Margin Based Active Learning

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.

• Type: Conference
• Year: 2007
• Where: COLT
• Authors: Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang
• Keywords: COLT 2007, Linear Separators, Machine Learning, Small Noise Condition, Specific Noisy Setting