Search Results for author: Jinhang Zuo

Found 6 papers, 1 papers with code

Hierarchical Conversational Preference Elicitation with Bandit Feedback

no code implementations6 Sep 2022 Jinhang Zuo, Songwen Hu, Tong Yu, Shuai Li, Handong Zhao, Carlee Joe-Wong

To achieve this, the recommender system conducts conversations with users, asking their preferences for different items or item categories.

Recommendation Systems

Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms

no code implementations31 Aug 2022 Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C. S. Lui, Wei Chen

Under this new condition, we propose a BCUCB-T algorithm with variance-aware confidence intervals and conduct regret analysis which reduces the $O(K)$ factor to $O(\log K)$ or $O(\log^2 K)$ in the regret bound, significantly improving the regret bounds for the above applications.

Combinatorial Multi-armed Bandits for Resource Allocation

1 code implementation10 May 2021 Jinhang Zuo, Carlee Joe-Wong

In doing so, the decision maker should learn the value of the resources allocated for each user from feedback on each user's received reward.

Multi-Armed Bandits

Online Competitive Influence Maximization

no code implementations24 Jun 2020 Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C. S. Lui, Wei Chen

In this paper, we introduce a new Online Competitive Influence Maximization (OCIM) problem, where two competing items (e. g., products, news stories) propagate in the same network and influence probabilities on edges are unknown.

Observe Before Play: Multi-armed Bandit with Pre-observations

no code implementations21 Nov 2019 Jinhang Zuo, Xiaoxi Zhang, Carlee Joe-Wong

We consider the stochastic multi-armed bandit (MAB) problem in a setting where a player can pay to pre-observe arm rewards before playing an arm in each round.

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