大阪大学　数理・データ科学教育研究センター
Center for Mathematical Modeling and Data Science,Osaka University

Advanced Multilevel Monte Carlo Methods

Ajay Jasra (National University of Singapore)

1. ホーム
2. セミナー・集中講義
3. セミナー
4. Advanced Multilevel Monte Carlo Methods

大阪大学 数理・データ科学セミナー データ科学セミナーシリーズ 第21回(JST CREST共催)

Advanced Multilevel Monte Carlo Methods

Ajay Jasra (National University of Singapore)

This talk reviews advanced Monte Carlo techniques that are used in the application of multilevel Monte Carlo methods. Multilevel Monte Carlo (MLMC) methods are employed to compute expectations which can be biased in some sense, for instance by using the discretization of the associated probability law. The MLMC method works with a hierarchy of biased approximations. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational costs for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas are generally focused on cases where exact sampling from couples in the hierarchy is possible. However, this talk considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo (MCMC), sequential Monte Carlo which have been applied in the literature and different strategies which facilitates the application of MLMC in practice.