2 papers
econ.TH2024
Wisdom and Foolishness of Noisy Matching Markets
Kenny Peng, Nikhil Garg
We consider a many-to-one matching market where colleges share true preferences over students but make decisions using only independent noisy rankings. Each student has a true valu…
cs.IR2023
Interface Design to Mitigate Inflation in Recommender Systems
Rana Shahout, Yehonatan Peisakhovsky, Sasha Stoikov +1
Recommendation systems rely on user-provided data to learn about item quality and provide personalized recommendations. An implicit assumption when aggregating ratings into item qu…