10 citations · 14 across the 10 of their papers we have counts for
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cs.AI2017
Context Attentive Bandits: Contextual Bandit with Restricted Context
Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi +1
We consider a novel formulation of the multi-armed bandit model, which we call the contextual bandit with restricted context, where only a limited number of features can be accesse…
stat.ML2017★ 3 cited
Reinforcement Learning Algorithm Selection
Romain Laroche, Raphael Feraud
This paper formalises the problem of online algorithm selection in the context of Reinforcement Learning. The setup is as follows: given an episodic task and a finite number of off…