Vol. 14 No. 1 (2024): Regular issue, including articles based on presentations at TPDP 2022 | Journal of Privacy and Confidentiality

Regular issue, includes additional articles based on presentations at TPDP 2022 - Theory and Practice of Differential Privacy.

Executive Editors: Lars Vilhuber and Rachel Cummings

Guest Editors (TPDP 2022 content): Audra McMillan and Gautam Kamath

DOI: https://doi.org/10.29012/jpc.v14i1

Published: 2024-02-11

Differentially Private Guarantees for Analytics and Machine Learning on Graphs: A Survey of Results

Tamara T. Mueller, Dmitrii Usynin, Johannes C. Paetzold, Rickmer Braren, Daniel Rueckert, Georgios Kaissis

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Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism

Arjun Wilkins, Daniel Kifer, Danfeng Zhang, Brian Karrer

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The Bounded Gaussian Mechanism for Differential Privacy

Bo Chen, Matthew Hale

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Private Convex Optimization via Exponential Mechanism

Sivakanth Gopi, Yin Tat Lee, Daogao Liu

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Numerical Composition of Differential Privacy

Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz

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The Journal of Privacy and Confidentiality is an open-access multi-disciplinary journal whose purpose is to facilitate the coalescence of research methodologies and activities in the areas of privacy, confidentiality, and disclosure limitation. The JPC seeks to publish a wide range of research and review papers, not only from academia, but also from government (especially official statistical agencies) and industry, and to serve as a forum for exchange of views, discussion, and news. For more information, see the About the Journal page.

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Published by the Society for Privacy and Confidentiality Research.

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