4 citations · 7 across the 6 of their papers we have counts for
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cs.LG2025
Shadow defense against gradient inversion attack in federated learning
Le Jiang, Liyan Ma, Guang Yang
Federated learning (FL) has emerged as a transformative framework for privacy-preserving distributed training, allowing clients to collaboratively train a global model without shar…
cs.LG2024★ 1 cited
Advancing oncology with federated learning: transcending boundaries in breast, lung, and prostate cancer. A systematic review
Anshu Ankolekar, Sebastian Boie, Maryam Abdollahyan +11
Federated Learning (FL) has emerged as a promising solution to address the limitations of centralised machine learning (ML) in oncology, particularly in overcoming privacy concerns…