Causal Inference and Machine Learning in Practice: Use Cases for Product, Brand, Policy and Beyond
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- Causal Inference and Machine Learning in Practice: Use Cases for Product, Brand, Policy and Beyond
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Causal Inference and Causal Machine Learning with Practical Applications: The paper highlights the concepts of Causal Inference and Causal ML along with different implementation techniques
CODS-COMAD '23: Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD)One of the most important research areas in Machine Learning is to build prescriptive models. This requires understanding and measurement of the causal impact of any proposed treatment, followed by designing optimal strategy based on such causal ...
Open problems in causal structure learning: A case study of COVID-19 in the UK
AbstractCausal machine learning (ML) algorithms recover graphical structures that tell us something about cause-and-effect relationships. The causal representation provided by these algorithms enables transparency and explainability, which is necessary ...
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- General Chairs:
- Ambuj Singh,
- Yizhou Sun,
- Program Chairs:
- Leman Akoglu,
- Dimitrios Gunopulos,
- Xifeng Yan,
- Ravi Kumar,
- Fatma Ozcan,
- Jieping Ye
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Association for Computing Machinery
New York, NY, United States
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