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【EP11】Improving Robustness to Distribution Shifts: Methods and Benchmarks
Data Distribution Shifts in ML: How to Monitor & Adapt Your Models for Real-World Changes 🔄
[CVPR2026] Fed-ADE: Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift
Machine Learning (ML) Model Adaptation and Concept Drift Detection
24. Robustness to Dataset Shift
Domain Adaptation
Machine Learning and Adaptation
Jiwei Zhao: Estimation and Inference in Unsupervised Domain Adaptation
Data+Shift: Supporting Visual Investigation of Data Distribution Shifts by Data Scientists
MedAI #47: Actionable Machine Learning for Tackling Distribution Shift | Huaxiu Yao
Shifts Challenge | Adapting to Novel Data Distributions | Kate Saenko
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Last Updated: August 18, 2026
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![[CVPR2026] Fed-ADE: Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift](https://i.ytimg.com/vi/o-HuMUdNha8/mqdefault.jpg)
