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stat.ML2024★ 1 cited
Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees
Xin Yu, Zelin He, Ying Sun +2
Personalized federated learning (PFL) offers a flexible framework for aggregating information across distributed clients with heterogeneous data. This work considers a personalized…
stat.ML2024★ 2 cited
TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression
Zelin He, Ying Sun, Jingyuan Liu +1
The main challenge that sets transfer learning apart from traditional supervised learning is the distribution shift, reflected as the shift between the source and target models and…
stat.ML2024★ 1 cited
AdaTrans: Feature-wise and Sample-wise Adaptive Transfer Learning for High-dimensional Regression
Zelin He, Ying Sun, Jingyuan Liu +1
We consider the transfer learning problem in the high dimensional linear regression setting, where the feature dimension is larger than the sample size. To learn transferable infor…