The problem of low-rank matrix factorization in the presence of missing data has seen significant attention in recent computer vision research. The approach that dominates the lit...
In this paper, we propose a novel document clustering method based on the non-negative factorization of the termdocument matrix of the given document corpus. In the latent semanti...
We present a new scheme for digital watermarking and secure copyright protection of digital images using nonnegative matrix factorization and singular value decomposition approach...
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
This paper concerns the adaptation of spectrum dictionaries in audio source separation with supervised learning. Supposing that samples of the audio sources to separate are availa...
Xabier Jaureguiberry, Pierre Leveau, Simon Maller,...