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We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypothesis sampled from a known prior distribution.
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Extensions of generalized binary search to group identification and exponential costs
Gowtham Bellala, Suresh Bhavnani, and Clayton Scott · 2010
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Sanjoy Dasgupta · 2006
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Adaptive submodularity: Theory and applications in active learning and stochastic optimization
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