{"id":27867,"date":"2026-04-13T12:29:03","date_gmt":"2026-04-13T12:29:03","guid":{"rendered":"https:\/\/dataforpublicgood.org.in\/?p=27867"},"modified":"2026-04-13T12:31:06","modified_gmt":"2026-04-13T12:31:06","slug":"improving-the-privacy-loss-under-user-level-dp-composition-for-fixed-estimation-error","status":"publish","type":"post","link":"https:\/\/dataforpublicgood.org.in\/cdpg\/data-privacy\/improving-the-privacy-loss-under-user-level-dp-composition-for-fixed-estimation-error\/","title":{"rendered":"Improving the Privacy Loss Under User-Level DP Composition for Fixed Estimation Error"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"27867\" class=\"elementor elementor-27867\">\n\t\t\t\t\t\t<div class=\"elementor-inner\">\n\t\t\t\t<div class=\"elementor-section-wrap\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2dac990 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2dac990\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-51804ec\" data-id=\"51804ec\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5ac4424 elementor-widget elementor-widget-text-editor\" data-id=\"5ac4424\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-438085c elementor-widget elementor-widget-text-editor\" data-id=\"438085c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<h1>Improving the Privacy Loss Under User-Level DP Composition for Fixed Estimation Error<\/h1>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ff9263c elementor-widget elementor-widget-text-editor\" data-id=\"ff9263c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p style=\"color: blue;\"><strong>Authors<\/strong>:V. A. Rameshwar and A. Tandon<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9514863 elementor-widget elementor-widget-text-editor\" data-id=\"9514863\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p>This paper considers the private release of statistics of several disjoint subsets of a datasets. In particular, we consider the\u00a0<span class=\"MathJax_Preview\">\\epsilon<\/span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax MathJax_Processing\" tabindex=\"0\"><\/span>-user-level differentially private release of sample means and variances of sample values in disjoint subsets of a dataset, in a potentially sequential manner. Traditional analysis of the privacy loss under user-level privacy due to the composition of queries to the disjoint subsets necessitates a privacy loss degradation by the total number of disjoint subsets. Our main contribution is an iterative algorithm, based on suppressing user contributions, which seeks to reduce the overall privacy loss degradation under a canonical Laplace mechanism, while not increasing the worst estimation error among the subsets. Important components of this analysis are our exact, analytical characterizations of the sensitivities and the worst-case bias errors of estimators of the sample mean and variance, which are obtained by clipping or suppressing user contributions. We test the performance of our algorithm on real-world and synthetic datasets and demonstrate improvements in the privacy loss degradation factor, for fixed estimation error. We also show improvements in the worst-case error across subsets, via a natural optimization procedure, for fixed numbers of users contributing to each subset.<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-85f0dee elementor-widget elementor-widget-text-editor\" data-id=\"85f0dee\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<strong>Journal\/Conference\n<\/strong> 2025 IEEE International Symposium on Information Theory (ISIT)\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-979fd33\" data-id=\"979fd33\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4ce5c30 elementor-widget elementor-widget-image\" data-id=\"4ce5c30\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-image\">\n\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"878\" height=\"772\" src=\"https:\/\/dataforpublicgood.org.in\/cdpg\/wp-content\/uploads\/2026\/04\/4.jpg.jpeg\" class=\"attachment-full size-full\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c27cce3 elementor-button-success elementor-align-center elementor-widget elementor-widget-button\" data-id=\"c27cce3\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a href=\"https:\/\/arxiv.org\/abs\/2405.06261v2\" target=\"_blank\" class=\"elementor-button-link elementor-button elementor-size-sm elementor-animation-shrink\" role=\"button\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Know more<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3d308ba elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3d308ba\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-e1458bc\" data-id=\"e1458bc\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5229c9c elementor-widget elementor-widget-html\" data-id=\"5229c9c\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\n    .post-style-3 .entry-header {\n        display: none;\n    }\n    \n    h1 {\n        font-size:28px !important;\n        text-transform: inherit !important;\n    }\n    \n<\/style>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<div style=\"margin-top: 0px; margin-bottom: 0px;\" class=\"sharethis-inline-share-buttons\" ><\/div>","protected":false},"excerpt":{"rendered":"<p>Improving the Privacy Loss Under User-Level DP Composition for Fixed Estimation Error Authors:V. A. Rameshwar and A. Tandon This paper considers the private release of statistics of several disjoint subsets of a datasets. In particular, we consider the\u00a0epsilon-user-level differentially private release of sample means and variances of sample values in disjoint subsets of a dataset, in a potentially sequential manner. &hellip;<\/p>\n","protected":false},"author":3,"featured_media":27868,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[92],"tags":[],"class_list":["post-27867","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-privacy"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.12 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Breaking Data Silos: How GDI is Transforming Access to Geospatial Information in India<\/title>\n<meta name=\"description\" content=\"Designed to treat publicly funded geospatial data as a common good, GDI has established itself as a unified, open-access platform for 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