Communications of the ACM
Machine learning: a theoretical approach
Machine learning: a theoretical approach
Computational learning theory: an introduction
Computational learning theory: an introduction
Computational learning theory: survey and selected bibliography
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Learning Conjunctions of Horn Clauses
Machine Learning - Computational learning theory
The weighted majority algorithm
Information and Computation
An introduction to computational learning theory
An introduction to computational learning theory
Exact learning Boolean functions via the monotone theory
Information and Computation
On the boosting ability of top-down decision tree learning algorithms
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Journal of the ACM (JACM)
An efficient membership-query algorithm for learning DNF with respect to the uniform distribution
Journal of Computer and System Sciences
Efficient noise-tolerant learning from statistical queries
Journal of the ACM (JACM)
Reinforcement learning and mistake bounded algorithms
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Machine learning and data mining
Communications of the ACM
Machine Learning
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Some remarks are given on the history, the main results and the future research directions of computational learning theory.