An extension of McDiarmid's inequality

November 17, 2015 ยท Declared Dead ยท ๐Ÿ› International Symposium on Information Theory

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Authors Richard Combes arXiv ID 1511.05240 Category cs.LG: Machine Learning Cross-listed math.PR, math.ST Citations 37 Venue International Symposium on Information Theory Last Checked 6 months ago
Abstract
We generalize McDiarmid's inequality for functions with bounded differences on a high probability set, using an extension argument. Those functions concentrate around their conditional expectations. We further extend the results to concentration in general metric spaces.
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