two algorithms that report this range. Both of our algorithms rely on obtaining multiple Nonnegative Matrix Factorizations … estimator. The key idea is to maximize/minimize the functional of interest over all these nonnegative matrix factorizations. To …

The exact nonnegative matrix factorization (exact NMF) problem is the following: given an m-by-n nonnegative matrix X … and a factorization rank r, find, if possible, an m-by-r nonnegative matrix W and an r-by-n nonnegative matrix H such that …

Nonnegative Matrix Factorization (NMF) is the problem of approximating a nonnegative matrix with the product of two low …

Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a nonnegative matrix …

Nonnegative Matrix Factorization (NMF) has gathered a lot of attention in the last decade and has been successfully … applied in numerous applications. It consists in the factorization of a nonnegative matrix by the product of two low … a new variant called Nonnegative Matrix Underapproximation (NMU) by adding the upper bound constraint VW£M. Besides …

results. The nonnegative matrix factorization (NMF) approach overcomes this issue, however the NMF approximation matrices …

Nonnegative Matrix Factorization (NMF) is a data analysis technique which allows compression and interpretation of … Objects by Nonnegative Matrix Factorization, Nature, 1999, vol. 401, pp. 788--791), which introduced an algorithm based on … necessarily nonnegative matrix with the product of two nonnegative matrices, which we refer to as Nonnegative Factorization …