2 citations · 2 across the 4 of their papers we have counts for
4 papers
MAFE: Enabling Equitable Algorithm Design in Multi-Agent Multi-Stage Decision-Making Systems
Zachary McBride Lazri, Anirudh Nakra, Ivan Brugere +5
Algorithmic fairness is often studied in static or single-agent settings, yet many real-world decision-making systems involve multiple interacting entities whose multi-stage action…
Balancing Fairness and Accuracy in Data-Restricted Binary Classification
Zachary McBride Lazri, Danial Dervovic, Antigoni Polychroniadou +3
Applications that deal with sensitive information may have restrictions placed on the data available to a machine learning (ML) classifier. For example, in some applications, a cla…
Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data
Yvonne Zhou, Mingyu Liang, Ivan Brugere +4
The growing use of machine learning (ML) has raised concerns that an ML model may reveal private information about an individual who has contributed to the training dataset. To pre…
A Canonical Data Transformation for Achieving Inter- and Within-group Fairness
Zachary McBride Lazri, Ivan Brugere, Xin Tian +4
Increases in the deployment of machine learning algorithms for applications that deal with sensitive data have brought attention to the issue of fairness in machine learning. Many…