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 presents the definition, useful properties, and important intuitions of convex sets. This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company. %%% CHAPTERS %%% 00:00 Intro & Definition 03:42 Examples of Convex & Non-Convex Sets 07:27 The Convex Hull 08:17 Inequality Constraints & Convexity 10:33 Intersections of Convex Sets 13:06 Feasible Sets & Outro