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Seoul National University
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Achieve statistically efficient regret guarantees in nonstationary bandit problems with *constant* per-round computation and memory costs – a feat previously unattainable.
MNL bandit optimization, previously plagued by computational bottlenecks, now has a scalable solution with provable optimality guarantees.
