Hello,
Given a neural network model called  S() and dataset  X^{5000 \times 18} where 5000 is the number of samples and 18 its dimensionality.
At the first layer (linear)  of S() l would like to learn   X= X * A* theta  such that  A^{18 \times 18}
With A randomly initialized and theta the parameters of the model
And A=B * B^{T} with B^{18*60} randomly initiliazed.
I would like to learn A which is the same for all the samples (A as the parameter of model) .
Any trick to do that ?
Thank you