5 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
Quantum Multi-Armed Bandits and Linear Bandits: Lower Bounds and Algorithms
Maoli Liu, Zhuohua Li, John C. S. Lui
We study quantum multi-armed bandits (QMAB) and quantum linear bandits (QLB), where the learner queries each arm or action through a quantum reward oracle or its inverse. Prior wor…
Leveraging the Power of Conversations: Optimal Key Term Selection in Conversational Contextual Bandits
Maoli Liu, Zhuohua Li, Xiangxiang Dai +1
Conversational recommender systems proactively query users with relevant "key terms" and leverage the feedback to elicit users' preferences for personalized recommendations. Conver…
Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
Zhuohua Li, Maoli Liu, Xiangxiang Dai +1
The contextual multi-armed bandit (MAB) problem is crucial in sequential decision-making. A line of research, known as online clustering of bandits, extends contextual MAB by group…
FedConPE: Efficient Federated Conversational Bandits with Heterogeneous Clients
Zhuohua Li, Maoli Liu, John C. S. Lui
Conversational recommender systems have emerged as a potent solution for efficiently eliciting user preferences. These systems interactively present queries associated with "key te…