On the Robustness of Active Learning

18 Jun 2020Lukas HahnLutz Roese-KoernerPeet CremerUrs ZimmermannOri MaozAnton Kummert

Active Learning is concerned with the question of how to identify the most useful samples for a Machine Learning algorithm to be trained with. When applied correctly, it can be a very powerful tool to counteract the immense data requirements of Artificial Neural Networks... (read more)

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