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Exploding and vanishing gradients in deep neural networks: the effect of residual connections
One-line summary
An AI research paper on Exploding and vanishing gradients in deep neural networks: the effect of residual connections.
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Chinese explanation / 中文解读
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Original abstract
The well known phenomenon of exploding and vanishing gradients in deep neural networks is analyzed using multiplicative ergodic theory. The effect of adding a residual connection is explained in this context. Specifically, a characterization of Liapunov exponents due to Furstenberg and Kifer is exploited in order to make a precise statement about the Liapunov spectrum and the effect of residual connections on it.
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