When: September 23, 2015, 12:30 PM
Location: Researchers' Link, 2nd floor of the Discovery Building
Contact: 608-316-4401, firstname.lastname@example.org
Geoffrey Schiebinger and Elina Robeva
Two 30 minute talks.
Presenting in the Researchers’ Link
Sparse Inverse Problems: Theory, Algorithms, and Applications
A common prior in modern statistical signal processing is that an observed signal is the noisy measurement of a few weighted sources. For example, the image of a collection of point sources of light can be parameterized by their locations and intensities. The goal of superresolution is to remove the blur induced by diffraction by solving for the locations and intensities of the individual point sources. This talk will introduce the basics of sparse inverse problems, present an algorithm to solve them, and discuss some theoretical guarantees for recovery. Throughout, we will focus on superresolution imaging as an example of a sparse inverse problem.
The Geometry of Positive Semidefinite Rank
I will first define positive semidefinite rank and mention some of its applications. We study the set of matrices of given psd rank. This set is semialgebraic. As a first step to giving a semialgebraic description, we describe its boundary. This is ongoing work with Kaie Kubjas and Richard Robinson.
SILO is a lecture series with speakers from the UW faculty, graduate students or invited researchers that discuss mathematical related topics. The seminars are organized by WID’s Optimization research group.
SILO’s purpose is to provide a forum that helps connect and recruit mathematically-minded graduate students. SILO is a lunch-and-listen format, where speakers present interesting math topics while the audience eats lunch.