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

• Type: Journal
• Year: 2010
• Where: CORR
• Authors: Daniel Golovin, Andreas Krause, Debajyoti Ray
• Keywords: CORR 2010, Education, Fundamental Problem, Greedy Algorithm, Observations