# Tight Generalization Bounds for Large-Margin Halfspaces

arXiv: https://arxiv.org/abs/2502.13692 · HTML: https://mlsanity.com/paper/2502.13692/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 23 references that are in the map.
- First posted on arXiv 19 Feb 2025.

## Builds on (most cited first, 3 of 3)

- [Near-Tight Margin-Based Generalization Bounds for Support Vector Machines](https://mlsanity.com/paper/2006.02175/) (2020)
- [Faster Algorithms for Structured Linear and Kernel Support Vector Machines](https://mlsanity.com/paper/2307.07735/) (2023)
- [Margins are Insufficient for Explaining Gradient Boosting](https://mlsanity.com/paper/2011.04998/) (2020)

## Built on by (most cited first, 1 of 1)

- [Tight Margin-Based Generalization Bounds for Voting Classifiers over Finite Hypothesis Sets](https://mlsanity.com/paper/2511.20407/) (2025)

## Abstract (arXiv)

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.