3 papers
stat.ML2026
Anchor PCA
Benedikt Seiter, Anya Fries, Julius von Kügelgen +1
Principal component analysis (PCA) is one of the most widely used unsupervised dimension reduction techniques. We study PCA for data from multiple related domains. Since principal…
stat.ML2026
Worst-case low-rank approximations
Anya Fries, Markus Reichstein, David Blei +1
Real-world data in health, economics, and environmental sciences are often collected across heterogeneous domains (such as hospitals, regions, or time periods). In such settings, d…
stat.ML2025
Maximum Risk Minimization with Random Forests
Francesco Freni, Anya Fries, Linus Kühne +2
We consider a regression setting where observations are collected in different environments modeled by different data distributions. The field of out-of-distribution (OOD) generali…