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Robust Supervised Learning

Published in Cambridge University Press eBooks • Aug 24, 2023
NobleIDNI3P67W63R80S56
Authors:
Ilias Diakonikolas
,
Daniel M. Kane

Abstract

Supervised machine learning techniques developed in the Probably Approximately Correct, Maximum A Posteriori, and Structural Risk Minimiziation frameworks typically make the assumption that the test data a learner is applied to is drawn from the same distribution as the training data. In various pro...

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