Title	Multilevel Monte Carlo methods
Creator	Giles, Mike
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2015-06-04T09:06
Description	With Monte Carlo methods, to achieve improved accuracy one often requires more expensive sampling (such as a finer timestep discretisation of a stochastic differential equation) in addition to more samples. Multilevel Monte Carlo methods aim to avoid this by combining simulations with different levels of accuracy. In the best cases, the average cost of each sample is independent of the overall target accuracy, leading to very large computational savings. The talk will emphasise the simplicity of the approach, give an overview of the range of applications being worked on by various researchers, and mention some recent extensions including work by Peter Glynn and Chang-han Rhee. Applications to be discussed will include financial modelling, engineering uncertainty quantification, stochastic chemical reactions, and the Feynman-Kac formula for high-dimensional parabolic PDEs. Further information can be obtained from http://people.maths.ox.ac.uk/gilesm/acta/
Extent	60 minutes
Subject	Mathematics; Probability theory and stochastic processes; Statistics; Operation research
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: Oxford University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2016-01-04
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivs 2.5 Canada
DOI	10.14288/1.0221666
URI	http://hdl.handle.net/2429/56150
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Faculty
Rights URI	http://creativecommons.org/licenses/by-nc-nd/2.5/ca/
Aggregated Source Repository	DSpace

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Multilevel Monte Carlo methods Giles, Mike

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