On the Relation between Asymptotic Learning Curve and Renormalizability in Learning Theory

摘要

In this paper we study a statistical estimation problem in which the true distribution is singular for and unrealizable by a learning machine. If the pair of a true distribution and a learning machine stistifies the renormalizable condition, then its learning curve is determined by a universal law. If otherwise, its learning curve is not subject to the universal law.