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Found 3 papers, 1 papers with code
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
The remaining subsampling-induced variance decreases with larger batch sizes, so large batches reduce the effective total gradient variance.
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
We investigate how our theory works in practice by evaluating the performance of an ensemble over many synthetic datasets for several real datasets and downstream predictors.
Noise-Aware Statistical Inference with Differentially Private Synthetic Data
For example, confidence intervals become too narrow, which we demonstrate with a simple experiment.
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