# Robust SVM Optimization in Banach spaces

arXiv: https://arxiv.org/abs/2202.08567 · HTML: https://mlsanity.com/paper/2202.08567/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 22 references that are in the map.
- First posted on arXiv 17 Feb 2022.

## Builds on (most cited first, 1 of 1)

- [Banach Wasserstein GAN](https://mlsanity.com/paper/1806.06621/) (2018)

## Abstract (arXiv)

We address the issue of binary classification in Banach spaces in presence of uncertainty. We show that a number of results from classical support vector machines theory can be appropriately generalised to their robust counterpart in Banach spaces. These include the Representer Theorem, strong duality for the associated Optimization problem as well as their geometric interpretation. Furthermore, we propose a game theoretic interpretation by expressing a Nash equilibrium problem formulation for the more general problem of finding the closest points in two closed convex sets when the underlying space is reflexive and smooth.