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cs.GT2024
Decentralized and Uncoordinated Learning of Stable Matchings: A Game-Theoretic Approach
S. Rasoul Etesami, R. Srikant
We consider the problem of learning stable matchings with unknown preferences in a decentralized and uncoordinated manner, where "decentralized" means that players make decisions i…
math.PR2024
Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
R. Srikant
We prove a non-asymptotic central limit theorem for vector-valued martingale differences using Stein's method, and use Poisson's equation to extend the result to functions of Marko…
cs.LG2024
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Cascading bandits have gained popularity in recent years due to their applicability to recommendation systems and online advertising. In the cascading bandit model, at each timeste…