Learning Inference Networks for Structured Prediction Energy Networks
Table 1: Test F1 when comparing methods on multi-label classification datasets.
['[EMPTY]', 'Bibtex', 'Bookmarks', 'Delicious', 'avg.']
Comparison to Prior Work. The MLP and “SPEN (BM16)” We obtained the “SPEN (E2E)” This method constructs a recurrent neural network that performs gradient-based minimization of the energy with respect to y. They noted in their software release that, while this method is more stable, it is prone to overfitting and actually performs worse than the original SPEN. We indeed find this to be the case, as SPEN (E2E) underperforms SPEN (BM16) on all three datasets.