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Bounding the Excess Risk for Linear Models Trained on
  Marginal-Preserving, Differentially-Private, Synthetic Data
v1v2 (latest)

Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data

6 February 2024
Yvonne Zhou
Mingyu Liang
Shubham Sharma
Dana Dachman-Soled
Danial Dervovic
Antigoni Polychroniadou
Min Wu
ArXiv (abs)PDFHTML

Papers citing "Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data"

2 / 2 papers shown
Private Regression via Data-Dependent Sufficient Statistic Perturbation
Private Regression via Data-Dependent Sufficient Statistic Perturbation
Cecilia Ferrando
Daniel Sheldon
244
3
0
23 May 2024
Balancing Fairness and Accuracy in Data-Restricted Binary Classification
Balancing Fairness and Accuracy in Data-Restricted Binary ClassificationACM Transactions on Knowledge Discovery from Data (TKDD), 2024
Zachary McBride Lazri
Danial Dervovic
Antigoni Polychroniadou
Shubham Sharma
Dana Dachman-Soled
Min Wu
FaML
186
0
0
12 Mar 2024
1