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Happiness Maximizing Sets under Group Fairness Constraints

Summary: Introduces FairHMS: select a small subset maximizing the minimum happiness ratio across all nonnegative linear utilities while enforcing per-group lower/upper cardinality bounds for representation. Proves NP-hardness for ≥3 dims, gives exact 2D IntCov, a bicriteria BiGreedy via submodular maximization under a matroid with adaptive sampling, and empirically validates efficiency and effectiveness. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13132
Venue
VLDB
Year
2023
Pagerank
4.3690661e-05
Overall Rank
9,246 | 35.68%
DOI
10.14778/3565816.3565830

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Rank Citing Paper Year Venue Pagerank
10,223 On Fair Epsilon Net and Geometric Hitting Set 2026 VLDB 4.1945683e-05
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