Introduces transductive linear bandits, gives instance-dependent lower bounds, and presents an algorithm matching them up to logarithmic factors, including the first non-asymptotic near-optimal method for standard linear bandits.
Action elimination and stopping conditions for the multi-armed bandit and reinforcement learning problems.Journal of machine learning research, 7(Jun):1079–1105
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Sequential Experimental Design for Transductive Linear Bandits
Introduces transductive linear bandits, gives instance-dependent lower bounds, and presents an algorithm matching them up to logarithmic factors, including the first non-asymptotic near-optimal method for standard linear bandits.