Boosting with Online Binary Learners for the Multiclass Bandit Problem

@inproceedings{Chen2014BoostingWO,
  title={Boosting with Online Binary Learners for the Multiclass Bandit Problem},
  author={Shang-Tse Chen and Hsuan-Tien Lin and Chi-Jen Lu},
  booktitle={ICML},
  year={2014}
}
We consider the problem of online multiclass prediction in the bandit setting. Compared with the full-information setting, in which the learner can receive the true label as feedback after making each prediction, the bandit setting assumes that the learner can only know the correctness of the predicted label. Because the bandit setting is more restricted, it is difficult to design good bandit learners and currently there are not many bandit learners. In this paper, we propose an approach that… CONTINUE READING

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