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Yulian Wu

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Open access 2025

Optimal Regret of Bandits under Differential Privacy

This work revisits the regret lower and upper bounds of ϵ -global DP bandits and proves a tighter regret lower bound involving a novel information-theoretic quantity characterising the hardness of ϵ -global DP in stochastic bandits.

Achraf Azize, Yulian Wu, Junya Honda et al. · 0 citations