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ref: work-0 tags: covariance matrix adaptation learning evolution continuous function normal gaussian statistics date: 06-30-2009 15:07 gmt revision:0 [head]

http://www.lri.fr/~hansen/cmatutorial.pdf

  • Details a method of sampling + covariance matrix approximation to find the extrema of a continuous (but intractable) fitness function
  • HAs flavors of RLS / Kalman filtering. Indeed, i think that kalman filtering may be a more principled method for optimization?
  • Can be used in high-dimensional optimization problems like finding optimal weights for a neural network.
  • Optimum-seeking is provided by weighting the stochastic samples (generated ala a particle filter or unscented kalman filter) by their fitness.
  • Introductory material is quite good, actually...