Welcome to MS&E314/CME336, 2012-2013!
This course covers linear, semidefinite, conic linear optimization problems as generalizations of classical linear programming.
This year's theme is on rank reduction or rank-constrained conic LP. Related convex analysis, including the separating
hyperplane theorem, Farkasí lemma, dual cones, optimality conditions,
and conic inequalities. Applications to max-cut problems, graph partitioning, sensor localization, graph realization, and
matrix completion. Course slides and monograph are available on the Handout page.