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20192021
most citedDP-MERF: Differentially Private Mean Embeddings with Random Features for Practical Privacy-Preserving Data Generation

23 citations · 26 across the 4 of their papers we have counts for

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Showing 2021Show all

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cs.LG2021★ 1 cited

Hermite Polynomial Features for Private Data Generation

Margarita Vinaroz, Mohammad-Amin Charusaie, Frederik Harder +2

Kernel mean embedding is a useful tool to represent and compare probability measures. Despite its usefulness, kernel mean embedding considers infinite-dimensional features, which a…