Mark Iwen

Let M be a smooth submanifold of R^n equipped with the Euclidean(chordal) metric. This talk will consider the smallest dimension, m, for which there exists a bi-Lipschitz function f:M →R^m with bi-Lipschitz constants close to one. We will begin by...

Compressive sensing in its most practical form aims to recover a function that exhibits sparsity in a given basis from as few function samples as possible. One of the fundamental results of compressive sensing tells us that $O(s \log^4 N)$ samples...

Compressive sensing has generated tremendous amounts of interest since first being proposed by Emmanuel Candes, David Donoho, Terry Tao, and others a bit more than a decade ago. This mathematical framework has its origins in (i) the observation that...