17 citations · 20 across the 10 of their papers we have counts for
6 papers · 1 filter
Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing
Bowei He, Yunpeng Weng, Xing Tang +5
Uplift modeling has been widely employed in online marketing by predicting the response difference between the treatment and control groups, so as to identify the sensitive individ…
Benchmarking for Deep Uplift Modeling in Online Marketing
Dugang Liu, Xing Tang, Yang Qiao +4
Online marketing is critical for many industrial platforms and business applications, aiming to increase user engagement and platform revenue by identifying corresponding delivery-…
Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneck
Hao Yang, Zexu Sun, Hongteng Xu +1
As a promising individualized treatment effect (ITE) estimation method, counterfactual regression (CFR) maps individuals' covariates to a latent space and predicts their counterfac…
MTN: Multi-gate Mixture-of-Experts based Multi-valued Treatment Network for Uplift Modeling
Zexu Sun, Xu Chen
Uplift modeling is a technique used to predict the effect of a treatment (e.g., discounts) on an individual's response. Although several methods have been proposed for multi-valued…
Offline Imitation Learning with Variational Counterfactual Reasoning
Bowei He, Zexu Sun, Jinxin Liu +3
In offline imitation learning (IL), an agent aims to learn an optimal expert behavior policy without additional online environment interactions. However, in many real-world scenari…
Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization
Zexu Sun, Bowei He, Ming Ma +4
Uplift modeling has shown very promising results in online marketing. However, most existing works are prone to the robustness challenge in some practical applications. In this pap…