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Apr 3, 2024 · Multi-armed bandits a simple but very powerful framework for algorithms that make decisions over time under uncertainty. An enormous body of work has ...
May 2, 2024 · An interesting class of MDPs are the multi-armed bandits (MAB) where given K Markov chains (each Markov chain corresponds to a bandit arm), the decision maker ...
Apr 23, 2024 · Although the design of clinical trials has been one of the principal practical problems motivating research on multi-armed bandits, bandit algorithms have never ...
Missing: proofs theorem.
Oct 28, 2023 · The Gittins policy was originally conceived to solve the Markovian multi-armed bandit ... The proof of Theorem 7.2 does not depend on the details of the Gittins ...
Aug 1, 2023 · The multi-armed bandit (MAB) problem [1] is a sequential decision-making model aimed at finding the right balance between exploration and exploitation, as faced ...
Missing: Four | Show results with:Four
Jul 19, 2023 · Note that when. P0 is the identity matrix, bandits are rested, i.e. the states of the arms that are not activated do not change. In such a case, a bandit is ...
Jul 13, 2023 · Differentially-private federated linear bandits. Advances in Neural Information Processing Systems, 33, 2020b. John C Gittins. Bandit processes and dynamic ...
Missing: Four | Show results with:Four
Jul 23, 2023 · This paper studies restless multi-armed bandit (RMAB) prob- lems with unknown arm transition dynamics but with known correlated arm features.
Missing: Four proofs
Feb 15, 2024 · The contributions of this work are three-fold. First, we propose a new, general contextual bandit algorithm that is computationally efficient and well motivated ...
Missing: Four proofs theorem.
May 30, 2024 · We study Pareto optimality in multi-objective multi-armed bandit by providing a formulation of adversarial multi-objective multi-armed bandit and defining ...
Missing: Four theorem.