A novel Discriminant Non-negative Matrix Factorization (DNMF) method that uses projected gradients, is presented in this paper. The proposed algorithm guarantees the algorithm'...
Nonnegative Matrix Factorization (NMF) approximates a given data matrix as a product of two low rank nonnegative matrices, usually by minimizing the L2 or the KL distance between ...
Non-negative matrix factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. Two different multiplicative algorithms for NMF are analyzed....
We consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly underdetermined convolutive mixture of source signals...
Abstract. This paper presents a novel robust digital image watermarking scheme using subsampling and nonnegative matrix factorization. Firstly, subsampling is used to construct a s...