We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
Linear Programming (LP) relaxations have become powerful tools for finding the most probable (MAP) configuration in graphical models. These relaxations can be solved efficiently u...
David Sontag, Talya Meltzer, Amir Globerson, Tommi...
Theoretical models for the evaluation of quickly improving search strategies, like limited discrepancy search, are based on specific assumptions regarding the probability that a va...
This paper presents a new MRF optimization algorithm, which is derived from Linear Programming and manages to go beyond current state-of-the-art techniques (such as those based on ...
Abstract--In this paper, we investigate the use of messagepassing algorithms for the problem of finding the max-weight independent set (MWIS) in a graph. First, we study the perfor...