@article{kim2025robustdppca,
  author = {Kim, Minwoo and Jung, Sungkyu},
  title = {Robust and Differentially Private Principal Component Analysis},
  journal = {Statistical Analysis and Data Mining: An ASA Data Science Journal},
  volume = {18},
  number = {6},
  pages = {e70053},
  doi = {https://doi.org/10.1002/sam.70053},
  year = {2025}
}

@article{dwork2014algorithmic,
author = {Dwork, Cynthia and Roth, Aaron},
title = {The Algorithmic Foundations of Differential Privacy},
year = {2014},
issue_date = {Aug 2014},
publisher = {Now Publishers Inc.},
address = {Hanover, MA, USA},
volume = {9},
number = {3–4},
issn = {1551-305X},
url = {https://doi.org/10.1561/0400000042},
doi = {10.1561/0400000042},
journal = {Found. Trends Theor. Comput. Sci.},
month = aug,
pages = {211–407},
numpages = {197}
}

@misc{ramsay2025pmw,
      title={Improved subsample-and-aggregate via the private modified winsorized mean},
      author={Kelly Ramsay and Dylan Spicker},
      year={2025},
      eprint={2501.14095},
      archivePrefix={arXiv},
      primaryClass={stat.ME},
      url={https://arxiv.org/abs/2501.14095},
      note = {Code available at \url{https://github.com/12ramsake/PMWM}}
}

@article{yu2024gaussian,
  title={Gaussian differentially private robust mean estimation and inference},
  author={Yu, Myeonghun and Ren, Zhao and Zhou, Wen-xin},
  journal={Bernoulli},
  volume={30},
  number={4},
  pages={3059--3088},
  year={2024},
  publisher={Bernoulli Society for Mathematical Statistics and Probability}
}

@inproceedings{nissim2007smooth,
  author = {Nissim, Kobbi and Raskhodnikova, Sofya and Smith, Adam},
  title = {Smooth Sensitivity and Sampling in Private Data Analysis},
  booktitle = {STOC'07: Proceedings of the 39th Annual ACM Symposium on Theory of Computing},
  year = {2007},
  pages = {75--84},
  doi = {10.1145/1250790.1250803},
  url = {https://doi.org/10.1145/1250790.1250803},
  isbn = {9781595936318}
}

@article{wasserman2010statistical,
author = {Wasserman, Larry and Zhou, Shuheng},
title = {A Statistical Framework for Differential Privacy},
journal = {Journal of the American Statistical Association},
volume = {105},
number = {489},
pages = {375--389},
year = {2010},
publisher = {ASA Website},
doi = {10.1198/jasa.2009.tm08651},
}


@inproceedings{karwa2017finite,
  title = {Finite Sample Differentially Private Confidence Intervals},
  author = {Karwa, Vishesh and Vadhan, Salil},
  booktitle = {Proceedings of the 9th Innovations in Theoretical Computer Science Conference},
  series = {Leibniz International Proceedings in Informatics},
  volume = {94},
  pages = {44:1--44:9},
  year = {2018},
  doi = {10.4230/LIPIcs.ITCS.2018.44}
}

@misc{adult,
  author       = {Becker, Barry and Kohavi, Ronny},
  title        = {{Adult}},
  year         = {1996},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: https://doi.org/10.24432/C5XW20},
  url          = {https://archive.ics.uci.edu/dataset/2/adult}
}
