A Bayesian NMF model with a correlated multivariate normal prior for mutational signatures is proposed, but the claimed accuracy gain is only demonstrated in favorable simulations.
On the complexity of nonnegative matrix factorization
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abstract
Nonnegative matrix factorization (NMF) has become a prominent technique for the analysis of image databases, text databases and other information retrieval and clustering applications. In this report, we define an exact version of NMF. Then we establish several results about exact NMF: (1) that it is equivalent to a problem in polyhedral combinatorics; (2) that it is NP-hard; and (3) that a polynomial-time local search heuristic exists.
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Bayesian Non-Negative Matrix Factorization with Correlated Mutation Type Probabilities for Mutational Signatures
A Bayesian NMF model with a correlated multivariate normal prior for mutational signatures is proposed, but the claimed accuracy gain is only demonstrated in favorable simulations.