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Optimization via Information Geometry

Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 114)

Abstract

Information Geometry has been used to inspire efficient algorithms for black-box optimization, both in the combinatorial and in the continuous case. We give an overview of the authors’ research program and some specific contribution to the underlying theory.

Keywords

Vector Bundle Exponential Family Bounded Continuous Function Natural Gradient Information Geometry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Dipartimento di InformaticaUniversità degli Studi di MilanoMilanoItaly
  2. 2.de Castro StatisticsCollegio Carlo AlbertoMoncalieriItaly

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