DC²B combines determinantal point processes with contextual combinatorial bandits for diversified interactive recommendation, using variational Bayesian Thompson sampling and providing regret analysis.
Fast greedy map inference for determinantal point process to improve recommendation diversity
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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.