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Soft weight-sharing for DNN

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Approach

where p(w) is the prior over w and p(D|w) is the model likelihood.


After re-training we set each weight to the mean of the component that takes most responsibility for it.

Experiment

References:
SOFT WEIGHT-SHARING FOR NEURAL NETWORK COMPRESSION, Karen Ullrich, 2017, ICLR

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