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To address these concerns, we introduce Fair-Count-Min, a frequency estimation sketch that guarantees equal expected approximation factors across various groups. We propose a column partitioning approach with group-aware semi-uniform hashing to eliminate collisions between elements from different groups. We provide theoretical guarantees for fairness, analyze its associated cost, and validate our findings through extensive experiments on real-world datasets in comparison with representative state-of-the-art baselines. Our experimental results demonstrate that Fair-Count-Min achieves fairness with generally small additional error while maintaining efficiency comparable to that of the Count-Min sketch.<\/jats:p>","DOI":"10.1145\/3802056","type":"journal-article","created":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T18:19:16Z","timestamp":1779128356000},"page":"1-28","source":"Crossref","is-referenced-by-count":0,"title":["F\n                    <scp>air<\/scp>\n                    -C\n                    <scp>ount<\/scp>\n                    -M\n                    <scp>in<\/scp>\n                    : Frequency Estimation under Equal Group-wise Approximation Factor"],"prefix":"10.1145","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7016-3807","authenticated-orcid":false,"given":"Nima","family":"Shahbazi","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Illinois Chicago, Chicago, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2114-8886","authenticated-orcid":false,"given":"Stavros","family":"Sintos","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois Chicago, Chicago, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5251-6186","authenticated-orcid":false,"given":"Abolfazl","family":"Asudeh","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Illinois Chicago, Chicago, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,5,18]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"frequency estimation algorithms under Zipfian distribution. arXiv preprint arXiv:1908.05198","author":"Aamand Anders","year":"2019","unstructured":"Anders Aamand, Piotr Indyk, and Ali Vakilian. 2019a. frequency estimation algorithms under Zipfian distribution. arXiv preprint arXiv:1908.05198 (2019)."},{"key":"e_1_2_1_2_1","volume-title":"arXiv preprint arXiv:1908.05198","author":"Aamand Anders","year":"2019","unstructured":"Anders Aamand, Piotr Indyk, and Ali Vakilian. 2019b. 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