AI RESEARCH
Pure Differential Privacy for Functional Summaries with a Laplace-like Process
arXiv CS.LG
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ArXi:2309.00125v3 Announce Type: replace-cross Many existing mechanisms for achieving differential privacy (DP) on infinite-dimensional functional summaries typically involve embedding these functional summaries into finite-dimensional subspaces and applying traditional multivariate DP techniques. These mechanisms generally treat each dimension uniformly and struggle with complex, structured summaries. This work