Scientific Computation and Applied & Industrial Mathematics Seminar: Robert M. Freund

Motivated by the problem of computing low-rank matrix completion solutions, we present an extension of the Frank-Wolfe method that is designed to induce near-optimal solutions on low-dimensional faces of the feasible region. We also present computational guarantees for the method that trade off efficiency in computing near-optimal solutions with upper bounds on the dimension of minimal faces of iterates. We then present computational results for large-scale matrix completion problems that demonstrate significant speed-ups in computing low-rank near-optimal solutions.