mlsanityData to 7 Oct 2026

Two-Sided Matching Meets Fair Division

arXiv 2107.07404 ↗First posted 15 Jul 2021cs.GT cs.AIcited by 5

Not on the map. Why?

Abstract (arXiv)

We introduce a new model for two-sided matching which allows us to borrow popular fairness notions from the fair division literature such as envy-freeness up to one good and maximin share guarantee. In our model, each agent is matched to multiple agents on the other side over whom she has additive preferences. We demand fairness for each side separately, giving rise to notions such as double envy-freeness up to one match (DEF1) and double maximin share guarantee (DMMS). We show that (a slight strengthening of) DEF1 cannot always be achieved, but in the special case where both sides have identical preferences, the round-robin algorithm with a carefully designed agent ordering achieves it. In contrast, DMMS cannot be achieved even when both sides have identical preferences.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 8 of its 32 references that are in the map. First posted on arXiv 15 Jul 2021.

Builds on

8 of 32 references.

References · 8

  1. 2020FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platformscited by 77
  2. 2020Best of Both Worlds: Ex-Ante and Ex-Post Fairness in Resource Allocationcited by 15
  3. 2018Fair Division Under Cardinality Constraintscited by 10
  4. 2020Almost Envy-free Repeated Matching in Two-sided Marketscited by 7
  5. 2020Simultaneously Achieving Ex-ante and Ex-post Fairnesscited by 6
  6. 2019Envy-Freeness in House Allocation Problemscited by 5
  7. 2019Envy-free Matchings in Bipartite Graphs and their Applications to Fair Divisioncited by 4
  8. 2017Envy-free Matchings with Lower Quotascited by 3

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 4.

5 papers.