Data Valuation and Detections in Federated Learning
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 which is …
of raw data. A challenge in this framework is the fair and efficient valuation of data which is …
Private Wasserstein Distance with Random Noises
W Li, H Wang, Z Huang, Y Pang - arXiv preprint arXiv:2404.06787, 2024 - arxiv.org
Wasserstein distance is a principle measure of data divergence from a distributional
standpoint. However, its application becomes challenging in the context of data privacy …
standpoint. However, its application becomes challenging in the context of data privacy …
An Overview of Data Contribution Evaluation Methods for Federated Learning
C Ding, M Zhang - Academic Journal of Science and Technology, 2024 - drpress.org
With the rapid development of artificial intelligence, especially machine learning technology,
the demand for data is also increasing. As a distributed learning method, federated learning …
the demand for data is also increasing. As a distributed learning method, federated learning …