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Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data.
Yvonne Zhou
Mingyu Liang
Ivan Brugere
Dana Dachman-Soled
Danial Dervovic
Antigoni Polychroniadou
Min Wu
Published in:
CoRR (2024)
Keyphrases
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synthetic data
linear models
differentially private
variable selection
differential privacy
mixed effects
data sets
linear model
linear regression
gaussian processes
real world
real image data
probability distribution
training set
privacy preserving
causal relationships
maximum likelihood