Titlebook: Computational Learning Theory; 15th Annual Conferen Jyrki Kivinen,Robert H. Sloan Conference proceedings 2002 Springer-Verlag Berlin Heidel

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Entropy, Combinatorial Dimensions and Random Averages function-class setup. Using this parameter we establish entropy bounds for subsets of the .-dimensional unit cube, and in particular, we present new bounds on the empirical covering numbers and gaussian averages associated with classes of functions in terms of the fat-shattering dimension.

Reclaim

Mixability and the Existence of Weak Complexitiesthat for many non-mixable games .(.) still converges to 1. The condition .(.) → 1 is shown to imply the existence of weak predictive complexity and it is proved that many games specify complexity up to √..

Water-Brash

BAIT

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https://doi.org/10.1007/978-3-642-88312-5vex then one can obtain better sample complexity bounds than usual. It has been claimed that there is a lower bound that showed there was an essential gap in the rate. In this paper we show that the lower bound proof has a gap in it. Although we do not provide a definitive answer to its validity. Mo

敬礼

摄取

Erkenntnisbeitrag der Untersuchung,obtain bounds on the continuity modulus on the convex hull of a function class in terms of the same quantity for the class itself. We also obtain new bounds on generalization error in terms of localized Rademacher complexities. This allows us to prove new results about generalization performance for

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