16 citations · 27 across the 11 of their papers we have counts for
13 papers
Metric Distortion of Social Welfare Functions
Fatih Erdem Kizilkaya, Aaryaman Aggarwal, Evi Micha
Metric distortion has primarily been studied for social choice functions, which select a single winner from ordinal preferences. We extend this framework to social welfare function…
Learning Fair Allocation of Indivisible Items from Limited Feedback
Xinyu Liu, David Kempe, Evi Micha
We study a setting in which an algorithm must output a fair allocation of indivisible items while "learning on the job". More specifically, the algorithm is to output an allocation…
Proportional Fairness in Non-Centroid Clustering
Ioannis Caragiannis, Evi Micha, Nisarg Shah
We revisit the recently developed framework of proportionally fair clustering, where the goal is to provide group fairness guarantees that become stronger for groups of data points…
Group Fairness in Peer Review
Haris Aziz, Evi Micha, Nisarg Shah
Large conferences such as NeurIPS and AAAI serve as crossroads of various AI fields, since they attract submissions from a vast number of communities. However, in some cases, this…
Strategic Classification With Externalities
Safwan Hossain, Evi Micha, Yiling Chen +1
We propose a new variant of the strategic classification problem: a principal reveals a classifier, and agents report their (possibly manipulated) features to be classified. Mo…
Can a Few Decide for Many? The Metric Distortion of Sortition
Ioannis Caragiannis, Evi Micha, Jannik Peters
Recent works have studied the design of algorithms for selecting representative sortition panels. However, the most central question remains unaddressed: Do these panels reflect th…
Boosting Sortition via Proportional Representation
Soroush Ebadian, Evi Micha
Sortition is based on the idea of choosing randomly selected representatives for decision making. The main properties that make sortition particularly appealing are fairness -- all…
What is Best for Students, Numerical Scores or Letter Grades?
Evi Micha, Shreyas Sekar, Nisarg Shah
We study letter grading schemes, which are routinely employed for evaluating student performance. Typically, a numerical score obtained via one or more evaluations is converted int…
Proportionally Fair Online Allocation of Public Goods with Predictions
Siddhartha Banerjee, Vasilis Gkatzelis, Safwan Hossain +3
We design online algorithms for the fair allocation of public goods to a set of agents over a sequence of rounds and focus on improving their performance using predictions.…
Individual Representation in Approval-Based Committee Voting
Markus Brill, Jonas Israel, Evi Micha +1
When selecting multiple candidates based on approval preferences of agents, the proportional representation of agents' opinions is an important and well-studied desideratum. Existi…
Two-Sided Matching Meets Fair Division
Rupert Freeman, Evi Micha, Nisarg Shah
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 maximi…
Fair Algorithms for Multi-Agent Multi-Armed Bandits
Safwan Hossain, Evi Micha, Nisarg Shah
We propose a multi-agent variant of the classical multi-armed bandit problem, in which there are agents and arms, and pulling an arm generates a (possibly different) stocha…
The distortion of distributed voting
Aris Filos-Ratsikas, Evi Micha, Alexandros A. Voudouris
Voting can abstractly model any decision-making scenario and as such it has been extensively studied over the decades. Recently, the related literature has focused on quantifying t…