Tuesday, 15:15 - 15:40 h, Room: H 1028


Andreas Tillmann
Heuristic optimality check and computational solver comparison for basis pursuit

Coauthors: Dirk A. Lorenz, Marc E. Pfetsch


The problem of finding a minimum l1-norm solution to an
underdetermined linear system is an important problem in compressed
sensing, where it is also known as basis pursuit. We propose a
heuristic optimality check (HOC) as a general tool for
l1-minimization, which often allows for early termination by
"guessing'' a primal-dual optimal pair based on an approximate
support. Moreover, we provide an extensive numerical comparison of
various state-of-the-art l1-solvers that have been proposed during
the last decade. The computational evaluation also includes a novel
subgradient algorithm which employs adaptive approximate projections
using conjugate gradients, and provides empirical evidence for the
effectiveness of the proposed HOC.


Talk 1 of the invited session Tue.3.H 1028
"Algorithms for sparse optimization I" [...]
Cluster 21
"Sparse optimization & compressed sensing" [...]


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