Advanced deep architecture pruning using single-filter performance
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Pruning the parameters and structure of neural networks reduces computational complexity, energy consumption, and latency during inference. Recently, an underlying mechanism for successful deep learning (DL) was presented based on a method that quantitatively ... ...
