69 citations · 173 across the 11 of their papers we have counts for
4 papers · 1 filter
RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender System
Kai Wang, Zhene Zou, Minghao Zhao +7
Reinforcement learning based recommender systems (RL-based RS) aim at learning a good policy from a batch of collected data, by casting recommendations to multi-step decision-makin…
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition
Junkun Yuan, Anpeng Wu, Kun Kuang +4
Instrumental variables (IVs), sources of treatment randomization that are conditionally independent of the outcome, play an important role in causal inference with unobserved confo…
Personalized Bundle Recommendation in Online Games
Qilin Deng, Kai Wang, Minghao Zhao +5
In business domains, \textit{bundling} is one of the most important marketing strategies to conduct product promotions, which is commonly used in online e-commerce and offline reta…
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation
Kai Wang, Zhene Zou, Qilin Deng +5
In recent years, there are great interests as well as challenges in applying reinforcement learning (RL) to recommendation systems (RS). In this paper, we summarize three key pract…