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cs.LG2025
Adaptive Decentralized Federated Learning for Robust Optimization
Shuyuan Wu, Feifei Wang, Yuan Gao +2
In decentralized federated learning (DFL), the presence of abnormal clients, often caused by noisy or poisoned data, can significantly disrupt the learning process and degrade the…
cs.LG2023
Improved Naive Bayes with Mislabeled Data
Qianhan Zeng, Yingqiu Zhu, Xuening Zhu +5
Labeling mistakes are frequently encountered in real-world applications. If not treated well, the labeling mistakes can deteriorate the classification performances of a model serio…