A Conditional Multinomial Mixture Model for Superset Label Learning

@inproceedings{Liu2012ACM,
  title={A Conditional Multinomial Mixture Model for Superset Label Learning},
  author={Li-Ping Liu and Thomas G. Dietterich},
  booktitle={NIPS},
  year={2012}
}
In the superset label learning problem (SLL), each training instance provides a set of candidate labels of which one is the true label of the instance. As in ordinary regression, the candidate label set is a noisy version of the true label. In this work, we solve the problem by maximizing the likelihood of the candidate label sets of training instances. We propose a probabilistic model, the Logistic StickBreaking Conditional Multinomial Model (LSB-CMM), to do the job. The LSBCMM is derived from… CONTINUE READING
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References

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Learning from Partial Labels

Journal of Machine Learning Research • 2011
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