45 citations · 85 across the 2 of their papers we have counts for
2 papers
cs.IR2021★ 40 cited
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising
Yongchun Zhu, Yudan Liu, Ruobing Xie +6
In recommender systems and advertising platforms, marketers always want to deliver products, contents, or advertisements to potential audiences over media channels such as display,…
cs.IR2019★ 45 cited
Real-time Attention Based Look-alike Model for Recommender System
Yudan Liu, Kaikai Ge, Xu Zhang +1
Recently, deep learning models play more and more important roles in contents recommender systems. However, although the performance of recommendations is greatly improved, the "Ma…