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About this paper
Aniruddhan Ganesaraman, VIdyadhar Kulkarni
The authors learn block-replacement schedules from incomplete records, replacing failures immediately and the group at intervals. Their bandit methods use longer-interval failure histories to inform shorter intervals, while a Kaplan–Meier method estimates lifetimes from censored data. In simulations in two models, Kaplan–Meier shows near-zero regret, and correlated bandits outperform independent ones; these findings are not general guarantees.
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