We introduce the MAN architecture in §2 and prove in §3 that it directly minimizes the (generalized) f-divergence among multiple distributions so that they are indistinguishable upon successful training.
for MDTC, MAN is used to overcome the aforementioned limitation in prior art where domain-specific features may sneak into the shared model.