3 papers
stat.ML2025
Lower Bounds on the MMSE of Adversarially Inferring Sensitive Features
Monica Welfert, Nathan Stromberg, Mario Diaz +1
We propose an adversarial evaluation framework for sensitive feature inference based on minimum mean-squared error (MMSE) estimation with a finite sample size and linear predictive…
cs.LG2024
Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest Neighbors Label Spreading
Nathan Stromberg, Rohan Ayyagari, Sanmi Koyejo +2
Last-layer retraining methods have emerged as an efficient framework for correcting existing base models. Within this framework, several methods have been proposed to deal with cor…
cs.LG2023
Smoothly Giving up: Robustness for Simple Models
Tyler Sypherd, Nathan Stromberg, Richard Nock +2
There is a growing need for models that are interpretable and have reduced energy and computational cost (e.g., in health care analytics and federated learning). Examples of algori…