Stephen Boyd: Convex Optimization

Submitted by Ingrid Richter on

The Department of Applied Mathematics is pleased to host this series of colloquium lectures, funded in part by a generous gift from the Boeing Company. This series will bring to campus prominent applied mathematicians from around the world.


Title:  Convex Optimization

Abstract:  Convex optimization has emerged as a useful tool for applications that include data analysis and model fitting, machine learning, and statistics, resource allocation, engineering design, network design and optimization, finance, and control and signal processing.

We give an overview of the basic mathematics, algorithms, and software frameworks for convex optimization, and give a few examples.

We describe real-time embedded convex optimization, in which small convex optimization problems are solved repeatedly in time frames measured in milliseconds.

Video: Watch the talk on YouTube

Share