Recent Advances in Convex Optimization

Joint work with Michael Grant, Jacob Mattingley, Yang Wang

Convex optimization---a special type of mathematical optimization
problem---is now widely used in automatic
control systems, signal processing,
networking, communications, machine learning, finance,
combinatorial optimization, and other fields.
In this talk I will give a brief overview of the basic idea
of convex optimization, and describe a few recent advances.
The first is the development of specification and modeling
languages specifically for convex optimization, which
allow very rapid development of applications based on convex
optimization, and enhance learning and teaching of the methods.
The second is automatic code generation for convex optimization
solvers, which can be used to develop solvers fast enough
for use in real-time and embedded applications.