Nonnegative Matrix Factorization (NMF) has emerged as a powerful tool in data analysis, particularly noted for its ability to produce parts‐based, interpretable representations from high ...

Matrix factorization algorithms help track neuronal activity They then excited the beads using blue laser light and collected the resulting fluorescence speckles using first a microscope objective and ...

We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of ...

Jean-Philippe Brunet, Pablo Tamayo, Todd R. Golub, Jill P. Mesirov, Eric S. Lander, Metagenes and Molecular Pattern Discovery Using Matrix Factorization, Proceedings of the National Academy of ...