Introductory resources on Computational Learning Theory Recently I've been reading a decent number of CoLT papers. Although I don't struggle with the individual papers (at least not more than I usually struggle with other theory papers), I don't feel I have a good broad grasp of the field as a whole.
Is there a standard text, surveys, or lecture notes for introducing CoLT at the graduate level?
I have a basic Theory A background, but no specific knowledge of Machine Learning or Statistics. I am mostly interested in things like PAC-learning and learning automata, and less interested in things like Bayesian inference and VC theory.
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Resource / book for recent advances in statistical learning theory
Kearns and Vazirani is maybe a bit old, but good introduction.