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passive voice by additional than 79% prime-1 accuracy drops by only 1% when Resnet-50 is pruned by 89%. Whilst the authors do not clarify why the initialization is significant, the presumption is that the mixture of initial weights and connectivity are nicely-suited for the job at hand. We posit that this good results is due to the fact that, in the XOR case when all input values are either or 1, the item of input and output weight magnitudes need to mimic the activation of the unit . A lot of of the exact same behaviors we observed in image-recognition networks also surface when understanding XOR with exceedingly easy networks. Convergence occasions and accuracy for Query three (pruning convolutions vs. completely-connected).
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