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We present a new framework and method for solving Multiple Instance Learning (MIL) problems. As a variation on supervised learning, MIL addresses the problem of classifying a bag of instances. If at least one of the instances in a bag is positive the bag is labeled positive, otherwise it is negative. We use a divide and conquer strategy to identify true positive group of instances in the positive...
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