On the relation between multi-instance learning and semi-supervised learning

@inproceedings{Zhou2007OnTR,
  title={On the relation between multi-instance learning and semi-supervised learning},
  author={Zhi-Hua Zhou and Jun-Ming Xu},
  booktitle={ICML},
  year={2007}
}
Multi-instance learning and semi-supervised learning are different branches of machine learning. The former attempts to learn from a training set consists of labeled bags each containing many unlabeled instances; the latter tries to exploit abundant unlabeled instances when learning with a small number of labeled examples. In this paper, we establish a bridge between these two branches by showing that multi-instance learning can be viewed as a special case of semi-supervised learning. Based on… CONTINUE READING
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Learning single and multiple instance decision trees for computer security applications

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