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Curvature-corrected learning dynamics in deep neural networks

ICML 2020 · Optimization › Implicit bias and generalization · approach: Edge-of-stability dynamics

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Full natural gradient descent (q=1) instead of gradient descentdeep linear networks · teacher-student linear taskgeneralization errorHurt
Fractional curvature correction (sqrt-NGD, q=2)deep linear networks · teacher-student linear taskgeneralization errorHelped
Block-diagonal approximation of NGD (NGD-d) (ablation)NGD · deep linear networksparameter dynamics stabilityHurt
Block-diagonal approximation of sqrt-NGD (sqrt-NGD-d) (ablation)sqrt-NGD · deep linear networksparameter dynamics stabilityNo clear effect
Full curvature correction (NGD) instead of SGDdeep linear networks · singular mode dynamics analysisconvergence speed of input-output mapHelped
Full curvature correction (NGD) instead of SGDdeep linear networks · singular mode dynamics analysisparameter update stability at saddle pointsHurt
Fractional curvature correction (sqrt-NGD) instead of SGD/NGDdeep linear networks · singular mode dynamics analysisparameter update speed and map nonlinearityMixed
Block-diagonal approximation of NGD (NGD-d)NGD · deep linear networksconservation of weight-path shapeHurt
Block-diagonal approximation of sqrt-NGD (sqrt-NGD-d)sqrt-NGD · deep linear networksconservation of weight-path shapeNo clear effect
Curvature correction (any of NGD, sqrt-NGD) instead of SGDdeep linear networks · parameter pathweight balance across layersNo clear effect

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