Michael Overton | PIMS - Pacific Institute for the Mathematical Sciences

Professor of Computer Science and Mathematics, New York University

Michael L. Overton received his B.Sc. from UBC in 1974, along with the Governor General's Gold Medal for Arts and Sciences. He received the M.S. and Ph.D. degrees in Computer Science from Stanford University. He is a fellow of SIAM (Society for Industrial and Applied Mathematics) and of the IMA (Institute of Mathematics and its Applications, UK). He served on the Council and Board of Trustees of SIAM from 1991 to 2005, including a term as Chair of the Board from 2004 to 2005. He is a member of the Council of FoCM (Foundations of Computational Mathematics) and served on the Board of Directors of the Canadian Mathematical Society from 2001 to 2005 and on the Scientific Advisory Board of the Fields Institute from 2001 to 2004. He currently serves on the editorial boards of SIAM Journal on Optimization (for which he was the Editor-in-Chief from 1995-1999), the IMA Journal of Numerical Analysis (for which he was an Editor-in-Chief from 2007 to 2008), SIAM Review, and Numerische Mathematik. His research interests are at the interface of optimization and linear algebra, especially nonsmooth optimization problems involving eigenvalues, pseudospectra, stability and robust control. He is the author of “Numerical Computing with IEEE Floating Point Arithmetic” (SIAM, 2001).

This short workshop is being hosted at the University of Washington and is in honor of Prof Adrian Lewis in recognition of his fundamental contributions to nonsmooth optimization Schedule: Aug 9: 9 am -- 5pm & Invited talks at the University of...

There are many algorithms for minimization when the objective function is differentiable or convex, but few options when it is neither. We describe two simple algorithmic approaches for minimization of nonsmooth, nonconvex objectives: BFGS (a new...

Let $A$ be an $n\times n$ matrix with $n$ distinct eigenvalues. Its open $\epsilon$-pseudospectrum is the set of points in the complex plane which are eigenvalues of a matrix $B$ with $||A-B|| \epsilon$. For sufficiently small $\epsilon$ the...

Abstract:The root radius and root abscissa of a monic polynomial are respectively the maximum modulus and the maximum real part of its roots; both these functions are nonconvex and are non-Lipschitz near polynomials with multiple roots. We begin the...

In many applications one wishes to minimize an objective function that is not convex and is not differentiable at its minimizers. We discuss two algorithms for minimization of nonsmooth, nonconvex functions. Gradient Sampling is a simple method that...

Crouzeix's conjecture is among the most intriguing developments in matrix theory in recent years. Made in 2004 by Michel Crouzeix, it postulates that, for any polynomial p and any matrix A, ||p(A)||

The generalized null space decomposition (GNSD), better known as the staircase decomposition, is a unitary reduction of a general matrix A of order n to a block upper triangular form that reveals the structure of the Jordan blocks of A corresponding...