4 papers · 2 filters
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…
Prediction-Intervention Games and Invariant Sets
Linus Kühne, Felix Schur, Jonas Peters
We consider the following two-player game: using observational data, the leader chooses a prediction function for a response variable from given covariates. The follower then r…
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…
Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?
Felix Schur, Niklas Pfister, Peng Ding +2
We study the problem of estimating causal effects under hidden confounding in the following unpaired data setting: we observe some covariates and an outcome under different…