(2017) further compare different methods for training a multi-domain system.
they compare concatenation that simply concatenates the multi-domain corpora, staking that iteratively trains the NMT system on each domain corpus, selection that selects a set of out-of-domain data which is close to the in-domain data, and ensemble that ensembles the multiple NMT models trained independently.