Dictionary-Based Low-Rank Approximations and the Mixed Sparse Coding Problem
Dictionary-Based Low-Rank Approximations and the Mixed Sparse Coding Problem
Constrained tensor and matrix factorization models allow to extract interpretable patterns from multiway data. Therefore crafting efficient algorithms for constrained low-rank approximations is nowadays an important research topic. This work deals with columns of factor matrices of a low-rank approximation being sparse in a known and possibly overcomplete basis, a …