Intrinsic complexity is used to measure the complexity of learning areas limited by broken-straight lines (called open semi-hulls) and intersections of such areas. Any strategy le...
A class C of recursive functions is called robustly learnable in the sense I (where I is any success criterion of learning) if not only C itself but even all transformed classes Î...
John Case, Sanjay Jain, Frank Stephan, Rolf Wiehag...
A classical learning problem in Inductive Inference consists of identifying each function of a given class of recursive functions from a ï¬nite number of its output values. Unifor...
We show that the class of monotone 2O( √ log n)-term DNF formulae can be PAC learned in polynomial time under the uniform distribution from random examples only. This is an expo...
We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm ...
We consider geometric conditions on a labeled data set which guarantee that boosting algorithms work well when linear classiï¬ers are used as weak learners. We start by providing ...
Abstract. We develop three new techniques to build on the recent advances in online learning with kernels. First, we show that an exponential speed-up in prediction time per trial ...