Hey!

I was working on an extreme multi-label classification task of which one of the modules is to create a function that would take a single document vector and label vector (both of 300 dimensions but created separately and so from different vector spaces) and would produce a new latent vector which would be binarily classifiable. My current naive approach is to simply concatenate the two vectors.

Could you please suggest some techniques, features or a general direction or topic to study. Any idea would be greatly appreciated as I have been at a total loss on how to proceed further.

Thank you!