14 citations · 14 across the 7 of their papers we have counts for
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cs.LG2023
SFP: Spurious Feature-targeted Pruning for Out-of-Distribution Generalization
Yingchun Wang, Jingcai Guo, Yi Liu +4
Model substructure learning aims to find an invariant network substructure that can have better out-of-distribution (OOD) generalization than the original full structure. Existing…
cs.LG2023
Towards Fairer and More Efficient Federated Learning via Multidimensional Personalized Edge Models
Yingchun Wang, Jingcai Guo, Jie Zhang +3
Federated learning (FL) is an emerging technique that trains massive and geographically distributed edge data while maintaining privacy. However, FL has inherent challenges in term…
cs.LG2022
Exploring Optimal Substructure for Out-of-distribution Generalization via Feature-targeted Model Pruning
Yingchun Wang, Jingcai Guo, Song Guo +2
Recent studies show that even highly biased dense networks contain an unbiased substructure that can achieve better out-of-distribution (OOD) generalization than the original model…