Two seminars by Mike Saunders:

Joint CRM Applied Math and McGill CSE seminar

Time: Friday, November 14, 2008, 2:30pm

Place: McGill, Burnside Hall 1205

Title: 40 Years of Linear Algebra and Optimization at Stanford

Speaker: Michael Saunders
Systems Optimization Laboratory (SOL)
Stanford University

I came to Stanford in 1967 as a very green graduate student
(not in today's ecological sense). Computer Science was a new
department, as was Operations Research. The CS qualifying
exams allowed 3 out of 5 topics, including numerical analysis.
Alan George and I obtained permission to take one of the OR
exams. Thus began a career of applying stable matrix methods
to numerical optimization (as pioneered by Gene Golub, Philip
Gill, and Walter Murray).

We trace the impact of Gene inviting numerous researchers to
Serra House (including Chris Paige and Bruce Murtagh), as well
as George Dantzig's creation of the Systems Optimization Lab
in the OR Department, and Gene's founding of the SCCM Program.

The talk includes some illustrations of the use of optimization
within the aerospace industry.

Coffee and cakes are served after the seminar in the lounge room
on the 10th floor.

Michael will also give another talk:

Time: Monday, Nov 17, 2008, 2:30pm

Place: McGill, McConnell Engineering Building, Room 103

Title: Computing Approximate Pagerank Vectors by Basis Pursuit Denoising

Basis Pursuit Denoising (BPDN) finds sparse solutions x
to underdetermined systems Ax ~= b by balancing the
1-norm of x against the 2-norm of the residual:

min_{x,r} lambda||x||_1 + 1/2 r'r, Ax + r = b.

The PageRank eigenvector problem involves a square system
Ax = b in which x is naturally nonnegative and somewhat
sparse (depending on b). We seek an approximate x that is
nonnegative and extremely sparse. We experiment with an
active-set optimization method designed for the dual of
the BPDN problem, and find that it tends to extract the
important elements of x in a greedy fashion.

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