3 papers
cs.LG2026
Towards a Fairer Non-negative Matrix Factorization
Lara Kassab, Erin George, Deanna Needell +3
There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is clearly no one-size-fits-all solution to fairness, ML methods s…
cs.LG2025
Observational Multiplicity
Erin George, Deanna Needell, Berk Ustun
Many prediction tasks can admit multiple models that can perform almost equally well. This phenomenon can can undermine interpretability and safety when competing models assign con…
cs.LG2024
Benign overfitting in leaky ReLU networks with moderate input dimension
Kedar Karhadkar, Erin George, Michael Murray +2
The problem of benign overfitting asks whether it is possible for a model to perfectly fit noisy training data and still generalize well. We study benign overfitting in two-layer l…