Paper 2022/225
Constant matters: Fine-grained Complexity of Differentially Private Continual Observation Using Completely Bounded Norms
Monika Henzinger and Jalaj Upadhyay
Abstract
We study fine-grained error bounds for differentially private algorithms for averaging and counting in the continual observation model. For this, we use the completely bounded spectral norm (cb norm) from operator algebra. For a matrix
Metadata
- Available format(s)
-
PDF
- Category
- Applications
- Publication info
- Preprint.
- Keywords
- Differential privacycontinual observationconcrete bounds
- Contact author(s)
- jalaj kumar upadhyay @ gmail com
- History
- 2022-02-25: received
- Short URL
- https://ia.cr/2022/225
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2022/225, author = {Monika Henzinger and Jalaj Upadhyay}, title = {Constant matters: Fine-grained Complexity of Differentially Private Continual Observation Using Completely Bounded Norms}, howpublished = {Cryptology {ePrint} Archive, Paper 2022/225}, year = {2022}, url = {https://eprint.iacr.org/2022/225} }