Asymptotic Bayes risk of semi-supervised learning with uncertain labeling

Victor Leger, Romain Couillet
3/26/2024
stat.MLcs.LG

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Abstract

This article considers a semi-supervised classification setting on a Gaussian mixture model, where the data is not labeled strictly as usual, but instead with uncertain labels. Our main aim is to compute the Bayes risk for this model. We compare the behavior of the Bayes risk and the best known algorithm for this model. This comparison eventually gives new insights over the algorithm.

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Cite this paper

@article{leger2024asymptotic,
  title  = {Asymptotic Bayes risk of semi-supervised learning with uncertain labeling},
  author = {Victor Leger and Romain Couillet},
  year   = {2024},
  eprint = {2403.17767},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.17767v2}
}

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