Gilad Lerman (School of Mathematics, University of Minnesota)
Wednesday, 29.12.2010, 11:30
We present several methods for multi-manifold data modeling,
i.e., modeling data by mixtures of possibly intersecting manifolds.
We focus on algorithms for the special case where the underlying
manifolds are affine or linear subspaces. We emphasize
various theoretical results supporting the performance of
some of these algorithms, in particular their robustness to noise
and outliers. We demonstrate how such theoretical insights guide us in
practical choices and present applications of such algorithms.
This is part of joint works with E. Arias-Castro, S. Atev, G. Chen,
A. Szlam, Y. Wang, T. Whitehouse and T. Zhang