Papers by Steven Eliuk

1 papers
Continual Learning Long Short Term Memory (2020.findings-emnlp)

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Challenge: Existing approaches to prevent catastrophic forgetting in neural networks are based on the stability-plasticity dilemma, but only a limited size of old data is available.
Approach: They propose a Continual Learning Long Short Term Memory cell in Recurrent Neural Network (RNN) that considers the state of each individual task's output gates and the correlation of the states between tasks.
Outcome: The proposed method significantly improves on spoken language understanding tasks over state-of-the-art approaches.

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