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SQUIDS Seminar - Nested expectations with kernel quadrature

Dates:5 March 2025
Times:15:00 - 16:00
What is it:Seminar
Organiser:Department of Mathematics
Who is it for:University staff, External researchers, Current University students
Speaker:François-Xavier Briol
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  • In category "Seminar"
  • In group "(Maths) Statistics, quantification of uncertainty, inverse problems and data science"
  • By Department of Mathematics

This paper considers the challenging computational task of estimating nested expectations. Existing algorithms, such as nested Monte Carlo or multilevel Monte Carlo, are known to be consistent but require a large number of samples at both inner and outer levels to converge. Instead, we propose a novel estimator consisting of nested kernel quadrature estimators and we prove that it has a faster convergence rate than all baseline methods when the integrands have sufficient smoothness. We then demonstrate empirically that our proposed method does indeed require fewer samples to estimate nested expectations on real-world applications including Bayesian optimisation, option pricing, and health economics.

Speaker

François-Xavier Briol

Organisation: University College London

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G.113
Alan Turing Building
Manchester

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Jonas Latz

jonas.latz@manchester.ac.uk

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