Jesse H. Krijthe

The Pessimistic Limits of Margin-based Losses in Semi-supervised Learning.

2016 · arXiv (Cornell University)

Consider a classification problem where we have both labeled and unlabeled data available. We show that for linear classifiers defined by convex margin-based surrogate losses that are decreasing, it is impossible to construct any semi-supervised …