The goal of this course is to investigate in-depth and to develop expert knowledge in the theory and algorithms for convex optimization. This course will provide a rigorous introduction to the rich ...

This course discusses basic convex analysis (convex sets, functions, and optimization problems), optimization theory (linear, quadratic, semidefinite, and geometric programming; optimality conditions ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...

What are some recent advances in non-convex optimization research? originally appeared on Quora - the knowledge sharing network where compelling questions are answered by people with unique insights.

This is a preview. Log in through your library . Abstract We apply conjugate duality to establish the existence of optimal portfolios in an assetallocation problem, with the goal of minimizing the ...