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SUMMARY:Quasi-Monte Carlo: structure in the randomness for better sampling
  - Isaac Reid\, University of Cambridge
DTSTART:20231018T100000Z
DTEND:20231018T113000Z
UID:TALK207490@talks.cam.ac.uk
CONTACT:Isaac Reid
DESCRIPTION:Quasi-Monte Carlo (QMC) sampling is well-established as a univ
 ersal tool to improve the convergence of MC methods\, improving the concen
 tration properties of estimators by using low-discrepancy samples to reduc
 e integration error. They replace i.i.d. samples with a correlated ensembl
 e\, carefully constructed to be more ‘diverse’ and hence improve appro
 ximation quality. In this reading group we will discuss both traditional Q
 MC schemes for approximating integrals R^d and recently-proposed counterpa
 rts for discrete space\, teasing out their common themes as we progress to
 wards a general recipe for more efficient sampling. 
LOCATION:Cambridge University Engineering Department\, CBL Seminar room BE
 4-38.
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