430 citations · 1.1k across the 13 of their papers we have counts for
13 papers
Sequential Recommendation with User Evolving Preference Decomposition
Weiqi Shao, Xu Chen, Long Xia +2
Modeling user sequential behaviors has recently attracted increasing attention in the recommendation domain. Existing methods mostly assume coherent preference in the same sequence…
User behavior understanding in real world settings
Weiqi Shao, Xu Chen, Jiashu Zhao +2
How to extract meaningful information in user historical behavior plays a crucial role in recommendation. User behavior sequence often contains multiple conceptually distinct items…
Gumble Softmax For User Behavior Modeling
Weiqi Shao, Xu Chen, Jiashu Zhao +2
Recently, sequential recommendation systems are important in solving the information overload in many online services. Current methods in sequential recommendation focus on learnin…
Data-Efficient Reinforcement Learning for Malaria Control
Lixin Zou, Long Xia, Linfang Hou +2
Sequential decision-making under cost-sensitive tasks is prohibitively daunting, especially for the problem that has a significant impact on people's daily lives, such as malaria c…
Neural Interactive Collaborative Filtering
Lixin Zou, Long Xia, Yulong Gu +4
In this paper, we study collaborative filtering in an interactive setting, in which the recommender agents iterate between making recommendations and updating the user profile base…
Off-policy Learning for Multiple Loggers
Li He, Long Xia, Wei Zeng +3
It is well known that the historical logs are used for evaluating and learning policies in interactive systems, e.g. recommendation, search, and online advertising. Since direct on…