Jong-Min Park

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An adaptive on-line learning method is presented to facilitate pattern classification using active sampling to identify the optimal decision boundary for a stochastic oracle with a minimum number of training samples. The strategy of sampling at the current estimate of the decision boundary is shown to be optimal compared to random sampling in the sense that(More)
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