ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
On Using Extended Statistical Queries to Avoid Membership Queries
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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We derive general bounds on the complexity of learning in the statistical query model and in the PAC model with classification noise. We do so by considering the problem of boosting the accuracy of weak learning algorithms which fall within the statistical query model. This new model was introduced by M. Kearns (1993) to provide a general framework for efficient PAC learning in the presence of classification noise.