Reliable Learning of Halfspaces under Gaussian Marginals

Neural Information Processing Systems 

We study the problem of PAC learning halfspaces in the reliable agnostic model of Kalai et al. (2012). The reliable PAC model captures learning scenarios where one type of error is costlier than the others.