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Is Active Learning Always Beneficial? (Student Abstract)
Proceedings of the AAAI Conference on Artificial Intelligence2021Vol. 35(18), pp. 15819–15820
Abstract
This study highlights the limitations of automated curriculum learning, which may not be a viable strategy for tasks in which the benefits of the chosen curriculum are not apparent until much later. Using a simple convolutional network and a two-task training regime, we show that in some cases a network is not able to derive an optimal learning strategy using only the data available during a single training run.
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