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)
Jensen's Inequality is one of the most important tools in convex analysis. We develop intuition for Jensen's inequality and explore its importance through an example result in probability theory. This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company. %%% CHAPTERS %%% 00:00 Intro 02:52 Jensen's Inequality 05:15 Geometric Interpretation 08:22 Example Application: Probability 13:03 Outro