Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holme...
Abstract. In this paper, we show that the optimization of density forecasting models for regression in machine learning can be formulated as a multi-objective problem. We describe ...
The IODA methodology allows automated construction of models from an ontology, consisting of generic interactions that we can assign to families of agents. Thanks to the measuremen...
Wikipedia provides a knowledge base for computing word relatedness in a more structured fashion than a search engine and with more coverage than WordNet. In this work we present e...
The typical difficulty of various NP-hard problems varies with simple parameters describing their structure. This behavior is largely independent of the search algorithm, but depe...