An online stochastic gradient descent algorithm learns gamma-margin halfspaces under Massart noise with O~(1/(gamma^2 epsilon^2)) samples, nearly matching the information-computation tradeoff lower bound.
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A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise
An online stochastic gradient descent algorithm learns gamma-margin halfspaces under Massart noise with O~(1/(gamma^2 epsilon^2)) samples, nearly matching the information-computation tradeoff lower bound.