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CORR
2010
Springer

Near-Optimal Bayesian Active Learning with Noisy Observations

9 years 8 months ago
Near-Optimal Bayesian Active Learning with Noisy Observations
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. In the case of noise
Daniel Golovin, Andreas Krause, Debajyoti Ray
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2010
Where CORR
Authors Daniel Golovin, Andreas Krause, Debajyoti Ray
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