3 papers
cs.GT2024
Low-Distortion Clustering with Ordinal and Limited Cardinal Information
Jakob Burkhardt, Ioannis Caragiannis, Karl Fehrs +3
Motivated by recent work in computational social choice, we extend the metric distortion framework to clustering problems. Given a set of agents located in an underlying metric…
cs.GT2023
Beyond the worst case: Distortion in impartial culture electorates
Ioannis Caragiannis, Karl Fehrs
{\em Distortion} is a well-established notion for quantifying the loss of social welfare that may occur in voting. As voting rules take as input only ordinal information, they are…
cs.GT2021
The Complexity of Learning Approval-Based Multiwinner Voting Rules
Ioannis Caragiannis, Karl Fehrs
We study the {PAC} learnability of multiwinner voting, focusing on the class of approval-based committee scoring (ABCS) rules. These are voting rules applied on profiles with appro…