Ioannis Dassios (University of Edinburgh)

Second-order methods for sparse signal reconstruction
Wednesday 23 October 2013 at 15.30, JCMB 6206

Abstract

In this talk we consider a family of optimization problems which arise in the field of signal reconstruction, i.e. L1 and Total-Variation (TV) regularized Least-Squares (LS), L1-Analysis and combinations. There has been a considerable effort for the development of first-order algorithms for L1 and TV regularized LS. State-of-the-art implementations such as SPGL1 and TwIST can solve large-scale problems in few seconds on a PC. However, the broader family of problems studied in this talk challenge these methods. We solve this family of problems in two steps. First, appropriate smoothing of the problems is applied, second, a class of Newton-type algorithms is employed, embedded in a continuation framework for further acceleration. Moreover, we present perturbation analysis of the optimal solution obtained by the smoothed problem as a function of a smoothing parameter.

Seminars by year

Current 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996