Fields- Workshop on Differential Privacy and Statistical Data Analysis

  1. Title:
    Private Learning of Gaussians and their Mixtures

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  2. Title:
    Control, Confidentiality, and the Right to Be Forgotten

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  3. Title:
    Private Tabular Survey Data Products through Synthetic Microdata Generation

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  4. Title:
    Plume: Differential Privacy at Scale

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  5. Title:
    Differentially Private Simple Linear Regression

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  6. Title:
    Obstacles to Adoption of DP at National Statistical Agencies

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  7. Title:
    The 2020 U.S. Census Disclosure Avoidance System TopDown Algorithm

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  8. Title:
    On the Complexity of Two-Party Differential Privacy

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  9. Title:
    Uncertainty Estimation in Differentially Private Analyses

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  10. Title:
    Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism

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  11. Title:
    The Sum-of-Squares Method

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  12. Title:
    Non-Parametric Differentially Private Confidence Intervals for the Median

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  13. Title:
    The Privacy-Accuracy Trade-off for Multivariate Medians

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  14. Title:
    Data Augmentation MCMC for Bayesian Inference from Privatized Data

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  15. Title:
    Practical Hypothesis Tests with Rank-Based Methods

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  16. Title:
    Misspecification, and Uncertainty Quantification in Differential Privacy

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  17. Title:
    Premonitions of Public Data for Private ML

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  18. Title:
    Differentially Private Sampling from Distributions

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  19. Title:
    Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms

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  20. Title:
    Privacy, Stability, and Online Learning

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