  This paper describes the Georgia Tech team's approach to the CoNLL-2016
supplementary evaluation on discourse relation sense classification. We use
long short-term memories (LSTM) to induce distributed representations of each
argument, and then combine these representations with surface features in a
neural network. The architecture of the neural network is determined by
Bayesian hyperparameter search.
