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Pooling and Drift in Delayed Bandits

Baghi, Melika
arXiv (All) · Papers
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machine-learning
A system often has to act long before it learns whether the act worked: a recommender sees a click in seconds and a purchase in days. With $K$ actions and a delay of $d$ rounds, the best rate known for this setting is $\widetilde{O}(\sqrt{(K+d)T})$ over $T$ rounds, so a longer menu is always more ex
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