Asymptotic methods in statistical theory
Asymptotic methods in statistical theory
Elements of information theory
Elements of information theory
A Learning Criterion for Stochastic Rules
Machine Learning - Computational learning theory
Rigorous learning curve bounds from statistical mechanics
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
The weighted majority algorithm
Information and Computation
Statistical theory of learning curves under entropic loss criterion
Neural Computation
Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension
Machine Learning - Special issue on computational learning theory
TIGHT WORST-CASE LOSS BOUNDS FOR PREDICTING WITH EXPERT ADVICE
TIGHT WORST-CASE LOSS BOUNDS FOR PREDICTING WITH EXPERT ADVICE
A Bayesian/information theoretic model of bias learning
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
A Bayesian/Information Theoretic Model of Learning to Learn viaMultiple Task Sampling
Machine Learning - Special issue on inductive transfer
Predictability, Complexity, and Learning
Neural Computation
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