1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Learning the Pareto Frontier of Predictive Models under Distribution Shift
Yiming Dong, Jiwei Zhao, Yang Young Lu
Modern machine learning pipelines increasingly rely on reusing pretrained and foundation models across downstream tasks. These pretrained models can differ not only in performance…
stat.ML2024★ 1 cited
ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift
Hwanwoo Kim, Xin Zhang, Jiwei Zhao +1
The presence of distribution shifts poses a significant challenge for deploying modern machine learning models in real-world applications. This work focuses on the target shift pro…
stat.ML2023★ 1 cited
ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models
Qinglong Tian, Xin Zhang, Jiwei Zhao
We study the domain adaptation problem with label shift in this work. Under the label shift context, the marginal distribution of the label varies across the training and testing d…