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On Differentially Private Federated Linear Contextual Bandits. (arXiv:2302.13945v2 [cs.LG] UPDATED)
cs.CR updates on arXiv.org arxiv.org
We consider cross-silo federated linear contextual bandit (LCB) problem under
differential privacy, where multiple silos (agents) interact with the local
users and communicate via a central server to realize collaboration while
without sacrificing each user's privacy. We identify three issues in the
state-of-the-art: (i) failure of claimed privacy protection and (ii) incorrect
regret bound due to noise miscalculation and (iii) ungrounded communication
cost. To resolve these issues, we take a two-step principled approach. First,
we design an algorithmic framework consisting …
art bandit collaboration differential privacy identify local privacy private problem protection server silos state under