187 citations · 521 across the 19 of their papers we have counts for
4 papers · 1 filter
Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation
Xiaocong Chen, Siyu Wang, Lina Yao +2
Deep reinforcement learning (DRL) has been proven its efficiency in capturing users' dynamic interests in recent literature. However, training a DRL agent is challenging, because o…
Contrastive Counterfactual Learning for Causality-aware Interpretable Recommender Systems
Guanglin Zhou, Chengkai Huang, Xiaocong Chen +4
The field of generating recommendations within the framework of causal inference has seen a recent surge, with recommendations being likened to treatments. This approach enhances i…
Plug-and-Play Model-Agnostic Counterfactual Policy Synthesis for Deep Reinforcement Learning based Recommendation
Siyu Wang, Xiaocong Chen, Lina Yao +2
Recent advances in recommender systems have proved the potential of Reinforcement Learning (RL) to handle the dynamic evolution processes between users and recommender systems. How…
Model-agnostic Counterfactual Synthesis Policy for Interactive Recommendation
Siyu Wang, Xiaocong Chen, Lina Yao
Interactive recommendation is able to learn from the interactive processes between users and systems to confront the dynamic interests of users. Recent advances have convinced that…