Specification and simulation of statistical query algorithms for efficiency and noise tolerance

A theory of the learnable

Communications of the ACM

Learning from good and bad data

Learning from good and bad data

Learning in the presence of malicious errors

STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing

A general lower bound on the number of examples needed for learning

Information and Computation

Learnability and the Vapnik-Chervonenkis dimension

Journal of the ACM (JACM)

The Strength of Weak Learnability

Machine Learning

Boosting a weak learning algorithm by majority

COLT '90 Proceedings of the third annual workshop on Computational learning theory

An improved boosting algorithm and its implications on learning complexity

COLT '92 Proceedings of the fifth annual workshop on Computational learning theory

Decision theoretic generalizations of the PAC model for neural net and other learning applications

Information and Computation

Efficient noise-tolerant learning from statistical queries

STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing

Statistical queries and faulty PAC oracles

COLT '93 Proceedings of the sixth annual conference on Computational learning theory

Weakly learning DNF and characterizing statistical query learning using Fourier analysis

STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing

On learning from noisy and incomplete examples

COLT '95 Proceedings of the eighth annual conference on Computational learning theory