Speaker
Danny Bickson
(The Hebrew University of Jerusalem)
Description
The canonical linear-algebraic problem of solving a system
of linear equations arises in numerous contexts in the
mathematical sciences and engineering. In this talk, we
introduce an efficient Gaussian belief propagation (GaBP)
solver that does not involve direct matrix inversion. The
iterative nature of our approach allows for a distributed
message-passing implementation of the solution algorithm. We
discuss the properties of the GaBP solver, including
convergence, exactness, computational complexity,
message-passing efficiency and its relation to classical
solution methods. The attractiveness of the proposed solver,
in comparison to conventional iterative solution methods, is
demonstrated using numerical examples and applications, like
linear detection.
The talk is based on a joint work with Prof. Jack K. Wolf (UCSD), Prof. Paul H. Siegel (UCSD), Dr. Ori Shental (UCSD) and Prof. Danny Dolev (HUJI).
The talk is based on a joint work with Prof. Jack K. Wolf (UCSD), Prof. Paul H. Siegel (UCSD), Dr. Ori Shental (UCSD) and Prof. Danny Dolev (HUJI).
