Tight Generalization Bounds for Large-Margin Halfspaces

Kasper Green Larsen, Natascha Schalburg

Advances in Neural Information Processing Systems 38 Main Conference (NeurIPS 2025) Main Conference Track DOI: 10.52202/085713-1531

We prove the first generalization bound for large-margin halfspaces that is asymptotically tight in the tradeoff between the margin, the fraction of training points with the given margin, the failure probability and the number of training points.