I Will Have Order! Optimizing Orders for Fair Reviewer Assignment

Abstract

We study mechanisms that allocate reviewers to papers in a fair and efficient manner. We model reviewer assignment as an instance of a fair allocation problem, presenting an extension of the classic round-robin mechanism, called Reviewer Round Robin (RRR). Round-robin mechanisms are a standard tool to ensure envy-free up to one item (EF1) allocations. However, fairness often comes at the cost of decreased efficiency. To overcome this challenge, we carefully select an approximately optimal round-robin order. Applying a relaxation of submodularity, γ-weak submodularity, we show that greedily inserting papers into an order yields a (1+γ²)-approximation to the maximum welfare attainable by our round-robin mechanism under any order. Our Greedy Reviewer Round Robin (GRRR) approach outputs highly efficient EF1 allocations for three real conference datasets, offering comparable performance to state-of-the-art paper assignment methods in fairness, efficiency, and runtime, while providing the only EF1 guarantee.

Cite

Text

Payan and Zick. "I Will Have Order! Optimizing Orders for Fair Reviewer Assignment." International Joint Conference on Artificial Intelligence, 2022. doi:10.24963/IJCAI.2022/63

Markdown

[Payan and Zick. "I Will Have Order! Optimizing Orders for Fair Reviewer Assignment." International Joint Conference on Artificial Intelligence, 2022.](https://mlanthology.org/ijcai/2022/payan2022ijcai-i/) doi:10.24963/IJCAI.2022/63

BibTeX

@inproceedings{payan2022ijcai-i,
  title     = {{I Will Have Order! Optimizing Orders for Fair Reviewer Assignment}},
  author    = {Payan, Justin and Zick, Yair},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {440-446},
  doi       = {10.24963/IJCAI.2022/63},
  url       = {https://mlanthology.org/ijcai/2022/payan2022ijcai-i/}
}