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cs.LG2026
Practical Adversarial Attacks on Stochastic Bandits via Fake Data Injection
Qirun Zeng, Eric He, Richard Hoffmann +2
Adversarial attacks on stochastic bandits have traditionally relied on some unrealistic assumptions, such as per-round reward manipulation and unbounded perturbations, limiting the…
cs.LG2026
Graphon Mean-Field Subsampling for Cooperative Heterogeneous Multi-Agent Reinforcement Learning
Emile Anand, Richard Hoffmann, Sarah Liaw +1
Coordinating large populations of interacting agents is a central challenge in multi-agent reinforcement learning (MARL), where the size of the joint state-action space scales expo…