This bootcamp explores the wide world of mathematical optimization, specifically for applications in machine learning, control theory, and inverse problems. This closely follows the textbook "Optimization: A Bootcamp for Machine Learning, Inverse Problems, and Control" (https://www.amazon.com/Optimization-Bootcamp-Machine-Learning-Problems/dp/1009755862)
Curated by: Steve Brunton (44 videos)
This lecture gives a high level overview of the intuitions, importance, and applications of convexity in optimization problems. This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company. %%% CHAPTERS %%% 00:00 Intro 03:22 What is Convexity? 05:43 Convexity & Local Optima 07:07 Convex Optimization and Affine Constraints 09:44 Maximization & Strict Convexity 11:46 Linear & Quadratic Programming 13:55 Outro