Shrinking the maxout layer remains more of a challenge (rows (g) and (h)), but the number of parameters in this layer is small.
shrinking all layers except the maxout layer leads to almost the same number of parameters (factor 1.05 in row (f)) as the original NMT network (a), and thus to a similar storage size, memory consumption, and decoding speed, but with a 1.8 BLEU gain.