TITLE: Semi-algebraic optimization theory

SPEAKER: Adrian lewis

ABSTRACT:

Concrete optimization problems, while often nonsmooth, are not
pathologically so. The class of "semi-algebraic" sets and functions -
those arising from polynomial inequalities - nicely exemplifies
nonsmoothness in practice. Semi-algebraic sets (and their
generalizations) are common, easy to recognize, and richly structured,
supporting powerful variational properties. In particular I will discuss
a generic property of such sets - partial smoothness - and its
relationship with a proximal algorithm for nonsmooth composite
minimization, a versatile model for practical optimization.


Bio:


Adrian S. Lewis was born in England in 1962. He is a Professor at
Cornell University in the School of Operations Research and Industrial
Engineering. Following his B.A., M.A., and Ph.D. degrees from Cambridge,
and Research Fellowships at Queens' College, Cambridge and Dalhousie
University, Canada, he worked in Canada at the University of Waterloo
(1989-2001) and Simon Fraser University (2001-2004). He is an Associate
Editor of the SIAM Journal on Optimization, Mathematics of Operations
Research, and the SIAM/MPS Book Series on Optimization, and is a
Co-Editor for Mathematical Programming. He received the 1995 Aisenstadt
Prize, from the Canadian Centre de Recherches Mathematiques, the 2003
Lagrange Prize for Continuous Optimization from SIAM and the
Mathematical Programming Society, and an Outstanding Paper Award from
SIAM in 2005. He co-authored "Convex Analysis and Nonlinear
Optimization" with J.M. Borwein.


Lewis' research concerns variational analysis and nonsmooth
optimization, with a particular interest in optimization problems
involving eigenvalues.