DC²B combines determinantal point processes with contextual combinatorial bandits for diversified interactive recommendation, using variational Bayesian Thompson sampling and providing regret analysis.
A contextual-bandit approach to personalized news article recommendation
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Bandit Learning for Diversified Interactive Recommendation
DC²B combines determinantal point processes with contextual combinatorial bandits for diversified interactive recommendation, using variational Bayesian Thompson sampling and providing regret analysis.