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Group Fairness and Multi-criteria Optimization in School Assignment
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We consider the problem of assigning students to schools, when students have different utilities for schools and schools have capacity. There are additional group fairness considerations over students that can be captured either by concave objectives, or additional constraints on the groups. We present approximation algorithms for this problem via convex program rounding that achieve various trade-offs between utility violation, capacity violation, and running time. We also show that our techniques easily extend to the setting where there are arbitrary covering constraints on the feasible assignment, capturing multi-criteria and ranking optimization.
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Near-feasible Fair Allocations in Two-sided Markets
A general rounding framework yields near-feasible fair allocations with tunable deviations across capacities, demands, and group utilities, with applications to school choice, couples matching, and apportionment.
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