
TL;DR
This paper investigates the problem of assigning jobs to applicants with preferences and weights, introducing efficient algorithms to find popular matchings where no alternative matching is preferred by a higher weighted group.
Contribution
It provides the first efficient algorithms for finding popular matchings in weighted applicant-job assignment problems.
Findings
Algorithms efficiently find popular matchings when they exist.
Characterization of conditions under which popular matchings are possible.
Improved understanding of weighted preference-based matchings.
Abstract
We study the problem of assigning jobs to applicants. Each applicant has a weight and provides a preference list ranking a subset of the jobs. A matching M is popular if there is no other matching M' such that the weight of the applicants who prefer M' over M exceeds the weight of those who prefer M over M'. This paper gives efficient algorithms to find a popular matching if one exists.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
