As organizations increasingly rely on algorithms to rank candidates for jobs, university spots, and financial services, a new ...
Abstract: The multi-armed bandit framework is a wellestablished learning paradigm that enables sequential decisionmaking under uncertainty. This framework has been widely applied in various domains, ...
Abstract: Accelerating the convergence of algorithms to Nash equilibrium is an important issue in game theory. In many games, particularly in complex game scenarios, the strategy space is typically ...
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