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From Exact Learning to Computing Boolean Functions and Back Again

The goal of the paper is to relate complexity measures associated with the evaluation of Boolean functions (certificate complexity, decision tree complexity) and learning dimensions used to characterize exact learning (teaching dimension, extended teaching dimension). The high level motivation is to discover non-trivial relations between exact learning of an unknown concept and testing whether an unknown concept is part of a concept class or not. Concretely, the goal is to provide lower and upper bounds of complexity measures for one problem type in terms of the other.

preprint2012arXivOpen access
Sergiu Goschin
Machine LearningDiscrete Mathematics
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Sergiu Goschin

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