Structured Low Rank Matrix Optimization Problems : a Penalty Approach

In this thesis, we study a class of structured low rank matrix optimization problems (SLR-MOPs) which aim at finding an approximate matrix of certain specific structures and whose rank is no more than a prescribed number. This kind of approximation is needed in many important applications arising from a wide range of fields. The SLR-MOPs are in general non… CONTINUE READING