Note that since edit decisions are based in part on (arbitrary) features of the target sequence, and since generation involves construction of the target sequence, it is not uncommon for a greedy generator to make edit decisions which are locally optimal, but which result several edits later in a partially constructed sequence in which no good edits are available.
1: Given a set S of source sequences 2: V ← [], an empty list 3: α ← 0, a weight vector 4: for some number of iterations do for s in S do 6: Pick t, t , t having higher affinity with s 7: end if Append α to V 13: end for 14: end for 15: Return the mean α from V Table 1: The training algorithm.