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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20181221T160904Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181115T083000
DTEND;TZID=America/Chicago:20181115T170000
UID:submissions.supercomputing.org_SC18_sess324_post173@linklings.com
SUMMARY:A Massively Parallel Evolutionary Markov Chain Monte Carlo Algorit
 hm for Sampling Complicated Multimodal State SpacesState
DESCRIPTION:Poster\nTech Program Reg Pass, Exhibits Reg Pass\n\nA Massivel
 y Parallel Evolutionary Markov Chain Monte Carlo Algorithm for Sampling Co
 mplicated Multimodal State SpacesState\n\nCho, Liu\n\nWe develop an Evolut
 ionary Markov Chain Monte Carlo (EMCMC) algorithm for sampling from large 
 multi-modal state spaces. Our algorithm combines the advantages of evoluti
 onary algorithms (EAs) as optimization heuristics and the theoretical conv
 ergence properties of Markov Chain Monte Carlo (MCMC) algorithms for sampl
 ing from unknown distributions. We harness massive computational power wit
 h a parallel EA framework that guides a large set of Markov chains. Our al
 gorithm has applications in many different fields of science. We demonstra
 te its effectiveness with an application to political redistricting.
URL:https://sc18.supercomputing.org/presentation/?id=post173&sess=sess324
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