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Caltech

Control and Dynamical Systems Seminar

Wednesday, October 29, 2014
11:00am to 12:00pm
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Annenberg 121
Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints
Laurent Lessard, Postdoctoral Scholar, Berkeley Center for Control and Identification, University of California, Berkeley,

Presenting a new method to analyze and design iterative optimization algorithms, built on the framework of Integral Quadratic Constraints (IQC) from robust control theory. IQCs provide sufficient conditions for the stability of complicated interconnected systems, and these conditions can be checked by semidefinite programming. I will how to adapt IQC theory to study optimization algorithms, proving new inequalities about convex functions. Using these inequalities, I will derive upper bounds on convergence rates for the gradient method, the heavy-ball method, Nesterov's accelerated method, and related variants by solving small, simple semidefinite programs. I will close with a discussion of how these techniques can be used to search for algorithms with desired performance characteristics, establishing a new methodology for algorithm design.

For more information, please contact Nikki Fauntleroy by phone at 626-395-4140 or by email at nikkif@caltech.edu.