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Strategic stability under regularized learning in games
As such, in games where the marginalization of CCE coincides with the game's Nash equilibria (like
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Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards
Each client pulls an arm and communicates with neighbors based on the graph provided by the environment.
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Covariance adaptive best arm identification
The learner's goal is to identify the optimal arm
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Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards
Lijun Zhang is the corresponding author.
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