Abstract
Singular Value Decomposition (SVD) provides a linear analogy to neural networks and can serve as an initial guess for network parameters, improving optimization.
AI-generated summary
Singular Value Decomposition (SVD) constitutes a bridge between the linear algebra concepts and multi-layer neural networks---it is their linear analogy. Besides of this insight, it can be used as a good initial guess for the network parameters, leading to substantially better optimization results.
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