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Found 2 papers, 1 papers with code
Riemannian Natural Gradient Methods
Moreover, we show that if the loss function satisfies certain convexity and smoothness conditions and the input-output map satisfies a Riemannian Jacobian stability condition, then our proposed method enjoys a local linear -- or, under the Lipschitz continuity of the Riemannian Jacobian of the input-output map, even quadratic -- rate of convergence.
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning
In this paper, a novel second-order method called NG+ is proposed.
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