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cs.LG2024
Causal Feature Selection Method for Contextual Multi-Armed Bandits in Recommender System
Zhenyu Zhao, Yexi Jiang
Effective feature selection is essential for optimizing contextual multi-armed bandits (CMABs) in large-scale online systems, where suboptimal features can degrade rewards, interpr…
stat.ME2024
Integrating Active Learning in Causal Inference with Interference: A Novel Approach in Online Experiments
Hongtao Zhu, Sizhe Zhang, Yang Su +2
In the domain of causal inference research, the prevalent potential outcomes framework, notably the Rubin Causal Model (RCM), often overlooks individual interference and assumes in…
stat.AP2024
Treatment Effect Estimation Amidst Dynamic Network Interference in Online Gaming Experiments
Yu Zhu, Zehang Richard Li, Yang Su +1
The evolving landscape of online multiplayer gaming presents unique challenges in assessing the causal impacts of game features. Traditional A/B testing methodologies fall short du…