Importance-Aware Feature Sparsification for Wireless Split Learning
cs.LG, eess.SP
Submitted: 2026-09-30
Updated: 2026-09-30
Sources
- Split learning for health: Distributed deep learning without sharing raw patient data
- FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients
- Convergence Analysis of Sequential Split Learning on Heterogeneous Data
- Two Stage Wireless Federated LoRA Fine-Tuning with Sparsified Orthogonal Updates
- Federated Learning Enhanced by Feature Reconstruction for Semantic Communication Module Updates of Agents
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