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
Bounds on the sample complexity of Bayesian learning using information theory and the VC dimension
COLT '91 Proceedings of the fourth 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
Neural Computation
Decision theoretic generalizations of the PAC model for neural net and other learning applications
Information and Computation
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
Learning by a population of perceptrons
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Distributed cooperative Bayesian learning strategies
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Minimax relative loss analysis for sequential prediction algorithms using parametric hypotheses
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Distributed cooperative mining for information consortia
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
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