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INRIA Lille - Nord Europe, SequeL team, 40 avenue Halley 59650, Villeneuve d’Ascq, France
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Learning user preferences for thousands of items can be achieved with just a handful of evaluations, thanks to a novel approach that leverages effective dimension in graph-based bandit problems.
Learning from noisy feedback doesn't have to be a guessing game: this new algorithm achieves near-optimal regret in online learning without needing to estimate the quality of the feedback.
