Variance Reduction Using In-Experiment Data: Efficient and Targeted Online Measurement for Sparse and Delayed Outcomes

Alex Deng, Michelle Du, Anna Matlin, Qing Zhang. Variance Reduction Using In-Experiment Data: Efficient and Targeted Online Measurement for Sparse and Delayed Outcomes. In Ambuj Singh, Yizhou Sun, Leman Akoglu, Dimitrios Gunopulos, Xifeng Yan, Ravi Kumar 0001, Fatma Ozcan, Jieping Ye, editors, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023. pages 3937-3946, ACM, 2023. [doi]

@inproceedings{DengDMZ23,
  title = {Variance Reduction Using In-Experiment Data: Efficient and Targeted Online Measurement for Sparse and Delayed Outcomes},
  author = {Alex Deng and Michelle Du and Anna Matlin and Qing Zhang},
  year = {2023},
  doi = {10.1145/3580305.3599928},
  url = {https://doi.org/10.1145/3580305.3599928},
  researchr = {https://researchr.org/publication/DengDMZ23},
  cites = {0},
  citedby = {0},
  pages = {3937-3946},
  booktitle = {Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023},
  editor = {Ambuj Singh and Yizhou Sun and Leman Akoglu and Dimitrios Gunopulos and Xifeng Yan and Ravi Kumar 0001 and Fatma Ozcan and Jieping Ye},
  publisher = {ACM},
}