AINeutralarXiv – CS AI · 9h ago6/10
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UMEDA: Unified Multi-modal Efficient Data Fusion for Privacy-Preserving Graph Federated Learning via Spectral-Gated Attention and Diffusion-Based Operator Alignment
Researchers introduce UMEDA, a federated learning framework designed to enable device-free localization across heterogeneous sensors while maintaining privacy. The system uses spectral signal processing and diffusion-based aggregation to align data from different sensor modalities without requiring direct node correspondence, achieving superior performance on multi-modal benchmarks under privacy constraints.