Part Overview of the Probably Approximately Correct PAC Learning Framework
نویسنده
چکیده
Here we survey some recent theoretical results on the e ciency of machine learning algorithms The main tool described is the notion of Probably Approximately Correct PAC learning intro duced by Valiant We de ne this learning model and then look at some of the results obtained in it We then consider some criticisms of the PAC model and the extensions proposed to address these criticisms Finally we look brie y at other models recently proposed in computational learning theory
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