Ichiro Hashimoto

Ichiro Hashimoto

PhD student, Statistics

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Universality of Benign Overfitting in Binary Linear Classification

Published in Arxiv, 2025

This work provides a comprehensive study of benign overfitting for linear maximum margin classifiers, discovers a phase transition for the noisy model which was previously unknown and provides some geometric intuition behind it. We further considerably relax the required covariate assumptions in both, the noisy and noiseless case. Our results demonstrate that benign overfitting of maximum margin classifiers holds in a much wider range of scenarios than was previously known.

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