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Sums of independent, bounded random variables concentrate around their expectation approximately as well a Gaussian of the same variance.
On a modification of chebyshev?s inequality and of the error formula of laplace
Sergei Bernstein · 1924
Earlier work this paper cites.
A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations
Herman Chernoff · 1952
Earlier work this paper cites.
Probability inequalities for sums of bounded random variables
Wassily Hoeffding · 1963
Earlier work this paper cites.
Weighted sums of certain dependent random variables
Kazuoki Azuma · 1967
Earlier work this paper cites.
On the method of bounded differences
Colin McDiarmid · 1989
Earlier work this paper cites.
Chernoff-hoeffding bounds for applications with limited independence
Jeanette P Schmidt, Alan Siegel, and Aravind Srinivasan · 1995
Cited alongside, same era.
Strong converse for identification via quantum channels
Rudolf Ahlswede and Andreas Winter · 2002
Cited alongside, same era.
Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
Cited alongside, same era.
Constructive proofs of concentration bounds
Russell Impagliazzo and Valentine Kabanets · 2010
Cited alongside, same era.
Elements of information theory
Thomas M Cover and Joy A Thomas · 2012
Cited alongside, same era.
Subgaussian random variables: An expository note
Omar Rivasplata · 2012
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Weighted polynomial approximations: Limits for learning and pseudorandomness
Mark Bun and Thomas Steinke · 2015
Later among the works it cites.
Algorithmic stability for adaptive data analysis
Raef Bassily, Kobbi Nissim, Adam Smith, Thomas Steinke, Uri Stemmer, and Jonathan Ullman · 2016
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Chernoff bounds
Wolfgang Mulzer · 2016
Later among the works it cites.
Concentration bounds for high sensitivity functions through differential privacy
Kobbi Nissim and Uri Stemmer · 2017
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