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Structural Convex Optimization: snapshot of the development (Information & Communication Mini-Symposium)

In this lecture we present the current status of research in one specific field of structural convex optimization. Firstly, we describe some applications related to random permutations and their use in machine scheduling. We show that the similar objects arise in switching linear systems. Moreover, for some nontrivial sets of positive matrices they can help to find exact values of the joint spectral radius. Finally, we describe the recent progress in algorithmic aspects related to the development of corresponding long-step infeasible-start interior-point methods.
Type of Seminar:
Public Seminar
Prof. Yurii Nesterov
Université Catholique de Louvain, Belgium
May 20, 2008   16:00

Contact Person:

Prof. Manfred Morari
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Biographical Sketch:
Yurii Nesterov, professor at Center for Operations Research and Econometrics (CORE), Catholic University of Louvain (UCL), Louvain-la-Neuve, Belgium. Author of 4 monographs and more than 70 refereed papers in the leading optimization journals. Winner of the triennial Dantzig Prize 2000 awarded by SIAM and Mathematical Programming Society for a research having a major impact on the field of mathematical programming. The main direction of his research is the development of efficient numerical methods for convex and nonconvex optimization problems supported by the global complexity analysis. The most important results are obtained for general interior-point methods (theory of self-concordant functions), fast gradient methods (smoothing technique) and global complexity analysis of the second-order schemes (cubic regularization of the Newton's method).