ISR Distinguished Lecturer: L. Vandenberghe, "Sparsity & Decomposition in Semidefinite Optimization"

Tuesday, March 22, 2016
5:00 p.m.
3117 CSIC
Regina King
301 405 6576
rking12@umd.edu

ISR Distinguished Lecturer

Sparsity and decomposition in semidefinite optimization

Lieven Vandenberghe
Professor, Electrical Engineering
University of California, Los Angeles

Host
André Tits

Abstract
Semidefinite optimization is an important tool in control, signal processing, machine learning, combinatorial optimization, and other  disciplines.  It is also heavily used in convex optimization modeling  software. In several of these applications, semidefinite optimization methods are restricted by the limited scalability of the available general-purpose  solvers.  The talk will present a survey of results and algorithms from sparse  matrix theory that are useful when solving large semidefinite optimization  problems with underlying graph structure.  Classical theorems on positive  semidefinite and Euclidean distance matrix completion of sparse matrices  with a chordal sparsity pattern have interesting implications for the structure  (sparsity and rank) of  the solution of a semidefinite optimization problem  with sparse coefficient matrices.  Multifrontal algorithms for sparse Cholesky  factorization can be extended to other fundamental matrix problems that arise  in semidefinite optimization, for example, the computation of the partial inverse  of a sparse positive definite matrix, and the evaluation of gradients and  Hessians of logarithmic barriers for cones of sparse positive semidefinite  matrices and their dual cones. The importance of these techniques for semidefinite optimization will be illustrated with applications to interior-point algorithms and  first-order decomposition methods.

Biography
Lieven Vandenberghe is Professor in the Electrical Engineering Department at UCLA, with a courtesy appointment in the Department of Mathematics.   He received a Ph.D. in Electrical Engineering from K.U. Leuven, Belgium,  in 1992.  He joined UCLA in 1997, following postdoctoral appointments at  K.U. Leuven and Stanford University, and has held visiting professor positions at   K.U. Leuven and the Technical University of Denmark.   He is author (with Stephen Boyd) of the book Convex Optimization (2004)  and editor (with Henry Wolkowicz and Romesh Saigal) of the Handbook of   Semidefinite Programming (2000).   His research interests are in optimization,  systems and control, and signal processing.

Audience: Graduate  Undergraduate  Faculty  Staff  Post-Docs  Alumni 

 

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