LANS Informal Seminar
"Algorithms for sparse reconstruction"
DATE: September 24, 2008
TIME: - Description:
SPEAKER: Michael Friedlander, University of British Columbia
LOCATION: Building 221, Room A-261, Argonne National Laboratory
Many imaging and compressed-sensing applications seek to approximate a signal as a linear combination of only a few elementary atoms drawn from a large collection. This is known as sparse reconstruction. The basis pursuit (BP) approach minimizes the 1-norm of the solution, and the BP denoising (BPDN) approach balances it against the least-squares fit. I will discuss the role of duality in revealing some unexpected and useful properties of these problems, and will show how they can lead to practical, large-scale algorithms.
Please send questions or suggestions to Krishna: snarayan at mcs.anl.gov.