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FDG
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Paper Name
Categories
Type
Recent issues
Target
Motivations
Contributions
Evaluation List
Conf./Jour.
Year
Link
Paper Name
Categories
Type
Recent issues
Target
Motivations
Contributions
Evaluation List
Conf./Jour.
Year
Link
1
Generalized Federated Learning via Sharpness Aware Minimization
Loss Function Design
Theoretical
General task
FDG
Usually take ERM → easily to get trapped into sharp minimizers.
Minimize over loss f.
Hyper-parameters.
Visualize loss-surface
Non-IID level
ICML
2022
2
Federated Domain Generalization with Generalization Adjustment.
Loss Function Design
Optimizer
FDG
General task
Theoretical
Different step-sizes + linear decay strategy.
Domain generalization gaps (Mean/Variance Gaps).
Visualize loss surface
3
Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning.
Data Augmentation
Domain-invariant features
Self-supervised Learning
Engineering
FDG
General task
4
StableFDG: Style and Attention Based Learning for Federated Domain Generalization
Mixing
Lack of data and style.
Style-based Learning → Style information.
Share style information with other clients.
AdaIN → MixStyle → Feature level style sampling
(Why get style = Gaussian is legit?).
5
DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning
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