## Abstract We present two random search methods for solving discrete stochastic optimization problems. Both of these methods are variants of the stochastic ruler algorithm. They differ from our earlier modification of the stochastic ruler algorithm in that they use different approaches for estimat
The Optimal Discretization of Stochastic Differential Equations
✍ Scribed by Norbert Hofmann; Thomas Müller-Gronbach; Klaus Ritter
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 239 KB
- Volume
- 17
- Category
- Article
- ISSN
- 0885-064X
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
## Abstract Adaptive time‐stepping methods based on the Monte Carlo Euler method for weak approximation of Itô stochastic differential equations are developed. The main result is new expansions of the computational error, with computable leading‐order term in a posteriori form, based on stochastic
In this paper we study infinite-dimensional, second-order Hamilton-Jacobi-Bellman equations associated to the feedback synthesis of stochastic Navier-Stokes equations forced by space-time white noise. Uniqueness and existence of viscosity solutions are proven for these infinite-dimensional partial d
## Abstract Symmetries of stochastic ordinary differential equations (SODEs) are analysed. This work focuses on maintaining the properties of the Weiner processes after the application of infinitesimal transformations. The determining equations (DEs) for first‐order SODEs are derived in an Itô calc