Robust large-scale non-negative matrix factorization using proximal point algorithm
A robust algorithm for non-negative matrix factorization (NMF) is presented in this paper with
the purpose of dealing with large-scale data, where the separability assumption is satisfied.
In particular, we modify the Linear Programming (LP) algorithm of [6] by introducing a
reduced set of constraints for exact NMF. In contrast to the previous approaches, the
proposed algorithm does not require the knowledge of factorization rank (extreme rays [3] or
topics [5]). Furthermore, motivated by a similar problem arising in the context of metabolic …
the purpose of dealing with large-scale data, where the separability assumption is satisfied.
In particular, we modify the Linear Programming (LP) algorithm of [6] by introducing a
reduced set of constraints for exact NMF. In contrast to the previous approaches, the
proposed algorithm does not require the knowledge of factorization rank (extreme rays [3] or
topics [5]). Furthermore, motivated by a similar problem arising in the context of metabolic …
Robust Large Scale Non-negative Matrix Factorization using Proximal Point Algorithm
J Gejie Liu, S Aeron - arXiv e-prints, 2014 - ui.adsabs.harvard.edu
A robust algorithm for non-negative matrix factorization (NMF) is presented in this paper with
the purpose of dealing with large-scale data, where the separability assumption is satisfied.
In particular, we modify the Linear Programming (LP) algorithm of [9] by introducing a
reduced set of constraints for exact NMF. In contrast to the previous approaches, the
proposed algorithm does not require the knowledge of factorization rank (extreme rays [3] or
topics [7]). Furthermore, motivated by a similar problem arising in the context of metabolic …
the purpose of dealing with large-scale data, where the separability assumption is satisfied.
In particular, we modify the Linear Programming (LP) algorithm of [9] by introducing a
reduced set of constraints for exact NMF. In contrast to the previous approaches, the
proposed algorithm does not require the knowledge of factorization rank (extreme rays [3] or
topics [7]). Furthermore, motivated by a similar problem arising in the context of metabolic …
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