Optimal Rates for Learning with Monotone Adversaries
By Anay Mehrotra · Paper · stat.ML
A monotone adversary observes an i.i.d. labeled sample and appends a finite number of further examples of its choice, every one of them labeled correctly by the target hypothesis. The learner sees a uniform shuffle of the combined sample and is scored on the original distribution