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About Active One Shot Learning 2016
This paper introduces a method for combining one-shot learning and reinforcement learning to perform active learning. A recurrent neural network is trained to make decisions about whether to predict labels or request true labels for image classification examples. The model can learn to trade off prediction accuracy versus label requests through its reward function. Preliminary results show the model can learn effectively from few label requests on an image classification task.
Detailed Information
Author: | ['Hola Patagonia'] |
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Publication Year: | 2017 |
Pages: | 8 |
Language: | English |
Format: | |
Price: | FREE |
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