BA-UCB identifies candidate backdoor sets from sequential data to estimate causal effects and construct UCBs for intervention selection in unknown-graph causal bandits, with regret bounds and extension to latent confounders.
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Defines private private signals and characterizes the optimal ones that maximize state informativeness subject to no cross-signal information leakage.
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Causal Bandit Over Unknown Graphs: Upper Confidence Bounds With Backdoor Adjustment
BA-UCB identifies candidate backdoor sets from sequential data to estimate causal effects and construct UCBs for intervention selection in unknown-graph causal bandits, with regret bounds and extension to latent confounders.
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Private Private Information
Defines private private signals and characterizes the optimal ones that maximize state informativeness subject to no cross-signal information leakage.