Communications of the ACM
Learning from good and bad data
Learning from good and bad data
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)
Bounding sample size with the Vapnik-Chervonenkis dimension
Discrete Applied Mathematics
Learning in the presence of malicious errors
SIAM Journal on Computing
Efficient noise-tolerant learning from statistical queries
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
General bounds on the number of examples needed for learning probabilistic concepts
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
A result of Vapnik with applications
Discrete Applied Mathematics
Machine Learning
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
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