Pointwise spectral density estimation under local differential privacy

Aktivität: VorträgeVortragScience to Science


Invited talk held at the Session "Time series 2"
Abstract: We propose a new interactive locally differentially private mechanism for estimating Höldersmooth spectral density functions of stationary Gaussian processes. Anonymization is achieved through two-stage truncation and subsequent Laplace perturbation. In particular, we show that our method
achieves a pointwise L2-rate with a dependency of only a^2 on the privacy parameter a. This rate stands in contrast to the results of (Kroll, 2024), who proposed a non-interactive mechanism for spectral density estimation and showed a dependency of a^4 on the privacy parameter for the uniform L2-rate.
Zeitraum26 Juni 2024
EreignistitelInternational Symposium on Nonparametric Statistics 2024
OrtBraga, PortugalAuf Karte anzeigen


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