Toward principled regularization of deep networks-From weight decay to feature contraction.

Maki, Atsuto · Sci Robot · 2019

basic_science · Level V

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Abstract

Training deep artificial neural networks for classification problems may benefit from exploiting intrinsic class similarities by way of network regularization that compensates for a drawback in the commonly used target error.