Papers with deep learning paradigm
Bayes-enhanced Lifelong Attention Networks for Sentiment Classification (2020.coling-main)
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| Challenge: | Existing deep learning paradigms focus on learning a model from training data of a single task and the learned model is also tested on the same task. |
| Approach: | They propose a Bayes-enhanced lifelong attention network to learn attention knowledge from a sequence of sentiment classification tasks and build lifelong ones. |
| Outcome: | The proposed model is able to learn attention knowledge from a set of sentiment classification tasks and build lifelong attentions. |