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cs.LG2025★ 1 cited
Uncertainty-Aware Generative Oversampling Using an Entropy-Guided Conditional Variational Autoencoder
Amirhossein Zare, Amirhessam Zare, Parmida Sadat Pezeshki +5
Class imbalance remains a major challenge in machine learning, especially for high-dimensional biomedical data where nonlinear manifold structures dominate. Traditional oversamplin…
cs.LG2025
FedAVOT: Exact Distribution Alignment in Federated Learning via Masked Optimal Transport
Herlock, Rahimi, Dionysis Kalogerias
Federated Learning (FL) allows distributed model training without sharing raw data, but suffers when client participation is partial. In practice, the distribution of available use…
cs.LG2025
Convergence of Agnostic Federated Averaging
Herlock, Rahimi, Dionysis Kalogerias
Federated learning (FL) enables decentralized model training without centralizing raw data. However, practical FL deployments often face a key realistic challenge: Clients particip…