Session details: Active learning
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- Session details: Active learning
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Transfer active learning
CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge managementActive learning traditionally assumes that labeled and unlabeled samples are subject to the same distributions and the goal of an active learner is to label the most informative unlabeled samples. In reality, situations may exist that we may not have ...
Session details: Oral Session 3: Multimedia Applications (Oral presentations)
ICMR '17: Proceedings of the 2017 ACM on International Conference on Multimedia RetrievalA probabilistic model of active learning with multiple noisy oracles
In this paper, we focus on obtaining an accurate classifier in active learning, when there are multiple noisy oracles with different and unknown levels of expertise to provide labels for selected instances. We propose a probabilistic model of active ...
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- General Chairs:
- Ingrid Russell,
- Susan Haller,
- Program Chairs:
- J. D. Dougherty,
- Susan Rodger
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Association for Computing Machinery
New York, NY, United States
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