• Corpus ID: 7565247

Learning Theory for Distribution Regression

@article{Szab2014LearningTF,
  title={Learning Theory for Distribution Regression},
  author={Zolt{\'a}n Szab{\'o} and Bharath K. Sriperumbudur and Barnab{\'a}s P{\'o}czos and Arthur Gretton},
  journal={J. Mach. Learn. Res.},
  year={2014},
  volume={17},
  pages={152:1-152:40}
}
We focus on the distribution regression problem: regressing to vector-valued outputs from probability measures. Many important machine learning and statistical tasks fit into this framework, including multi-instance learning and point estimation problems without analytical solution (such as hyperparameter or entropy estimation). Despite the large number of available heuristics in the literature, the inherent two-stage sampled nature of the problem makes the theoretical analysis quite… 

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