Recent Advances in Convex Optimization

  • Stephen Boyd | Stanford University

Convex optimization is now widely used in control, signal processing,
networking, communications, machine learning, finance, combinatorial
optimization, and other fields. For many problem classes reliable general
purpose solvers are now available, with development of new algorithms and
implementations continuing at a rapid pace.

In this talk I will give an overview of some recent advances. The first is the
development of specification and modeling languages specifically for convex
optimization. These languages allow very rapid development of applications
based on convex optimization, and enhance learning and teaching of the methods.
The second is the development of methods for extremely large convex problems,
with millions (or more) of variables and constraints, for specific families of
problems arising in applications. Truncated Newton interior-point methods, with
well-chosen pre-conditioner, can solve far larger problems than generic
methods. The third advance is in the area of algorithms for fast solution of
convex optimization problems, for use in real-time and embedded applications.
(Joint work with Michael Grant, Kwangmoo Koh, Seung-Jean Kim, Yang Wang)

Speaker Details

Stephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. His current research focus is on convex optimization applications in control, signal processing, and circuit design. He received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U.C. Berkeley in 1985. In 1985 he joined the faculty of Stanford’s Electrical Engineering Department. Prof. Boyd is the author of many research articles and three books: Linear Controller Design: Limits of Performance (with Craig Barratt, 1991), Linear Matrix Inequalities in System and Control Theory (with L. El Ghaoui, E. Feron, and V. Balakrishnan, 1994), and Convex Optimization (with Lieven Vandenberghe, 2004). He has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and an IBM faculty development award, and the 1992 AACC Donald P. Eckman Award. He was elected Distinguished Lecturer of the IEEE Control Systems Society in 1993, and Fellow of the IEEE in 1999. He received the Perrin Award for Outstanding Undergraduate Teaching in the School of Engineering in 1994, and the AACC Ragazzini Education award in 2003.

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