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CDPD 2023, Long Beach, CA, USA
- Thuc Duy Le, Jiuyong Li, Robert Ness, Sofia Triantafillou, Shohei Shimizu, Peng Cui, Kun Kuang, Jian Pei, Fei Wang, Mattia Prosperi:
The KDD'23 Workshop on Causal Discovery, Prediction and Decision, 07 August 2023, Long Beach, CA, USA. Proceedings of Machine Learning Research 218, PMLR 2023 - Thuc Duy Le, Jiuyong Li, Robert Ness, Sofia Triantafillou, Shohei Shimizu, Peng Cui, Kun Kuang, Jian Pei, Fei Wang, Mattia Prosperi:
Preface: The 2023 ACM SIGKDD Workshop on Causal Discovery, Prediction and Decision. 1-2 - Oliver Schacht, Sven Klaassen, Philipp Schwarz, Martin Spindler, Daniel Grünbaum, Sebastian Imhof:
Causally Learning an Optimal Rework Policy. 3-24 - Lorenzo Masoero, Doug Hains, James McQueen:
Leveraging covariate adjustments at scale in online A/B testing. 25-48 - Shengyu Zhang, Yunze Tong, Kun Kuang, Fuli Feng, Jiezhong Qiu, Jin Yu, Zhou Zhao, Hongxia Yang, Zhongfei Zhang, Fei Wu:
Stable Prediction on Graphs with Agnostic Distribution Shifts. 49-74 - Wang Lu, Jindong Wang, Yidong Wang, Xing Xie:
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution. 75-97 - Inyoung Jun, Scott A. Cohen, Sarah E. Ser, Simone Marini, Robert J. Lucero, Jiang Bian, Mattia Prosperi:
Optimizing Dynamic Antibiotic Treatment Strategies against Invasive Methicillin-Resistant Staphylococcus Aureus Infections using Causal Survival Forests and G-Formula on Statewide Electronic Health Record Data. 98-115 - Ruoxuan Xiong, Alex Chin, Sean J. Taylor:
Bias-Variance Tradeoffs for Designing Simultaneous Temporal Experiments. 115-131
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