Advanced Multilevel Monte Carlo Methods


Ajay Jasra (National University of Singapore)
  1. MMDSについて
  2. MMDSの教員・組織
  3. MMDSで学びたい方へ
  4. カリキュラム
  5. MMDSの活動

  6. 学内向け情報



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.

講 師:
Ajay Jasra (National University of Singapore)
テーマ:
Advanced Multilevel Monte Carlo Methods
日 時:
2017年06月27日(火)14:40-16:10
場 所:
大阪大学(豊中キャンパス) 大学院基礎工学研究科 I407数理セミナー室3
参加費:
無料
アクセス:
会場までのアクセスは下記URLをご参照ください。
http://www.es.osaka-u.ac.jp/ja/access.html
お問い合せ:
本ウェブサイトの「お問い合せ」のページをご参照ください。