CMU 10-725 Convex Optimization

Overview

Nearly every problem in machine learning and computational statistics can be formulated
in terms of the optimization of some function, possibly under some set of constraints. As
we obviously cannot solve every problem in machine learning, this means that we cannot
generically solve every optimization problem (at least not efficiently). Fortunately, many
problems of interest in machine learning can be posed as optimization tasks that have
special propertiessuch as convexity, smoothness, sparsity, separability, etc.permitting
standardized, efficient solution techniques.