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PAC learning under helpful distributions

François DenisRémi Gilleron — 2001

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

A PAC teaching model – under helpful distributions – is proposed which introduces the classical ideas of teaching models within the PAC setting: a polynomial-sized teaching set is associated with each target concept; the criterion of success is PAC identification; an additional parameter, namely the inverse of the minimum probability assigned to any example in the teaching set, is associated with each distribution; the learning algorithm running time takes this new parameter into account. An Occam...

PAC Learning under Helpful Distributions

François DenisRémi Gilleron — 2010

RAIRO - Theoretical Informatics and Applications

A PAC teaching model -under helpful distributions -is proposed which introduces the classical ideas of teaching models within the PAC setting: a polynomial-sized teaching set is associated with each target concept; the criterion of success is PAC identification; an additional parameter, namely the inverse of the minimum probability assigned to any example in the teaching set, is associated with each distribution; the learning algorithm running time takes this new parameter into account. ...

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