General Bounds on Statistical Query Learning and PAC Learning with Noise via Hypothesis Boosting
نویسندگان
چکیده
منابع مشابه
General Bounds on Statistical Query Learning and PAC Learning with Noise via Hypothesis Bounding
We derive general bounds on the complexity of learning in the Statistical Query model and in the PAC model with classification noise. We do so by considering the problem of boosting the accuracy of weak learning algorithms which fall within the Statistical Query model. This new model was introduced by Kearns [12] to provide a general framework for efficient PAC learning in the presence of class...
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ژورنال
عنوان ژورنال: Information and Computation
سال: 1998
ISSN: 0890-5401
DOI: 10.1006/inco.1998.2664