The work establishes the first DP regret bound of order O(K^{3/5}) for model-free online RL under general function approximation and the first coverability-based regret bound for batched non-private RL.
Differentially private empirical risk minimization
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Towards Differentially Private Reinforcement Learning with General Function Approximation
The work establishes the first DP regret bound of order O(K^{3/5}) for model-free online RL under general function approximation and the first coverability-based regret bound for batched non-private RL.