Two-layer linear denoising autoencoders show a bias-variance trade-off in bottleneck width, and skip connections reduce variance near the interpolation peak.
A Random Matrix Perspective on Mixtures of Nonlinearities in High Dimensions
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Impact of Bottleneck Layers and Skip Connections on the Generalization of Linear Denoising Autoencoders
Two-layer linear denoising autoencoders show a bias-variance trade-off in bottleneck width, and skip connections reduce variance near the interpolation peak.