16 citations · 27 across the 11 of their papers we have counts for
6 papers · 1 filter
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…