10 citations · 10 across the 1 of their papers we have counts for
3 papers
cs.IR2021
One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction
Xiang-Rong Sheng, Liqin Zhao, Guorui Zhou +8
Traditional industrial recommenders are usually trained on a single business domain and then serve for this domain. However, in large commercial platforms, it is often the case tha…
cs.IR2020★ 10 cited
COLD: Towards the Next Generation of Pre-Ranking System
Zhe Wang, Liqin Zhao, Biye Jiang +3
Multi-stage cascade architecture exists widely in many industrial systems such as recommender systems and online advertising, which often consists of sequential modules including m…
stat.ML2018
Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate
Xiao Ma, Liqin Zhao, Guan Huang +4
Estimating post-click conversion rate (CVR) accurately is crucial for ranking systems in industrial applications such as recommendation and advertising. Conventional CVR modeling a…