Demystifying ResNet

3 Nov 2016 Sihan Li Jiantao Jiao Yanjun Han Tsachy Weissman

The Residual Network (ResNet), proposed in He et al. (2015), utilized shortcut connections to significantly reduce the difficulty of training, which resulted in great performance boosts in terms of both training and generalization error. It was empirically observed in He et al. (2015) that stacking more layers of residual blocks with shortcut 2 results in smaller training error, while it is not true for shortcut of length 1 or 3... (read more)

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