Concepedia

Differentially Private Mean Estimation

Differentially Private Mean Estimation is a statistical method for estimating the mean of a dataset while providing rigorous privacy guarantees by ensuring that the inclusion or exclusion of any single data point does not significantly affect the output distribution, thereby satisfying the formal criterion of differential privacy.

20

Publications

684

Citations

55

Authors

34

Institutions

Publications per year

2017–2026

18

Parents

Publications

20

Differential Privacy for Statistics: What we Know and What we Want to Learn

Cynthia Dwork, Adam Smith · Journal of Privacy and Confidentiality · 2010 · 275 citations · Full text

, , +12

Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs

Antonious M. Girgis, Deepesh Data, Suhas Diggavi et al. · IEEE Journal on Selected Areas in Information Theory · 2021 · 50 citations

, , +16

Finite Sample Differentially Private Confidence Intervals

Vishesh Karwa, Salil Vadhan · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 2017 · 38 citations · Full text

, , +13

Mean estimation over numeric data with personalized local differential privacy

Qiao Xue, Youwen Zhu, Jian Wang · Frontiers of Computer Science · 2021 · 34 citations

, , +16

CoinPress: Practical Private Mean and Covariance Estimation

Sourav Biswas, Yihe Dong, Gautam Kamath et al. · arXiv (Cornell University) · 2020 · 26 citations · Full text

, , +13

1–5 of 20

Authors

55

  1. GK
    Gautam Kamath

    Massachusetts Institute of Technology, United States

    5 publications · 94 citations

    5

    h-index

  2. JU
    Jonathan Ullman

    Harvard University, United States

    3 publications · 60 citations

    3

    h-index

  3. VS
    Vikrant Singhal

    Universidad del Noreste, Mexico

    2 publications · 34 citations

    2

    h-index

  4. TS
    Thomas Steinke

    Zuse Institute Berlin, Germany

    2 publications · 48 citations

    2

    h-index

  5. MB
    Mark Bun

    Princeton University, United States

    2 publications · 48 citations

    2

    h-index

1–5 of 55

Institutions

34

  1. University of Waterloo

    Waterloo, Canada

    4 h-index

    5 publications

    100 citations

  2. Massachusetts Institute of Technology

    Cambridge, United States

    3 h-index

    3 publications

    49 citations

  3. Carnegie Mellon University

    Pittsburgh, United States

    2 h-index

    4 publications

    113 citations

  4. Northeastern University

    Boston, United States

    2 h-index

    3 publications

    64 citations

  5. Microsoft Research (United Kingdom)

    Cambridge, United Kingdom

    2 h-index

    2 publications

    292 citations

  6. Google (United States)

    Mountain View, United States

    2 h-index

    3 publications

    117 citations

  7. University of California, Los Angeles

    Los Angeles, United States

    1 h-index

    3 publications

    150 citations

  8. Microsoft (United States)

    Redmond, United States

    1 h-index

    1 publications

    275 citations

1–8 of 34

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 194 citations

    11

    h-index

  2. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 1 publications · 38 citations

    1

    h-index

  3. 2022 IEEE Symposium on Security and Privacy (SP)

    Conference · 1 publications · 25 citations

    1

    h-index

  4. Frontiers of Computer Science

    1 publications · 34 citations

    1

    h-index

  5. IEEE Journal on Selected Areas in Information Theory

    JSAIT · 1 publications · 50 citations

    1

    h-index

1–5