My team has a custom optimization routine that we would have wanted to plug in as a replacement for the default LBFGS / OWLQN for use by some of the ml/mllib algorithms.
However it seems the choice of optimizer is hard-coded in every algorithm except LDA: and even in that one it is only a choice between the internally defined Online or batch version. Any suggestions on how we might be able to incorporate our own optimizer? Or do we need to roll all of our algorithms from top to bottom - basically side stepping ml/mllib? thanks stephen
