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What and Who

Near-feasible Fair Allocations in Two-sided Markets

Javier Cembrano
Max-Planck-Institut für Informatik - D1
AG1 Mittagsseminar (own work)
AG 1  
AG Audience
English

Date, Time and Location

Thursday, 3 July 2025
13:00
30 Minutes
E1 4
024
Saarbrücken

Abstract

We study resource allocation in two-sided markets from a fundamental perspective and introduce a general modeling and algorithmic framework to effectively incorporate the complex and multidimensional aspects of fairness. Our main technical contribution is to show the existence of a range of near-feasible resource allocations parameterized in different model primitives to give flexibility when balancing the different policymaking requirements, allowing policy designers to fix these values according to the specific application. To construct our near-feasible allocations, we start from a fractional resource allocation and perform an iterative rounding procedure to get an integer allocation. We show a simple yet flexible and strong sufficient condition for the target feasibility deviations to guarantee that the rounding procedure succeeds, exhibiting the underlying trade-offs between market capacities, agents' demand, and fairness. To showcase our framework's modeling and algorithmic capabilities, we consider three prominent market design problems: school allocation, stable matching with couples, and political apportionment. In each of them, we obtain strengthened guarantees on the existence of near-feasible allocations capturing the corresponding fairness notions, such as proportionality, envy-freeness, and stability.


This is joint work with Andrés Moraga and Victor Verdugo. To appear in EC'25.

Contact

Nidhi Rathi
+49 681 9325 1134
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Virtual Meeting Details

Zoom
897 027 2575
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Nidhi Rathi, 06/18/2025 13:59
Nidhi Rathi, 06/18/2025 13:56 -- Created document.