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UID:DSC-3963
DTSTART;TZID=Europe/Berlin:20121108T140000
SEQUENCE:1349868391
TRANSP:OPAQUE
DTEND;TZID=Europe/Berlin:20121108T150000
URL:https://www.dresden-science-calendar.de/calendar/de/detail/3963
LOCATION:TUD Willers-Bau\, Zellescher Weg 12-1401069 Dresden
SUMMARY:Sbalzarini: From stochastic optimization to more efficient simulati
 on algorithms
CLASS:PUBLIC
DESCRIPTION:Speaker: Dr. Ivo F. Sbalzarini\nInstitute of Speaker: Max Planc
 k Institute of Molecular Cell Biology and Genetics\, Dresden\nTopics:\nMat
 hematik\n Location:\n  Name: TUD Willers-Bau (WIL A 124)\n  Street: Zelles
 cher Weg 12-14\n  City: 01069 Dresden\n  Phone: \n  Fax: \nDescription: St
 ochastic dynamics provides a rich framework for analyzing and designing op
 timization  and simulation methods. In continuous black-box optimization\,
  bio-inspired concepts from  Darwinian evolution have triggered the develo
 pment of numerous algorithms\, including  Genetic Algorithms and Evolution
  Strategies. Despite the success of these algorithms in  real-world applic
 ations\, however\, the underlying stochastic dynamics remains poorly  unde
 rstood\, and guarantees of solution quality and convergence are not availa
 ble for any  but the simplest toy cases. We analyze stochastic optimizatio
 n algorithms as probability  processes based on Gaussian Adaptation and il
 lustrate several analogies and connections  with stochastic processes in c
 hemistry and physics\, as well as with adaptive MCMC  sampling. Exploiting
  these connections helps understand stochastic optimization  algorithms\, 
 but also inspires more efficient algorithms for adaptive sampling and  sto
 chastic simulations. The latter is shown for chemical kinetics on the exam
 ple of the  PDM exact Stochastic Simulation Algorithm.  
DTSTAMP:20260805T130928Z
CREATED:20121009T170212Z
LAST-MODIFIED:20121010T112631Z
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