The power of localization for efficiently learning linear separators with noise

@article{Awasthi2014ThePO,
  title={The power of localization for efficiently learning linear separators with noise},
  author={Pranjal Awasthi and Maria-Florina Balcan and Philip M. Long},
  journal={J. ACM},
  year={2014},
  volume={63},
  pages={50:1-50:27}
}
We introduce a new approach for designing computationally efficient learning algorithms that are tolerant to noise, and we demonstrate its effectiveness by designing algorithms with improved noise tolerance guarantees for learning linear separators. We consider both the malicious noise model of Valiant [1985] and Kearns and Li [1988] and the adversarial label noise model of Kearns, Schapire, and Sellie [1994]. For malicious noise, where the adversary can corrupt both the label and the features… CONTINUE READING
Highly Cited
This paper has 75 citations. REVIEW CITATIONS

2 Figures & Tables

Topics

Statistics

02040201320142015201620172018
Citations per Year

75 Citations

Semantic Scholar estimates that this publication has 75 citations based on the available data.

See our FAQ for additional information.