# Learning Halfspaces with Massart Noise Under Structured Distributions

@article{Diakonikolas2020LearningHW, title={Learning Halfspaces with Massart Noise Under Structured Distributions}, author={Ilias Diakonikolas and Vasilis Kontonis and Christos Tzamos and Nikos Zarifis}, journal={ArXiv}, year={2020}, volume={abs/2002.05632} }

We study the problem of learning halfspaces with Massart noise in the distribution-specific PAC model. We give the first computationally efficient algorithm for this problem with respect to a broad family of distributions, including log-concave distributions. This resolves an open question posed in a number of prior works. Our approach is extremely simple: We identify a smooth {\em non-convex} surrogate loss with the property that any approximate stationary point of this loss defines a… CONTINUE READING

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