2 papers
cs.LG2025
An Effective Theory of Bias Amplification
Arjun Subramonian, Samuel J. Bell, Levent Sagun +1
Machine learning models can capture and amplify biases present in data, leading to disparate test performance across social groups. To better understand, evaluate, and mitigate the…
stat.ML2025
A Differentiable Rank-Based Objective For Better Feature Learning
Krunoslav Lehman Pavasovic, David Lopez-Paz, Giulio Biroli +1
In this paper, we leverage existing statistical methods to better understand feature learning from data. We tackle this by modifying the model-free variable selection method, Featu…