We propose an augmentation of MG-CNN, Multi-Group Norm Constraint CNN (MGNC-CNN), which differs in its regularization strategy.
in this variant we impose grouped regularization constraints, independently regularizing subcomponents o l derived from the respective embeddings, i.e., we impose separate max norm constraints λ l for each o l (where l again indexes embedding sets); these λ l hyper-parameters are to be tuned on a validation set.