Uncertainty-aware Self-training for Few-shot Text Classification
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..., 2019) and few-shot text classification (Mukherjee and Awadallah, 2020; Wang et al., 2020) show the effectiveness of self-training methods in exploiting task-specific unlabeled data with stochastic regularization techniques like dropouts and data augmentation....
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..., 2020), few-shot text classification (Mukherjee and Awadallah, 2020; Wang et al., 2020), and neural machine translation (Zhang and Zong, 2016; He et al....
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"Uncertainty-aware Self-training for..." refers methods in this paper
...We use Adam [Kingma and Ba, 2015] as the optimizer with early stopping and use the best model found so far from the validation loss for all the models....
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"Uncertainty-aware Self-training for..." refers methods in this paper
...SST-2 [Socher et al., 2013], IMDB [Maas et al., 2011] and Elec [McAuley and Leskovec, 2013] are used for sentiment classification for movie reviews and Amazon electronics product reviews respectively....
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"Uncertainty-aware Self-training for..." refers background in this paper
...One of the earlier works in neural networks leveraging easiness of the samples for learning is given by curriculum learning [Bengio et al., 2009]....
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...Sample selection leveraging teacher confidence has been studied in curriculum learning [Bengio et al., 2009] and self-paced learning [Kumar et al., 2010] frameworks....
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...Sample selection leveraging teacher confidence has been studied in curriculum learning [Bengio et al., 2009] and self-paced learning [Kumar et al....
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