Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
We use Wikipedia articles to semantically inform the generation of query models. To this end, we apply supervised machine learning to automatically link queries to Wikipedia artic...
We present a novel algorithm for multilingual dependency parsing that uses annotations from a diverse set of source languages to parse a new unannotated language. Our motivation i...
— Metaheuristics such as Estimation of Distribution Algorithms and the Cross-Entropy method use probabilistic modelling and inference to generate candidate solutions in optimizat...
Marcus Gallagher, Ian Wood, Jonathan M. Keith, Geo...
The goal of our current research is machine learning with the help and guidance of a knowledge base (KB). Rather than learning numerical models, our approach generates explicit sy...