brown univ providence ri div of applied mathematics, 2006
To exploit large deviation approximations for allocation and occupancy problems one must solve a deterministic optimal control problem (or equivalently, a...
brown univ providence ri div of applied mathematics, 2002
A heuristic that has emerged in the area of importance sampling is that the changes of measure used to prove large deviation lower bounds give good performance...
brown univ providence ri div of applied mathematics, 2004
We use process level large deviation analysis to obtain the rate function for a general family of occupancy problems. Our interest is the asymptotics of the...
A large deviation principle is established for a general class of stochastic flows in the small noise limit. This result is then applied to a Bayesian...
brown univ providence ri lefschetz center for dynamical systems, 2007
The large deviations analysis of solutions to stochastic differential equations and related processes is often based on approximation. The construction and...
brown univ providence ri lefschetz center for dynamical systems, 2006
Importance sampling is a variance reduction technique for efficient estimation of rare-event probabilities by Monte Carlo. For random variables with heavy...
brown univ providence ri div of applied mathematics, 2005
Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of...
brown univ providence ri div of applied mathematics, 2005
In this paper, refined large deviation asymptotics are derived for the classical occupancy problem. The asymptotics are established for a sequential filling...
brown univ providence ri div of applied mathematics, 2003
A Large Deviations Principle (LDP), demonstrated for occupancy problems with indistinguishable balls, is generalized to the case in which balls may be...
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