Linear and bilinear models arise in many research areas including statistics, signal processing, machine learning, approximation theory, or image analysis. In cases when the problem of interest is ill-conditioned or suffers from separation ambiguity, the classical solutions such as ordinary least squares or non-negative matrix factorization fail and additional information is needed for acceptable...