DC²B combines determinantal point processes with contextual combinatorial bandits for diversified interactive recommendation, using variational Bayesian Thompson sampling and providing regret analysis.
Contextual combinatorial bandit and its application on diversified online 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.