Normalized stochastic subgradient descent iterates converge, after perfect classification, to critical points of the normalized margin for homogeneous neural networks.
Stochastic approximations and differential inclusions
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The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks
Normalized stochastic subgradient descent iterates converge, after perfect classification, to critical points of the normalized margin for homogeneous neural networks.