34 citations · 63 across the 26 of their papers we have counts for
5 papers · 1 filter
Private sampling: a noiseless approach for generating differentially private synthetic data
March Boedihardjo, Thomas Strohmer, Roman Vershynin
In a world where artificial intelligence and data science become omnipresent, data sharing is increasingly locking horns with data-privacy concerns. Differential privacy has emerge…
Privacy of synthetic data: a statistical framework
March Boedihardjo, Thomas Strohmer, Roman Vershynin
Privacy-preserving data analysis is emerging as a challenging problem with far-reaching impact. In particular, synthetic data are a promising concept toward solving the aporetic co…
Matrix Concentration Inequalities and Free Probability
Afonso S. Bandeira, March T. Boedihardjo, Ramon van Handel
A central tool in the study of nonhomogeneous random matrices, the noncommutative Khintchine inequality, yields a nonasymptotic bound on the spectral norm of general Gaussian rando…
Covariance's Loss is Privacy's Gain: Computationally Efficient, Private and Accurate Synthetic Data
March Boedihardjo, Thomas Strohmer, Roman Vershynin
The protection of private information is of vital importance in data-driven research, business, and government. The conflict between privacy and utility has triggered intensive res…
The spectral norm of Gaussian matrices with correlated entries
Afonso S. Bandeira, March T. Boedihardjo
We give a non-asymptotic bound on the spectral norm of a matrix with centered jointly Gaussian entries in terms of the covariance matrix of the entries. In some cas…