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Seyed Mohammad Azimi-Abarghouyi

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#machine learning Preprint Sep 2026

FedHV: Low-Overhead Hypervolume Weighting for Federated Multi-Objective Optimization

Task-wise federated multi-objective optimization (FedMOO) trains a shared model for competing prediction objectives under heterogeneous data, partial participation, and communication constraints. Existing methods commonly derive task weights from gradient or update geometry. This requires task-specific information or i...

Amirardalan Dehghanpour, Seyed Mohammad Azimi-Abarghouyi, Christopher G. Brinton · 0 citations

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