Margin Based Active Learning

Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang

Abstract: We present a framework for margin based active learning of linear separators. We instantiate it for a few important cases, some of which have been previously considered in the literature. We analyze the effectiveness of our framework both in the realizable case and in a specific noisy setting related to the Tsybakov small noise condition.