Convergence of SDP hierarchies for polynomial optimization on the hypersphere

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Event Speaker: 

Stephanie Wehner (National University of Singapore)

Event Location: 

32-D677

Event Date/Time: 

Monday, November 19, 2012 - 11:00am

Abstract:
We show how to bound the accuracy of a family of semi-definite programming relaxations for the problem of polynomial optimization on the hypersphere. Our method is inspired by a set of results from quantum information known as quantum de Finetti theorems. In particular, we prove a de Finetti theorem for a special class of real symmetric matrices to establish the existence of approximate representing measures for moment matrix relaxations. Joint work with Andrew Doherty (U. of Sydney). Preprint available at http://arxiv.org/abs/1210.5048.
 
Biography:
Stephanie Wehner is a computer scientist at the Centre for Quantum Technologies, National University of Singapore, born in Wuerzburg, Germany. She studied at the University of Amsterdam and obtained her Ph.D. at CWI, before moving to Caltech as a postdoctoral researcher under John Preskill. Since 2010 Wehner is an assistant professor in the department of computer science at the National University of Singapore.