We present an algorithm for learning context free grammars from positive structural examples (unlabeled parse trees). The algorithm receives a parameter in the form of a finite se...
We propose a novel a framework for deriving approximations for intractable probabilistic models. This framework is based on a free energy (negative log marginal likelihood) and ca...
Title of thesis: BOOTSTRAPPING FREE-SPACE OPTICAL NETWORKS Fang Liu, Master of Science, 2004 Thesis directed by: Professor Uzi Vishkin Department of Electrical and Computer Engine...
Abstract. According to the No Free Lunch (NFL) theorems all blackbox algorithms perform equally well when compared over the entire set of optimization problems. An important proble...
This paper introduces a tree generating system called Lexicalized Context-Free Grammar (LCFG) and describes a cubic-time parser for it. LCFG embeds the elegance of the analyses fo...