Papers by Neil O’Hare
Effective Few-Shot Classification with Transfer Learning (2020.coling-main)
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| Challenge: | Recent work on few-shot learning addresses the problem of learning based on a small amount of training data. |
| Approach: | They adapt the Amazon Review Sentiment Classification (ARSC) text dataset for few-shot learning . they train a single binary classifier to learn all few- shot classes jointly . |
| Outcome: | The proposed approach outperforms most published results on the ARSC text dataset . the results suggest that the classes in the AR SC few-shot task are very similar to each other . |