2 citations · 2 across the 3 of their papers we have counts for
3 papers
CTRL Your Shift: Clustered Transfer Residual Learning for Many Small Datasets
Gauri Jain, Dominik Rothenhäusler, Kirk Bansak +1
Machine learning (ML) tasks often utilize large-scale data that is drawn from several distinct sources, such as different locations, treatment arms, or groups. In such settings, pr…
Optimal Empirical Risk Minimization under Temporal Distribution Shifts
Yujin Jeong, Ramesh Johari, Dominik Rothenhäusler +1
Temporal distribution shifts pose a key challenge for machine learning models trained and deployed in dynamically evolving environments. This paper introduces RIDER (RIsk minimizat…
Learning under random distributional shifts
Kirk Bansak, Elisabeth Paulson, Dominik Rothenhäusler
Many existing approaches for generating predictions in settings with distribution shift model distribution shifts as adversarial or low-rank in suitable representations. In various…