We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
A monotone distribution P over a (partially) ordered domain assigns higher probability to y than to x if y x in the order. We study several natural problems concerning testing pr...
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...
We propose a new method for measuring the semantic similarity of genes based on path length between their annotation terms in the Gene Ontology. Our method applies an exponential ...
Today, result sets of skyline queries are unmanageable due to their exponential growth with the number of query predicates. In this paper we discuss the incremental re-computation ...