2 citations · 2 across the 3 of their papers we have counts for
4 papers
Bi-Level Decision-Focused Causal Learning for Large-Scale Marketing Optimization: Bridging Observational and Experimental Data
Shuli Zhang, Hao Zhou, Jiaqi Zheng +4
Online Internet platforms require sophisticated marketing strategies to optimize user retention and platform revenue -- a classical resource allocation problem. Traditional solutio…
STATE: A Robust ATE Estimator of Heavy-Tailed Metrics for Variance Reduction in Online Controlled Experiments
Hao Zhou, Kun Sun, Shaoming Li +4
Online controlled experiments play a crucial role in enabling data-driven decisions across a wide range of companies. Variance reduction is an effective technique to improve the se…
Decision Focused Causal Learning for Direct Counterfactual Marketing Optimization
Hao Zhou, Rongxiao Huang, Shaoming Li +4
Marketing optimization plays an important role to enhance user engagement in online Internet platforms. Existing studies usually formulate this problem as a budget allocation probl…
Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing
Hao Zhou, Shaoming Li, Guibin Jiang +2
Marketing is an important mechanism to increase user engagement and improve platform revenue, and heterogeneous causal learning can help develop more effective strategies. Most dec…