Learning Longer-term Dependencies in RNNs with Auxiliary Losses

    Trieu H. Trinh
    Trieu H. Trinh

    ICML, pp. 4965-4974, 2018.

    Cited by: 43|Bibtex|Views52|Links
    EI

    Abstract:

    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

    Code:

    Data:

    Your rating :
    0

     

    Tags
    Comments