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stat.ME2025
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…
stat.ME2024
Out-of-distribution generalization under random, dense distributional shifts
Yujin Jeong, Dominik Rothenhäusler
Many existing approaches for estimating parameters in settings with distributional shifts operate under an invariance assumption. For example, under covariate shift, it is assumed…
stat.ME2024
Identifying sparse treatment effects in high-dimensional outcome spaces
Yujin Jeong, Emily Fox, Ramesh Johari
Based on technological advances in sensing modalities, randomized trials with primary outcomes represented as high-dimensional vectors have become increasingly prevalent. For examp…