• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 128 matches

• 2025
• 
  Anam Zahid, Faisal Kamiran, Samar Abbas, Bilal Qureshi, Asim Karim:
  Data-Driven Uplift Modeling. IEEE Access 13: 62462-62475 (2025)
• 
  Yertai Tanai, Kamil Ciftci:
  How to customize an early start preparatory course policy to improve student graduation success: an application of uplift modeling. Ann. Oper. Res. 347(2): 913-936 (2025)
• 
  Björn Bokelmann, Stefan Lessmann:
  Heteroscedasticity-aware stratified sampling to improve uplift modeling. Eur. J. Oper. Res. 325(1): 118-131 (2025)
• 
  Zexu Sun, Qiyu Han, Minqin Zhu, Hao Gong, Dugang Liu, Chen Ma:
  Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing. KDD (1) 2025: 1325-1336
• 
  Zexu Sun, Qiyu Han, Minqin Zhu, Hao Gong, Dugang Liu, Chen Ma:
  Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing. CoRR abs/2502.15697 (2025)
• 
  Hangtao Zhang, Zhe Li, Kairui Zhang:
  TSCAN: Context-Aware Uplift Modeling via Two-Stage Training for Online Merchant Business Diagnosis. CoRR abs/2504.18881 (2025)
• 2024
• 
  Carla Vairetti, María José Marfán, Sebastián Maldonado:
  Dealing With Class Imbalance in Uplift Modeling-Efficient Data Preprocessing via Oversampling and Matching. IEEE Access 12: 188993-189008 (2024)
• 
  Jinping Hu, Evert de Haan, Bernd Skiera:
  Uplift modeling with quasi-loss-functions. Data Min. Knowl. Discov. 38(4): 2495-2519 (2024)
• 
  Dujuan Wang, Qihang Xu, Yi Feng, Joshua Ignatius, Yunqiang Yin, Di Xiao:
  Uplift modeling and its implications for appointment date prediction in attended home delivery. Decis. Support Syst. 185: 114303 (2024)
• 
  Baoqiang Zhan, Chao Li, Yongli Li, Chong Wu:
  Weighted doubly robust learning: An uplift modeling technique for estimating mixed treatments' effect. Decis. Support Syst. 176: 114060 (2024)
• 
  Carla Vairetti, Franco Gennaro, Sebastián Maldonado:
  Propensity score oversampling and matching for uplift modeling. Eur. J. Oper. Res. 316(3): 1058-1069 (2024)
• 
  Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi:
  Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment. Mach. Learn. 113(3): 1043-1067 (2024)
• 
  Carla Vairetti, Raimundo Vargas, Catalina Sánchez, Andrés García, Guillermo Armelini, Sebastián Maldonado:
  Improving incentive policies to salespeople cross-sells: a cost-sensitive uplift modeling approach. Neural Comput. Appl. 36(28): 17541-17558 (2024)
• 
  Zexu Sun, Dugang Liu, Xing Tang, Yunpeng Weng, Xiuqiang He:
  Towards Effective and Efficient Multi-valued Treatment Uplift Modeling in Online Marketing. DASFAA (7) 2024: 121-138
• 
  Zexu Sun, Xu Chen:
  M³TN: Multi-Gate Mixture-of-Experts Based Multi-Valued Treatment Network for Uplift Modeling. ICASSP 2024: 5065-5069
• 
  Kun Li, Liangshu Zhu:
  A New Transformation Approach for Uplift Modeling with Binary Outcome. ICMAI 2024: 73-77
• 
  Bowei He, Yunpeng Weng, Xing Tang, Ziqiang Cui, Zexu Sun, Liang Chen, Xiuqiang He, Chen Ma:
  Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing. KDD 2024: 5093-5104
• 
  Xin Zhang, Kai Wang, Zengmao Wang, Bo Du, Shiwei Zhao, Runze Wu, Xudong Shen, Tangjie Lv, Changjie Fan:
  Temporal Uplift Modeling for Online Marketing. KDD 2024: 6247-6256
• 
  Baoqiang Zhan, Eric W. T. Ngai, Chong Wu:
  Assigning the Optimal Treatment for Your Customers: A Counterfactual-based Uplift Modeling Approach. PACIS 2024
• 
  George Panagopoulos, Daniele Malitesta, Fragkiskos D. Malliaros, Jun Pang:
  Uplift Modeling Under Limited Supervision. ECML/PKDD (6) 2024: 127-144
• 
  Junjie Gao, Xiangyu Zheng, Dongdong Wang, Zhixiang Huang, Bangqi Zheng:
  UTBoost: Gradient Boosted Decision Trees for Uplift Modeling. PRICAI (1) 2024: 41-53
• 
  Zexu Sun, Hao Yang, Dugang Liu, Yunpeng Weng, Xing Tang, Xiuqiang He:
  End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling. RecSys 2024: 560-569
• 
  Yinqiu Huang, Shuli Wang, Min Gao, Xue Wei, Changhao Li, Chuan Luo, Yinhua Zhu, Xiong Xiao, Yi Luo:
  Entire Chain Uplift Modeling with Context-Enhanced Learning for Intelligent Marketing. WWW (Companion Volume) 2024: 226-234
• 
  Wenjie Wang, Changsheng Wang, Fuli Feng, Wentao Shi, Daizong Ding, Tat-Seng Chua:
  Uplift Modeling for Target User Attacks on Recommender Systems. WWW 2024: 3343-3354
• 
  Zexu Sun, Xu Chen:
  M³TN: Multi-gate Mixture-of-Experts based Multi-valued Treatment Network for Uplift Modeling. CoRR abs/2401.14426 (2024)
• 
  Yinqiu Huang, Shuli Wang, Min Gao, Xue Wei, Changhao Li, Chuan Luo, Yinhua Zhu, Xiong Xiao, Yi Luo:
  Entire Chain Uplift Modeling with Context-Enhanced Learning for Intelligent Marketing. CoRR abs/2402.03379 (2024)
• 
  Wenjie Wang, Changsheng Wang, Fuli Feng, Wentao Shi, Daizong Ding, Tat-Seng Chua:
  Uplift Modeling for Target User Attacks on Recommender Systems. CoRR abs/2403.02692 (2024)
• 
  Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou:
  Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling. CoRR abs/2403.06489 (2024)
• 
  Serdar Kadioglu, Filip Michalský:
  Fairness Evaluation for Uplift Modeling in the Absence of Ground Truth. CoRR abs/2403.12069 (2024)
• 
  Bowei He, Yunpeng Weng, Xing Tang, Ziqiang Cui, Zexu Sun, Liang Chen, Xiuqiang He, Chen Ma:
  Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing. CoRR abs/2405.15301 (2024)

skipping 98 more matches