Abstract
The importance of learning capability for the realization of flexible information processing is being recognized lately, and active research in the area of machine learning is being pursued from various approaches. Among them is the field of computational learning theory, whose goal is to formally model learning activities and analyze the complexity of learning problems in the learning models thus set forth, both from computational and statistical points of view. This article will review some of the new learning models in this field as well as the results obtained concerning them. In particular, we focus on the learning models introduced and studied by researchers at NEC C&C Research Laboratories.
