Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
Graph sub-isomorphism is a very common approach to solving pattern search problems, but this is a NP-complete problem. This way, it is necessary to invest in research of approxima...
Abstract Consider a random graph model where each possible edge e is present independently with some probability pe. Given these probabilities, we want to build a large/heavy match...
Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching...
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...