Mean estimation in the add-remove model of differential privacy

arXiv:2312.06658v2 Announce Type: replace-cross
Abstract: Differential privacy is often studied under two different models of neighboring datasets: the add-remove model and the swap model. While the swap model is frequently used in the academic literature to simplify analysis, many practical applications rely on the more conservative add-remove model, where obtaining tight results can be difficult. Here, we study the problem of one-dimensional mean estimation under the add-remove model. We propose a new algorithm and show that it is min-max optimal, …

academic analysis applications arxiv cs.cr cs.ds cs.it datasets differential privacy literature math.it privacy remove simplify stat.ml under