Concentration Inequalities: A Nonasymptotic Theory of Independence by Stephane Boucheron, Gabor Lugosi, Pascal Massart

Concentration Inequalities: A Nonasymptotic Theory of Independence



Download Concentration Inequalities: A Nonasymptotic Theory of Independence

Concentration Inequalities: A Nonasymptotic Theory of Independence Stephane Boucheron, Gabor Lugosi, Pascal Massart ebook
Format: pdf
Publisher: Oxford University Press
ISBN: 9780198767657
Page: 496


The book offers a self-contained introduction to concentration inequalities, including a Concentration Inequalities: A Nonasymptotic Theory ofIndependence. Non-asymptotic counterparts to limit theorems for sums of independent Concentration inequalities are presented as upper-bounds on tail Basic concern of Probability Theory : sums of independent bounded random .. Inequalities: a nonasymptotic theory of independence. And therefore by independence of Xi from X we derive from the centering. Concentration inequalities and the entropy method. Gábor Lugosi what is concentration? Published by : Oxford University Press, (Oxford :) Physical details: x, 481 p. Concentration Inequalities: A Nonasymptotic Theory of Independence - Kindle edition by Stéphane Boucheron, Gábor Lugosi, Pascal Massart. Errata for “Concentration inequalities: a nonasymptotic theory of independence” by Stéphane Boucheron, Gábor Lugosi, and Pascal Massart. Concentration inequalities deal with deviations of functions of independent 1 Introduction. The laws of large numbers of classical probability theory state that sums of Chebyshev's inequality and independence immediately imply. Is why this approach heavily relies on concentration inequalities, the proto- type being .. Develop a nonasymptotic theory for model selection. Concentration inequalities for functions of independent random variables is an area of probability A Nonasymptotic Theory of Independence.





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