Algorithms using Follow-The-Perturbed-Leader and Counting Asleep Times deliver regret bounds for full-information, bandit, and restricted-information feedback in online learning with stochastically available composite actions, improving guarantees for the sleeping bandit problem.
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Online combinatorial optimization with stochastic decision sets and adversarial losses
Algorithms using Follow-The-Perturbed-Leader and Counting Asleep Times deliver regret bounds for full-information, bandit, and restricted-information feedback in online learning with stochastically available composite actions, improving guarantees for the sleeping bandit problem.