Near-Optimal Bayesian Active Learning with Noisy Observations

Daniel Golovin, Andreas Krause, Debajyoti Ray

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 hypoth…