Figure 1 (a) provides an illustration of the proposed architecture The model can be trained by maximizing the log likelihood of correct predictions in the training data: where ans(t) ∈ {1 .
without distinguishing domains, a feature vector takes the form x ∈ {0, 1} d for any domain k ∈ {1 .