After two decades of research on automated discovery, many principles are shaping up as a foundation of discovery science. In this paper we view discovery science as automation of ...
This article addresses collaborative learning in a multiagent system: each agent revises incrementally its beliefs B (a concept representation) to keep it consistent with the whol...
Gauvain Bourgne, Dominique Bouthinon, Amal El Fall...
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
Small-sample learning in image retrieval is a pertinent and interesting problem. Relevance feedback is an active area of research that seeks to find algorithms that are robust wi...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...