Convex Optimization and Feasibility Problems Publication Trend The graph below shows the total number of publications each year in Convex Optimization and Feasibility Problems.

Graph Optimisation: The process of identifying the best solution among many possibilities in graph-structured problems, typically to optimise parameters such as cost, distance or connectivity.

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 ...

Non-convex optimization is now ubiquitous in machine learning. While previously, the focus was on convex relaxation methods, now the emphasis is on being able to solve non-convex problems directly.

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

IEMS 459: Convex Optimization VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Linear Algebra, Calculus , Real Analysis Description The goal of this course is to investigate in-depth and to develop ...