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We aim to investigate methods balancing exploitation with exploration in active learning to improve the performance of uncertainty sampling. Two exploration guided sampling methods are compared to uncertainty sampling on various real-life datasets from the 2010 Active Learning Challenge. Our initial experiments seems to indicate that combining exploration with uncertainty sampling improves performance on certain datasets but not all.
Hu, Rong et al.:Exploring the Frontier of Uncertainty Space. AISTATS 2010 Active Learning and Experimental Design Workshop Poster Highlight Papers