A Framework for Multiple-Instance Learning

  title={A Framework for Multiple-Instance Learning},
  author={Oded Maron and Tom{\'a}s Lozano-P{\'e}rez},
Multiple-instance learning is a variation on supervised learning, where the task is to learn a concept given positive and negative bags of instances. Each bag may contain many instances, but a bag is labeled positive even if only one of the instances in it falls within the concept. A bag is labeled negative only if all the instances in it are negative. We describe a new general framework, called Diverse Density, for solving multiple-instance learning problems. We apply this framework to learn a… CONTINUE READING
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