Comparing the Bayes and Typicalness Frameworks

@inproceedings{Melluish2001ComparingTB,
  title={Comparing the Bayes and Typicalness Frameworks},
  author={Thomas Melluish and Craig Saunders and Ilia Nouretdinov and Vladimir Vovk},
  booktitle={ECML},
  year={2001}
}
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these confidence values have no theoretical base – even though the algorithms’ predictive performance may be good. There also exist many successful learning algorithms which only depend on the iid assumption. Often however they produce no confidence values for their predictions. Bayesian frameworks are often applied to… CONTINUE READING
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