Abstract. Robustness has long been recognised as a critical issue for coevolutionary learning. It has been achieved in a number of cases, though usually in domains which involve so...
In this paper, we propose a cautious cooperative learning approach using distributed case-based reasoning. Our approach consists of two learning mechanisms: individual and coopera...
As data streams are gaining prominence in a growing number of emerging application domains, classification on data streams is becoming an active research area. Currently, the typi...
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...
Abstract. Mechanisms for adapting models, filters, regulators and so on to changing properties of a system are of fundamental importance in many modern identification, estimation...