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We present a canonical way to turn any smooth parametric family of probability distributions on an arbitrary search space $X$ into a continuous-time black-box optimization method on $X$, the \emph{information-geometric optimization} (IGO) method.
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Learning in Markov random fields using tempered transitions
R. Salakhutdinov · 2009
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Efficient natural evolution strategies
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Information-geometric optimization: A unifying picture via invariance principles
Y. Ollivier, L. Arnold, A. Auger, and N. Hansen · 2011
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High dimensions and heavy tails for natural evolution strategies
T. Schaul, T. Glasmachers, and J. Schmidhuber · 2011
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E. Zhou and J. Hu · 2014
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S. Bhatnagar E. Zhou · 2016
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