March Boedihardjo

According to our database, March Boedihardjo authored at least 9 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Covariance's Loss is Privacy's Gain: Computationally Efficient, Private and Accurate Synthetic Data.

March Boedihardjo, Thomas Strohmer, Roman Vershynin

Found. Comput. Math., February, 2024

2023

Privacy of Synthetic Data: A Statistical Framework.

March Boedihardjo, Thomas Strohmer, Roman Vershynin

IEEE Trans. Inf. Theory, 2023

Sample-efficient private data release for Lipschitz functions under sparsity assumptions.

Konstantin Donhauser, Johan Lokna, Amartya Sanyal, March Boedihardjo, Robert Hönig, Fanny Yang

CoRR, 2023

Covariance loss, Szemeredi regularity, and differential privacy.

March Boedihardjo, Thomas Strohmer, Roman Vershynin

CoRR, 2023

2022

Private Sampling: A Noiseless Approach for Generating Differentially Private Synthetic Data.

March Boedihardjo, Thomas Strohmer, Roman Vershynin

SIAM J. Math. Data Sci., September, 2022

Private measures, random walks, and synthetic data.

March Boedihardjo, Thomas Strohmer, Roman Vershynin

CoRR, 2022

2021

A Performance Guarantee for Spectral Clustering.

March Boedihardjo, Shaofeng Deng, Thomas Strohmer

SIAM J. Math. Data Sci., 2021

2020

DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM.

Bao Wang, Quanquan Gu, March Boedihardjo, Lingxiao Wang, Farzin Barekat, Stanley J. Osher

Proceedings of Mathematical and Scientific Machine Learning, 2020

2019

DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM.

Bao Wang, Quanquan Gu, March Boedihardjo, Farzin Barekat, Stanley J. Osher

CoRR, 2019