Titlebook: Computational Learning Theory; 4th European Confere Paul Fischer,Hans Ulrich Simon Conference proceedings 1999 Springer-Verlag Berlin Heide

动作谜

Mumble

Cholagogue

Ambulatory

量被毁坏

Strukturiert es Programmieren in Cnsion with respect to the average case. We show that the teaching complexity in the best case is bounded by the self-directed learning complexity. It is also bounded by the VCdimension, if the concept class is intersection-closed. This does not hold for arbitrary concept classes. We find examples which substantiate this gap.

忘恩负义的人

Learnability of Quantified Formulasroperty of the basis of relations, their clone of polymorphisms. Finally, we use this technique to give a simpler proof of the already known dichotomy theorem over boolean domains and we present an extension of this theorem to bases with infinite size.

柔美流畅

人造

A Geometric Approach to Leveraging Weak Learners For this potential function, the direction of steepest descent can have negative components. Therefore we provide two transformations for obtaining suitable distributions from these directions of steepest descent. The resulting algorithms have bounds that are incomparable to AdaBoost’s, and their empirical performance is similar to AdaBoost’s.

Brochure

Hardness Results for Neural Network Approximation Problemsnits, it is NP-hard to find such a network that makes mistakes on a proportion smaller than .. of the examples, for some constant .. We prove a similar result for the problem of approximately minimizing the quadratic loss of a two-layer network with a sigmoid output unit.

配置

Learning Range Restricted Horn Expressionser utilises a previous result on learning function free Horn expressions. This is done by using techniques for flattening and unflattening of examples and clauses, and a procedure for model finding for range restricted expressions. This procedure can also be used to solve the implication problem for this class.