Energetic Natural Gradient Descent

Abstract

We propose a new class of algorithms for minimizing or maximizing functions of parametric probabilistic models. These new algorithms are natural gradient algorithms that leverage more information than prior methods by using a new metric tensor in place of the commonly used Fisher information matrix. This new metric tensor is derived by computing directions… (More)

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020406020162017
Citations per Year

Citation Velocity: 9

Averaging 9 citations per year over the last 2 years.

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Cite this paper

@inproceedings{Thomas2016EnergeticNG, title={Energetic Natural Gradient Descent}, author={Philip S. Thomas and Bruno Castro da Silva and Christoph Dann and Emma Brunskill}, booktitle={ICML}, year={2016} }