Assistant Professor, Massachusetts Institute of Technology
2 papers at NeurIPS 2025
We propose a new evaluation method that makes use of three sources of information (unlabeled data, multiple classifiers, and probabilistic classifier scores) to produce more accurate performance estimates than prior work.
Correlated algorithms can reduce competition and result in higher prices, posing antitrust implications
