novel document clustering method based on the non-negative factorization of the term- document matrix of the given document corpus.
Missing: Correntropy | Show results with:Correntropy
Oct 3, 2014 · Abstract: Nonnegative matrix factorization (NMF) has been success- fully applied to many areas for classification and clustering.
Oct 3, 2014 · This paper provides a theoretical support for clustering aspect of the nonnegative matrix factorization (NMF). By utilizing the Karush-Kuhn- ...
Nonnegative Matrix Factorization (NMF) is one of the popular techniques to reduce the number of attributes of the data. It has been also widely used for ...
Nonnegative Matrix Factorization (NMF) is one of the popular techniques to reduce the number of attributes of the data. It has been also widely used for ...
Mar 24, 2013 · We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering.
Missing: Document | Show results with:Document
Nonnegative Matrix Factorization (NMF) is a popular dimension reduction technique of clustering by extracting latent features from high-dimensional data.