Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets Kai Han 1,2 Yunhe Wang

Neural Information Processing Systems 

The giant formula for simultaneously enlarging the resolution, depth and width provides us a Rubik's cube for neural networks. So that we can find networks with high efficiency and excellent performance by twisting the three dimensions.

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