NeurIPS 2023poster4 citations
The Distortion of Binomial Voting Defies Expectation
Yannai Gonczarowski, Gregory Kehne, Ariel D. Procaccia, Ben Schiffer, Shirley Zhang
Abstract
In computational social choice, the distortion of a voting rule quantifies the degree to which the rule overcomes limited preference information to select a socially desirable outcome. This concept has been investigated extensively, but only through a worst-case lens. Instead, we study the expected distortion of voting rules with respect to an underlying distribution over voter utilities. Our main contribution is the design and analysis of a novel and intuitive rule, binomial voting, which provides strong distribution-independent guarantees for both expected distortion and expected welfare.
computational social choicestatisticsdistortion
BibTeX
@inproceedings{
gonczarowski2023the,
title={The Distortion of Binomial Voting Defies Expectation},
author={Yannai Gonczarowski and Gregory Kehne and Ariel D. Procaccia and Ben Schiffer and Shirley Zhang},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023},
url={https://openreview.net/forum?id=Sv5bo2StIx}
}