Bandit Learning in Matching Markets Robust to Adversarial Corruptions

Published in International Conference on Learning Representations (ICLR 2026), 2026

This work studies robust bandit learning in two-sided matching markets under adversarial corruptions.

Recommended citation: Zheshun Wu, Jinhang Zuo, Zenglin Xu, and Fang Kong. (2026). Bandit Learning in Matching Markets Robust to Adversarial Corruptions. In ICLR.