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cs.LG2025
Private Wasserstein Distance
Wenqian Li, Yan Pang
Wasserstein distance is a key metric for quantifying data divergence from a distributional perspective. However, its application in privacy-sensitive environments, where direct sha…
cs.LG2024
Data Valuation and Detections in Federated Learning
Wenqian Li, Shuran Fu, Fengrui Zhang +1
Federated Learning (FL) enables collaborative model training while preserving the privacy of raw data. A challenge in this framework is the fair and efficient valuation of data, wh…