In this paper, a novel Topology Preserving Nonnegative Matrix Factorization (TPNMF)
method is proposed for face recognition. The TPNMF is based on minimizing the constraint …

In this paper, a novel topology preserving non-negative matrix factorization (TPNMF) method
is proposed for face recognition. We derive the TPNMF model from original NMF algorithm …

In this paper, we propose a new variation of the Nonnegative Matrix Factorization (NMF) for
face recognition. The original NMF algorithm is distinguished from the other methods of …

In this paper, we extend the Fisher nonnegative matrix factorization (FNMF) to weighted
FNMF (WFNMF). The goal of this technique is to improve the performance of FNMF-based …

Face recognition has received growing attention because of its wide applications. In this
paper, an efficient face recognition algorithm based on non-negative matrix factorization …

Non-negative matrix factorization (NMF) is an unsupervised learning algorithm that can
extract parts from visual data. The goal of this technique is to find intuitive basis such that …

In this paper, we propose a face recognition method called the Laplacian Nonnegative
Matrix Factorization. By incorporating Laplacianfaces inside the Nonnegative Matrix …

In this paper, we propose a face recognition technique based on modification of the
nonnegative matrix factorization (NMF) technique, which is known as sorted locally confined …

In this paper, we propose a Locality Preserving Nonnegative Matrix Factorization (LPNMF)
method to discover the manifold structure embedded in high-dimensional face space that is …

Non-negative matrix factorization (NMF) as a part-based representation method allows only
additive combinations of non-negative basis components to represent the original data, so it …