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How Far is Adam from Natural Gradient Descent?

Paka-Hegde, Vihaan
arXiv (All) · Papers
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68t07i-2-6
Adam is the standard optimizer in deep learning, yet its geometric relationship to natural gradient descent (NGD) contains unresolved questions. We study Adam's full update rule, including momentum, as a diagonal empirical Fisher approximation subject to diagonal truncation, empirical label substitu
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