Resource-Aware Federated Mixture-of-Experts with Adaptive Pruning for Onboard Learning in LEO Satellite Constellations
cs.LG, cs.CV
Submitted: 2026-09-25
Updated: 2026-09-25
Terminology
Sources
- Expanding the Reach of Federated Learning by Reducing Client Resource Requirements
- HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
- Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
- On the Convergence of FedAvg on Non-IID Data
- Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
- Mixture of Experts in Image Classification: What's the Sweet Spot?
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