Hi Nick and others,
I would like to use alternating minimisation of parameters as in this PCA example or this stackoverflow discussion.
There people suggest specifying the list of variable to minimise via
train_W = optimizer.minimize(loss, var_list=[W]). I cannot find where
greta::opt executes this operation, though. I suppose one can easily add the extra
sess.run(train_W) steps in
object$run_minimiser as several calls to
The user interface for specifying alternating minimisation could be adding list argument to
opt() where each element tells which greta variables should be updated during each step of alternating minimisation.
Would it be straightforward to implement something like this and where might I add equivalent operation
train_W = optimizer.minimize(loss, var_list=[W]) in