Yosi Keller received the BSc degree in Electrical Engineering in 1994 from the Technion-Israel Institute of Technology, Haifa. He received the MSc and PhD degrees in electrical engineering from Tel-Aviv University, Tel-Aviv, in 1998 and 2003, respectively. From 2003 to 2006 he was a Gibbs assistant professor with the Department of Mathematics, Yale University. He is an Associate Professor at the Faculty of Engineering in Bar Ilan University, Israel. His research relates to the applications of graph theory and machine learning to signal processing, computer vision and 3D modelling. His talk takes place on Thursday, November 26, 1pm in room E105.
Probabilistic approach to high order assignment problems
A gamut of computer vision and engineering problems can be cast as high order matching problems, where one considers the affinity/probability of two or more assignments simultaneously. The spectral matching approach of Leordeanu and Hebert (2005) was shown to provide an approximate solution of this np-hard problem. It this talk we present recent results on the probabilistic interpretation of spectral matching. We extend the results of Zass and Shashua (2008) and provide a probabilistic interpretation to the spectral matching and graduated assignment (1996) algorithms. We then derive a new probabilistic matching scheme, and show that it can be extended to high order matching scheme, via a dual marginalization-decomposition scheme. We will present a novel Integer Least Squares algorithm and apply it to the decoding of MIMO and OFDM channels, in the uncoded and coded cases, respectively. Joint work with Amir Egozi, Michael Chertok , Avi Septimus, Ayelet Haimovitch, Shimrit Haber and Dr. Itzik Bergel.