Pruning Depthwise Separable Convolutions for Extra Efficiency Gain of Lightweight Models

ICLR 2020 Anonymous

Deep convolutional neural networks are good at accuracy while bad at efficiency. To improve the inference speed, two kinds of directions are developed, lightweight model designing and network weight pruning... (read more)

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