Database Paper Browser

Back to papers

Optimizing Fitness-For-Use of Differentially Private Linear Queries

Summary: Treats DP for linear queries with per-query accuracy, noting matrix mechanisms optimize total error rather than per-query usefulness. Proposes Gaussian-noise strategy with optimized covariance to meet per-query accuracy while minimizing privacy cost. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12358
Venue
VLDB
Year
2021
Pagerank
4.6105691e-05
Overall Rank
7,997 | 44.37%
DOI
10.14778/3467861.3467864

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers