The learning complexity of smooth functions of a single variable
Don Kimber, Philip M. Long · 1992
We study the on-line learning of classes of functions of a single real variable formed through bounds on various norms of functions' derivatives. We determine the best bounds obtainable on the worst-case sum of squared errors (also “absolute” errors) for several such classes.