In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
Searching in decentralized peer-to-peer networks is a challenging problem. In common applications such as Gnutella, searching is performed by randomly forwarding queries to all pee...
Data noise is present in many machine learning problems domains, some of these are well studied but others have received less attention. In this paper we propose an algorithm for ...
We present the problem of categorizing web services according to a shallow ontology for presentation on a specialist portal, using their WSDL and associated textual documents foun...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...