Nonnegative matrix factorization (NMF) is a widely-used tool for obtaining low-rank approximations of nonnegative data such as digital images, audio signals, textual data, financ...
The Web abounds with dyadic data that keeps increasing by every single second. Previous work has repeatedly shown the usefulness of extracting the interaction structure inside dya...
The nonnegative matrix factorization (NMF) has been shown recently to be useful for clustering. Various extensions of NMF have also been proposed. In this paper we present an over...
We present a new scheme for digital watermarking and secure copyright protection of digital images using nonnegative matrix factorization and singular value decomposition approach...
Kernel nonnegative matrix factorization (KNMF) is a recent kernel extension of NMF, where matrix factorization is carried out in a reproducing kernel Hilbert space (RKHS) with a f...