Negative Results for Active Learning with Convex Losses
Steve Hanneke, Lin Forrest Yang · International Conference on Artificial Intelligence and Statistics · 2010
We study the problem of active learning with convex loss functions. We prove that even under bounded noise constraints, the minimax rates for proper active learning are often no better than passive learning.