To filter prune, or to layer prune, that is the question

11 Jul 2020Sara ElkerdawyMostafa ElhoushiAbhineet SinghHong ZhangNilanjan Ray

Recent advances in pruning of neural networks have made it possible to remove a large number of filters or weights without any perceptible drop in accuracy. The number of parameters and that of FLOPs are usually the reported metrics to measure the quality of the pruned models... (read more)

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