Web: http://arxiv.org/abs/2205.05662

May 12, 2022, 1:11 a.m. | Wuyang Chen, Wei Huang, Xinyu Gong, Boris Hanin, Zhangyang Wang

cs.LG updates on arXiv.org arxiv.org

Advanced deep neural networks (DNNs), designed by either human or AutoML
algorithms, are growing increasingly complex. Diverse operations are connected
by complicated connectivity patterns, e.g., various types of skip connections.
Those topological compositions are empirically effective and observed to smooth
the loss landscape and facilitate the gradient flow in general. However, it
remains elusive to derive any principled understanding of their effects on the
DNN capacity or trainability, and to understand why or in which aspect one
specific connectivity pattern …

analysis architecture arxiv connectivity convergence deep

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