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)
On the computational complexity of approximating distributions by probabilistic automata
COLT '90 Proceedings of the third annual workshop on Computational learning theory
A Learning Criterion for Stochastic Rules
Machine Learning - Computational learning theory
Machine Learning
Rigorous learning curve bounds from statistical mechanics
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Noise-tolerant learning near the information-theoretic bound
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
On the complexity of learning from drifting distributions
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Strong minimax lower bounds for learning
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Computational sample complexity
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Uniform-distribution attribute noise learnability
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Uniform-distribution attribute noise learnability
Information and Computation
Combining linguistic and statistical analysis to extract relations from web documents
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
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