Large Deviations and Idempotent Probability

164 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

On large deviations of coupled diffusions with time scale separation (2013, background): “roperty that a certain process be a martingale, it may also arise out of the description of the process dynamic. The large deviation rate function is identiﬁed by the limiting relation, see Puhalskii [38, 39, 40], Puhalskii and Vladimirov [41] for various case studies. In this paper, the large devia”
Large Deviations for Stochastic Processes (2006, unknown): “The emphasis will be on the use of compactness ideas (more extensive results are in Puhalskii [ 13 ]).”
Conditional Essential Suprema with Applications (2003, background): “The goal of the idempotent probability (or “possibility”) theory developed in [ 13 ] are the large deviation theorems while our goal is the use of conditional max in classical probability theory.”
Ergodic Markov processes and Poisson equations (lecture notes) (2016, background): “However, this simple result does not pretend to be even an introduction to large deviations, about which theory see [5, 7, 13, 14, 17, 36, 42], et al.”
Asymptotic behavior of random determinants in the Laguerre, Gram and Jacobi ensembles (2006, background): “…in Subsection 5.5,Un and Vn bethetwoLaguerrevariables.From theexponentialtightnessofUn and Vn,we deduce easily the exponentialtightnessofW n.From Puhalskii(2001), the sequence W n containssubsequencessatisfying LDP.Ifforsuch a subsequence wecallIp the ratefunction,the independence gives I U =…”