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Most Correlated Arms Identification

Most Correlated Arms Identification

This video was recorded at 27th Annual Conference on Learning Theory (COLT), Barcelona 2014. We study the problem of finding the most mutually correlated arms among many arms. We show that adaptive arms sampling strategies can have significant advantages over the non-adaptive uniform sampling strategy. Our proposed algorithms rely on a novel correlation estimator. The use of this accurate estimator allows us to get improved results for a wide range of problem instances.


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