Spectral bandits achieve scalable regret in graph-structured recommendation by using an effective dimension to learn good policies from few node evaluations.
http://proceedings.mlr.press/v23/agrawal12/agrawal12.pdf Analysis of Thompson sampling for the multi-armed bandit problem
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Spectral bandits
Spectral bandits achieve scalable regret in graph-structured recommendation by using an effective dimension to learn good policies from few node evaluations.