17 citations · 20 across the 10 of their papers we have counts for
4 papers · 1 filter
Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing
Zexu Sun, Qiyu Han, Minqin Zhu +3
Improving user engagement and platform revenue is crucial for online marketing platforms. Uplift modeling is proposed to solve this problem, which applies different treatments (e.g…
End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling
Zexu Sun, Hao Yang, Dugang Liu +3
In modern online platforms, incentives are essential factors that enhance user engagement and increase platform revenue. Over recent years, uplift modeling has been introduced as a…
OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction
Yunpeng Weng, Xing Tang, Zhenhao Xu +4
Customer Lifetime Value (CLTV) prediction is a critical task in business applications. Accurately predicting CLTV is challenging in real-world business scenarios, as the distributi…
Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning
Jiakai Tang, Sunhao Dai, Zexu Sun +6
In recent years, graph contrastive learning (GCL) has received increasing attention in recommender systems due to its effectiveness in reducing bias caused by data sparsity. Howeve…