Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization-Reference-Cited by-同舟云学术

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Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization

Published:2023-12-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Data Mining (ICDM)
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Author:

Sun Zexu¹,He Bowei²,Ma Ming³,Tang Jiakai¹,Wang Yuchen³,Ma Chen²,Liu Dugang⁴

Affiliation:

1. Renmin University of China,Gaoling School of Artificial Intelligence

2. City University of Hong Kong,Department of Computer Science

3. Kuaishou Technology

4. Shenzhen University,Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10415628/10415561/10415650.pdf?arnumber=10415650

Reference17 articles.

1. Explicit Feature Interaction-aware Uplift Network for Online Marketing

2. Qini-based uplift regression

3. Metalearners for estimating heterogeneous treatment effects using machine learning

4. Real-world uplift modelling with significance-based uplift trees;Radcliffe;White Paper TR-2011-1, Stochastic Solutions,2011

5. Increasing the robustness of uplift modeling using additional splits and diversified leaf select

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Improve ROI with Causal Learning and Conformal Prediction;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

2. M³TN: Multi-Gate Mixture-of-Experts Based Multi-Valued Treatment Network for Uplift Modeling;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Towards Effective and Efficient Multi-valued Treatment Uplift Modeling in Online Marketing;Lecture Notes in Computer Science;2024

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