A single parameter k in a binary-gate network training method interpolates between dropout, standard training, and sparse or expanded architectures.
Wide residual networks,
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Neural Plasticity Networks
A single parameter k in a binary-gate network training method interpolates between dropout, standard training, and sparse or expanded architectures.