Dp-cryptography: marrying differential privacy and cryptography in emerging applications
DP-cryptography: marrying differential privacy and cryptography in emerging applications
Page 1 84 COMMUNICATIONS OF THE ACM | FEBRUARY 2021 | VOL. 64 | NO. 2 review …
Page 1 84 COMMUNICATIONS OF THE ACM | FEBRUARY 2021 | VOL. 64 | NO. 2 review …
Winning the NIST Contest: A scalable and general approach to differentially private synthetic data
We propose a general approach for differentially private synthetic data generation, that
consists of three steps:(1) select a collection of low-dimensional marginals,(2) measure …
consists of three steps:(1) select a collection of low-dimensional marginals,(2) measure …
(Amplified) Banded Matrix Factorization: A unified approach to private training
Matrix factorization (MF) mechanisms for differential privacy (DP) have substantially
improved the state-of-the-art in privacy-utility-computation tradeoffs for ML applications in a …
improved the state-of-the-art in privacy-utility-computation tradeoffs for ML applications in a …
Tabular and latent space synthetic data generation: a literature review
The generation of synthetic data can be used for anonymization, regularization,
oversampling, semi-supervised learning, self-supervised learning, and several other tasks …
oversampling, semi-supervised learning, self-supervised learning, and several other tasks …
Improved differential privacy for sgd via optimal private linear operators on adaptive streams
Motivated by recent applications requiring differential privacy in the setting of adaptive
streams, we investigate the question of optimal instantiations of the matrix mechanism in this …
streams, we investigate the question of optimal instantiations of the matrix mechanism in this …
Differentially private query release through adaptive projection
We propose, implement, and evaluate a new algo-rithm for releasing answers to very large
numbersof statistical queries likek-way marginals, sub-ject to differential privacy. Our …
numbersof statistical queries likek-way marginals, sub-ject to differential privacy. Our …
Graphical-model based estimation and inference for differential privacy
Many privacy mechanisms reveal high-level information about a data distribution through
noisy measurements. It is common to use this information to estimate the answers to new …
noisy measurements. It is common to use this information to estimate the answers to new …
Aim: An adaptive and iterative mechanism for differentially private synthetic data
We propose AIM, a novel algorithm for differentially private synthetic data generation.\aim is
a workload-adaptive algorithm, within the paradigm of algorithms that first selects a set of …
a workload-adaptive algorithm, within the paradigm of algorithms that first selects a set of …
Privatesql: a differentially private sql query engine
Differential privacy is considered a de facto standard for private data analysis. However, the
definition and much of the supporting literature applies to flat tables. While there exist …
definition and much of the supporting literature applies to flat tables. While there exist …
Leveraging public data for practical private query release
In many statistical problems, incorporating priors can significantly improve performance.
However, the use of prior knowledge in differentially private query release has remained …
However, the use of prior knowledge in differentially private query release has remained …