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Fast Rates in Statistical and Online Learning

van Erven, Tim; Grunwald, Peter; Mehta, Nishant A; Reid, Mark; Williamson, Robert


The speed with which a learning algorithm converges as it is presented with more data is a central problem in machine learning — a fast rate of convergence means less data is needed for the same level of performance. The pursuit of fast rates in online and statistical learning has led to the discovery of many conditions in learning theory under which fast learning is possible. We show that most of these conditions are special cases of a single, unifying condition, that comes in two forms: the...[Show more]

CollectionsANU Research Publications
Date published: 2015
Type: Journal article
Source: Journal of Machine Learning Research
Access Rights: Open Access


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