A sequence-to-sequence learning model learns the distribution of regular expressions R given an input NL sentence S: By default, the sequence-to-sequence learning model uses maximum likelihood estimation (MLE) for training, i.e., maximizing the likelihood of mapping the input sequence to the output sequence for each pair in the training set.
the optimal parameters θ * are obtained as follow: Gradient descent is used to search out optimal parameters θ * .