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DTSTART:20230312T070000
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DTSTART:20221106T060000
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DTSTART;TZID=America/Toronto:20231027T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20231027T170000
URL:https://uwaterloo.ca/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-jeffrey-rosenthal
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West Room: DC 1302 Waterloo ON N2L 3G1 Canada
SUMMARY:David Sprott Distinguished Lecture by Jeffrey Rosenthal
CLASS:PUBLIC
DESCRIPTION:Distinguished Lecture Series\n\nJEFFREY ROSENTHAL\n_University 
 of Toronto_\n\nRoom: DC 1302\n\nSPEEDING UP METROPOLIS USING THEOREMS\n\n-
 ------------------------\n\nMarkov chain Monte Carlo (MCMC) algorithms\, s
 uch as the Metropolis\nalgorithm\, are designed to converge to complicated
  high-dimensional\ntarget distributions\, to facilitate sampling.  The sp
 eed of this\nconvergence is essential for practical use.  In this talk\, 
 we will\npresent several theoretical results which can help improve the\nM
 etropolis algorithm's convergence speed.  Specific topics will\ninclude: 
 diffusion limits\, optimal scaling\, optimal proposal shape\,\ntempering\,
  adaptive MCMC\, the Containment property\, and the notion of\nadversarial
  Markov chains.  The ideas will be illustrated using the\nsimple graphica
 l example available at probability.ca/met.  No\nparticular background kno
 wledge will be assumed.\n\n-------------------------
DTSTAMP:20260410T173219Z
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