10 citations · 10 across the 5 of their papers we have counts for
5 papers
The Art of Calling the Winner by Asking Just Enough Questions: Competitive Preference Elicitation with Next-Best Queries
Nisarg Shah, Ziqi Yu
We study active elicitation of agent preferences for collectively choosing among alternatives using prominent voting rules. We focus on the next-best query model, in which an a…
Unifying Proportional Fairness in Centroid and Non-Centroid Clustering
Benjamin Cookson, Nisarg Shah, Ziqi Yu
Proportional fairness criteria inspired by democratic ideals of proportional representation have received growing attention in the clustering literature. Prior work has investigate…
Multi-Agent Risks from Advanced AI
Lewis Hammond, Alan Chan, Jesse Clifton +41
The rapid development of advanced AI agents and the imminent deployment of many instances of these agents will give rise to multi-agent systems of unprecedented complexity. These s…
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…
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…