Author

James R. Foulds

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Book Open access Sep 2026

When Fairness Metrics Help Each Other: Look-Ahead Optimization for Multi-Metric Fairness Weighting

Fairness-aware machine learning depends crucially on the fairness criterion chosen, and it is well understood that these criteria are often in conflict with each other. In this work, we challenge this conventional wisdom by exploring how competing fairness criteria may in some cases interact in helpful ways. We investi...

Munshi Mahbubur Rahman, Shi-Mei Pan, J. Foulds · 0 citations

DP-EM: Diﬀerentially Private Expectation Maximization

A practical private EM algorithm that overcomes this challenge by using a novel moment perturbation formulation for diﬀerentially private EM (DP-EM), and the use of two recently developed composition methods to bound the privacy “cost” of multiple EM iterations: the moments accountant (MA) and zero-mean concentrated di...

Mijung Park, James R. Foulds, Kamalika Chaudhuri et al. · 0 citations