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Private Multiplicative Weights Beyond Linear Queries

Summary: Adapts the Private Multiplicative Weights paradigm to convex minimization, enabling accurate differentially private solutions for exponentially many convex optimization tasks (e.g., linear and logistic regression). Introduces reductions and algorithmic techniques to handle general convex loss queries, extending PMW beyond linear queries. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1640
Venue
PODS
Year
2015
Pagerank
7.3115472e-05
Overall Rank
3,261 | 77.32%
DOI
10.1145/2745754.2745755

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