IEEE

Robust Federated Learning Client Selection With Combinatorial Class Representations and Data Augmentation

Abstract: The federated learning (FL) client selection scheme can effectively mitigate global model performance degradation caused by the random aggregation of clients with heterogeneous data.
IEEE

Multi-Class Imbalance Classification Based on Data Distribution and Adaptive Weights

Abstract: AdaBoost approaches have been used for multi-class imbalance classification with an imbalance ratio measured on class sizes. However, such ratio would assign each training sample of the same ...