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Theory and software for sparse approximation algorithm phase transitions.

Jared Tanner, Professor of Mathematics, University of Edinburgh

Date and Time: Nov 16, 2011 (12:30 PM)
Location: Orchard room (3280) at the Wisconsin Institute for Discovery Building


Abstract: We review the eigen-analysis and convex polytope approaches for
the development of sparse approximation and compressed sensing algorithms.
Problems which can be recast as convex relaxations are amenable to a precise
analysis, but non-convex formulated algorithms have a dramatically less precise
theoretical understanding. We present a gpu accelerated software package for
the empirical investigation of non-convex algorithms. Large scale testing reveals
a map of problem parameters and which algorithm has the lowest complexity for
that problem parameters.

This work is joint with Bah, Blanchard, and Donoho.