Corpus ID: 195345447

Distribution-Independent PAC Learning of Halfspaces with Massart Noise

@inproceedings{Diakonikolas2019DistributionIndependentPL,
  title={Distribution-Independent PAC Learning of Halfspaces with Massart Noise},
  author={Ilias Diakonikolas and Themis Gouleakis and Christos Tzamos},
  booktitle={NeurIPS},
  year={2019}
}

• Ilias Diakonikolas, Themis Gouleakis, Christos Tzamos
• Published in NeurIPS 2019
• Computer Science, Mathematics

We study the problem of {\em distribution-independent} PAC learning of halfspaces in the presence of Massart noise. Specifically, we are given a set of labeled examples $(\mathbf{x}, y)$ drawn from a distribution $\mathcal{D}$ on $\mathbb{R}^{d+1}$ such that the marginal distribution on the unlabeled points $\mathbf{x}$ is arbitrary and the labels $y$ are generated by an unknown halfspace corrupted with Massart noise at noise rate $\eta<1/2$. The goal is to find a hypothesis $h$ that minimizes… Expand

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