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 that jointly and naturally optimizes the trade-off. In contrast, existing works have primarily develo...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Association for Computing Machinery (ACM),
2015-12-19T02:35:30Z.
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| Subjects: | |
| Online Access: | Get fulltext |