Learning Longer-term Dependencies in RNNs with Auxiliary Losses
ICML, pp. 4965-4974, 2018.
Despite recent advances in training recurrent neural networks (RNNs), capturing long-term dependencies in sequences remains a fundamental challenge. Most approaches use backpropagation through time (BPTT), which is difficult to scale to very long sequences. This paper proposes a simple method that improves the ability to capture long term...More