HO-SFL: Hybrid-Order Split Federated Learning with Backprop-Free Clients and Dimension-Free Aggregation
cs.LG, cs.AI
Submitted: 2026-03-16
Updated: 2026-09-27
Code: https://github.com/HKU-WILL-Lab/HO-SFL
Terminology
Sources
- Training Deep Nets with Sublinear Memory Cost
- The Llama 3 Herd of Models
- Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
- SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models
- Gemma 3 Technical Report
- Split learning for health: Distributed deep learning without sharing raw patient data
- Qwen3 Technical Report
- OPT: Open Pre-trained Transformer Language Models
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