DoctoralIn this note we introduce and discuss a few concentration tools for the study of concentration inequalities on the real line. After recalling versions of the Chernoff method, we move to concentration inequalities for predictable processes. We especially focus on bounds that enable to handle the sum of real-valued random variables, where the number of summands is itself a random stopping time, and target fully explicit and empirical bounds. We then discuss some important other tools, such as the Laplace method and the transportation lemma
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...
DoctoralIn this note we introduce and discuss a few concentration tools for the study of concentrati...
DoctoralIn this note we introduce and discuss a few concentration tools for the study of concentrati...
We give a combinatorial proof of the Chernoff-Hoeffding concentration bound [Che52, Hoe63], which sa...
The classical Gaussian concentration inequality for Lipschitz functions is adapted to a setting wher...
Concentration inequalities deal with deviations of functions of independent random variables from th...
Concentration inequalities deal with deviations of functions of independent random variables from th...
Concentration inequalities are fundamental tools in probabilistic combinatorics and theoretical comp...
Using the method of transportation-information inequality introduced in \cite{GLWY}, we establish Be...
Götze F, Sambale H, Sinulis A. Concentration Inequalities for Bounded Functionals via Log-Sobolev-Ty...
A nonnegative coarse Ricci curvature for a Markov chain and the existence of an attractive point imp...
If a random variable is not exponentially integrable, it is known that no concentration inequality h...
If a random variable is not exponentially integrable, it is known that no concentration inequality h...
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...
DoctoralIn this note we introduce and discuss a few concentration tools for the study of concentrati...
DoctoralIn this note we introduce and discuss a few concentration tools for the study of concentrati...
We give a combinatorial proof of the Chernoff-Hoeffding concentration bound [Che52, Hoe63], which sa...
The classical Gaussian concentration inequality for Lipschitz functions is adapted to a setting wher...
Concentration inequalities deal with deviations of functions of independent random variables from th...
Concentration inequalities deal with deviations of functions of independent random variables from th...
Concentration inequalities are fundamental tools in probabilistic combinatorics and theoretical comp...
Using the method of transportation-information inequality introduced in \cite{GLWY}, we establish Be...
Götze F, Sambale H, Sinulis A. Concentration Inequalities for Bounded Functionals via Log-Sobolev-Ty...
A nonnegative coarse Ricci curvature for a Markov chain and the existence of an attractive point imp...
If a random variable is not exponentially integrable, it is known that no concentration inequality h...
If a random variable is not exponentially integrable, it is known that no concentration inequality h...
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...
International audienceNon-Gaussian concentration estimates are obtained for invariant probability me...