This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF’s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Deco
Recently Non-negative Matrix Factorization (NMF) has become increasingly popular for feature extraction in com- puter vision and pattern recognition. NMF seeks for two non-negative matrices whose product can best approximate the original matrix. The
Projected Gradient Methods for Non-negative Matrix Factorization Chih-Jen Lin Department of Computer Science Abstract Non-negative matrix factorization (NMF) can be formulated as a minimization problem with bound constraints. Although bound-constrai
