Preface: The 2023 ACM SIGKDD Workshop on Causal Discovery, Prediction and Decision

Thuc Le, Jiuyong Li, Robert Ness, Sofia Triantafillou, Shohei Shimizu, Peng Cui, Kun Kuang, Jian Pei, Fei Wang, Mattia Prosperi; Proceedings of The KDD'23 Workshop on Causal Discovery, Prediction and Decision, PMLR 218:1-2

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Causally Learning an Optimal Rework Policy

Oliver Schacht, Sven Klaassen, Philipp Schwarz, Martin Spindler, Daniel Grunbaum, Sebastian Imhof; Proceedings of The KDD'23 Workshop on Causal Discovery, Prediction and Decision, PMLR 218:3-24

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Leveraging covariate adjustments at scale in online A/B testing

Lorenzo Masoero, Doug Hains, James McQueen; Proceedings of The KDD'23 Workshop on Causal Discovery, Prediction and Decision, PMLR 218:25-48

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Stable Prediction on Graphs with Agnostic Distribution Shifts

Shengyu Zhang, Yunze Tong, Kun Kuang, Fuli Feng, Jiezhong Qiu, Jin Yu, Zhou Zhao, Hongxia Yang, Zhongfei Zhang, Fei Wu; Proceedings of The KDD'23 Workshop on Causal Discovery, Prediction and Decision, PMLR 218:49-74

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Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution

Wang Lu, Wang Wang, Jindong Yidong, Xing Xie; Proceedings of The KDD'23 Workshop on Causal Discovery, Prediction and Decision, PMLR 218:75-97

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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

Inyoung Jun, Scott A. Cohen, Sarah E. Ser, Simone Marini, Robert J. Lucero, Jiang Bian, Mattia Prosperi; Proceedings of The KDD'23 Workshop on Causal Discovery, Prediction and Decision, PMLR 218:98-115

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Bias-Variance Tradeoffs for Designing Simultaneous Temporal Experiments

Ruoxuan Xiong, Alex Chin, Sean Taylor; Proceedings of The KDD'23 Workshop on Causal Discovery, Prediction and Decision, PMLR 218:115-131

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