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Federated learning for generalization, robustness, fairness: A survey and benchmark
W Huang, M Ye, Z Shi, G Wan, H Li… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Federated learning has emerged as a promising paradigm for privacy-preserving
collaboration among different parties. Recently, with the popularity of federated learning, an …
collaboration among different parties. Recently, with the popularity of federated learning, an …
Domain generalization for medical image analysis: A survey
JS Yoon, K Oh, Y Shin, MA Mazurowski… - ar** robust artificial intelligence (AI) models that generalize well to unseen datasets
is challenging and usually requires large and variable datasets, preferably from multiple …
is challenging and usually requires large and variable datasets, preferably from multiple …
Enhancing one-shot federated learning through data and ensemble co-boosting
One-shot Federated Learning (OFL) has become a promising learning paradigm, enabling
the training of a global server model via a single communication round. In OFL, the server …
the training of a global server model via a single communication round. In OFL, the server …