Slimmable Neural Networks

ICLR, Volume abs/1812.08928, 2019.

Cited by: 521|Views112
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Abstract:

We present a simple and general method to train a single neural network executable at different widths (number of channels in a layer), permitting instant and adaptive accuracy-efficiency trade-offs at runtime. Instead of training individual networks with different width configurations, we train a shared network with switchable batch no...More

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