Sankar, GS and Louis, A and Nasre, M and Nimbhorkar, P (2021) Matchings with Group Fairness Constraints: Online and Offline Algorithms. In: 30th International Joint Conference on Artificial Intelligence, IJCAI 2021, 19-27 Aug 2021, Virtual, Online, pp. 377-383.
Full text not available from this repository.Abstract
We consider the problem of assigning items to platforms in the presence of group fairness constraints. In the input, each item belongs to certain categories, called classes in this paper. Each platform specifies the group fairness constraints through an upper bound on the number of items it can serve from each class. Additionally, each platform also has an upper bound on the total number of items it can serve. The goal is to assign items to platforms so as to maximize the number of items assigned while satisfying the upper bounds of each class. This problem models several important real-world problems like ad-auctions, scheduling, resource allocations, school choice etc. We show that if the classes are arbitrary, then the problem is NP-hard and has a strong inapproximability. We consider the problem in both online and offline settings under natural restrictions on the classes. Under these restrictions, the problem continues to remain NP-hard but admits approximation algorithms with small approximation factors. We also implement some of the algorithms. Our experiments show that the algorithms work well in practice both in terms of efficiency and the number of items that get assigned to some platform. © 2021 International Joint Conferences on Artificial Intelligence. All rights reserved.
| Item Type: | Conference Paper |
|---|---|
| Publication: | IJCAI International Joint Conference on Artificial Intelligence |
| Publisher: | International Joint Conferences on Artificial Intelligence |
| Additional Information: | The copyright for this article belongs to International Joint Conferences on Artifical Intelligence (IJCAI) |
| Keywords: | Artificial intelligence, Ad auctions; Fairness constraints; Matchings; NP-hard; Off-line algorithm; On-line algorithms; Problem models; Real-world problem; Scheduling resources; Upper Bound, Approximation algorithms |
| Department/Centre: | Division of Electrical Sciences > Computer Science & Automation |
| Date Deposited: | 18 Mar 2022 11:58 |
| Last Modified: | 18 Mar 2022 11:58 |
| URI: | http://eprints.iisc.ac.in/id/eprint/71604 |
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