Active Learning Is Planning: Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes
A fundamental issue in active learning of Gaussian processes is that of the exploration-exploitation trade-off. This paper presents a novel nonmyopic ε-Bayes-optimal active learning (ε-BAL) approach [4] that jointly optimizes the trade-off. In contrast, existing works have primarily developed greedy...
Автори: | Hoang, Trong Nghia, Low, Kian Hsiang, Jaillet, Patrick, Kankanhalli, Mohan |
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Інші автори: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Формат: | Стаття |
Мова: | en_US |
Опубліковано: |
Springer-Verlag
2015
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Онлайн доступ: | http://hdl.handle.net/1721.1/100448 https://orcid.org/0000-0002-8585-6566 |
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