How to calculate the derivative of a matrix multiplication such as WHW
Calculating derivatives are key to training AI neural networks, being part of a backpropagation step.
The mathematical details of how to calculate the derivative of a matrix multiplication is not very clear. For example, if we have a Mx1 weight vector \(W\) and a MxM matrix \(H\), we can calculate the derivative of \(W^THW\) as follows:
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