High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits
Abstract
We develop a novel latent-bandit algorithm for tackling the cold-start problem for new users joining a recommender system. This new algorithm significantly outperforms the state of the art, simultaneously achieving both higher accuracy and lower regret.
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