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Convex Optimization and Real Algebra

Many engineering problems can be reduced to the existence of real solutions of a finite number of polynomial inequalities and inequalities. A few concrete examples are geometric statements, network properties, and control theoretic problems. In general, this class of questions have bad complexity properties, and exact algorithms to solve them are usually computationally infeasible. The interaction of concepts from real algebra and convex optimization (in particular, semidefinite programming) has provided a very promising new approach to these classical NP-hard problems. The developed techniques, based on sum of squares decompositions, unify and generalize many well-known existing results. The ideas and algorithms will be illustrated with examples from a broad range of application domains.

Type of Seminar:
Public Seminar
Prof. Pablo A. Parrilo
Automatic Control Lab. ETH Zurich 8092 Zurich
Oct 31, 2001   17:15

ETH Zentrum, ETZ E6, Gloriastr. 35, 8006 Zurich
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Biographical Sketch:
Pablo A. Parrilo was born in Buenos Aires, Argentina. He received the Electronics Engineering degree from the University of Buenos Aires in 1994, and the PhD in Control and Dynamical Systems from the California Institute of Technology in June 2000. He joined the ETH faculty as an Assistant Professor in October 2001. His research interests include robust control and identification, robustness analysis, networked systems, convex optimization and computational algebra.