AI RESEARCH
Noise-Aware Differentially Private Variational Inference
arXiv CS.LG
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ArXi:2410.19371v3 Announce Type: replace-cross Differential privacy (DP) provides robust privacy guarantees for statistical inference, but this can lead to unreliable results and biases in downstream applications. While several noise-aware approaches have been proposed which integrate DP perturbation into the inference, they are limited to specific types of simple probabilistic models.