Dynamic Programming Boosting for Discriminative Macro-Action Discovery

@inproceedings{Lefakis2014DynamicPB,
  title={Dynamic Programming Boosting for Discriminative Macro-Action Discovery},
  author={Leonidas Lefakis and François Fleuret},
  booktitle={ICML},
  year={2014}
}
We consider the problem of automatic macroaction discovery in imitation learning, which we cast as one of change-point detection. Unlike prior work in change-point detection, the present work leverages discriminative learning algorithms. Our main contribution is a novel supervised learning algorithm which extends the classical Boosting framework by combining it with dynamic programming. The resulting process alternatively improves the performance of individual strong predictors and the… CONTINUE READING

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