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SUMMARY:Nature-Inspired Metaheuristic Algorithms for Generating Optimal Ex
 perimental Designs - Wong\, W-K (UCLA)
DTSTART:20110831T133000Z
DTEND:20110831T140000Z
UID:TALK32586@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:We explore a particle swarm optimization (PSO) method for find
 ing optimal experimental designs. This method is relatively new\, simple y
 et powerful and widely used in many fields to tackle real problems. The me
 thod does not assume the objective function to be optimized is convex or d
 ifferentiable. We demonstrate using examples that once a given regression 
 model is specified\, the PSO method can generate many types of optimal des
 igns quickly\, including optimal minimax designs where effective algorithm
 s to generate such designs remain elusive.\n
LOCATION:Seminar Room 1\, Newton Institute
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