Webinar DISA-DSM: stochastic analysis, statistics and machine learning

09:11 by Diana Unander

Our new DISA-group Deterministic and Stochastic Modelling (DSM) invites you to a seminar on Tuesday 27th at 13.00, this seminar is a part of a seminar series so keep an eye out for more information.

Title: Rare events simulation: least-squares Monte Carlo method vs deep learning based shooting method

Speaker: Omar Kebiri (University B-TU Cottbus-Senftenberg, Germany)

Abstract: When computing small probabilities associated with rare events by Monte Carlo it so happens that the variance of the estimator is of the same order as the quantity of interest. Importance sampling is a means to reduce the variance of the Monte Carlo estimator by sampling from an alternative probability distribution under which the rare event is no longer rare. Determine the optimal (i.e. zero variance) changes of measure leads to a stochastic optimal control problem. The control problem can be solved by a stochastic approximation algorithm, using the Feynman-Kac representation of the associated dynamic programming equations which leads to an FBSDE, and we discuss numerical aspects for high-dimensional problems along with simple toy examples using two methods: least-squares Monte Carlo method and deep learning based shooting method.
Joint work with Carsten Hartmann, Lara Neureither, and Lorenz Richter.

Practical information: We will book a room at LNU for those who wants to attend physically the seminar. Because of space restrictions due to Covid-19, please let me know if you want to do that, otherwise a link will be provided. Contact Nacira Agram – nacira.agram@lnu.se for more information.

Diana Unander

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