Abstract. Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for...
Ernesto E. Prudencio, Richard H. Byrd, Xiao-Chuan ...
Abstract. This paper’s intention is to present a new approach for decomposing motion trajectories. The proposed algorithm is based on nonnegative matrix factorization, which is a...
The multiplicative algorithms are well-known for nonnegative matrix and tensor factorizations. The ALS algorithm for canonical decomposition (CP) has been proved as a “workhorse...
Anh Huy Phan, Andrzej Cichocki, Kiyotoshi Matsuoka...
In this paper we are interested in non-negative matrix factorization (NMF) with the Itakura-Saito (IS) divergence. Previous work has demonstrated the relevance of this cost functi...
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...