Thus the training typically takes four or 16 times as much time as it would take for training a single unidirectional tagger, which looks somewhat expensive.
a naive implementation of this algorithm requires O(n 2 ) invocations of local classifiers, where n is the number of the words in the sentence, because we need to update the probabilities over the words at each iteration.