Towards Straggler-Resilient Split Federated Learning: An Unbalanced Update Approach
Fuente:
arXiv
Saved in:
| Main Authors: | Liang, Dandan, Zhang, Jianing, Chen, Evan, Li, Zhe, Li, Rui, Yang, Haibo |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FedCore: Straggler-Free Federated Learning with Distributed Coresets
by: Guo, Hongpeng, et al.
Published: (2024)
by: Guo, Hongpeng, et al.
Published: (2024)
Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates
by: Xiong, Guojun, et al.
Published: (2023)
by: Xiong, Guojun, et al.
Published: (2023)
Gradient Correction in Federated Learning with Adaptive Optimization
by: Chen, Evan, et al.
Published: (2025)
by: Chen, Evan, et al.
Published: (2025)
HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems
by: Lin, Zheng, et al.
Published: (2025)
by: Lin, Zheng, et al.
Published: (2025)
Efficient Federated Learning with Timely Update Dissemination
by: Jia, Juncheng, et al.
Published: (2025)
by: Jia, Juncheng, et al.
Published: (2025)
Federated Multi-Objective Learning
by: Yang, Haibo, et al.
Published: (2023)
by: Yang, Haibo, et al.
Published: (2023)
Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning
by: Chen, Sijia, et al.
Published: (2024)
by: Chen, Sijia, et al.
Published: (2024)
On the Byzantine-Resilience of Distillation-Based Federated Learning
by: Roux, Christophe, et al.
Published: (2024)
by: Roux, Christophe, et al.
Published: (2024)
FedTLU: Federated Learning with Targeted Layer Updates
by: Park, Jong-Ik, et al.
Published: (2024)
by: Park, Jong-Ik, et al.
Published: (2024)
Communication-Efficient and Differentially Private Vertical Federated Learning with Zeroth-Order Optimization
by: Zhang, Jianing, et al.
Published: (2025)
by: Zhang, Jianing, et al.
Published: (2025)
AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks
by: Lin, Zheng, et al.
Published: (2024)
by: Lin, Zheng, et al.
Published: (2024)
Guard: Scalable Straggler Detection and Node Health Management for Large-Scale Training
by: Liu, Guanliang, et al.
Published: (2026)
by: Liu, Guanliang, et al.
Published: (2026)
FedImpro: Measuring and Improving Client Update in Federated Learning
by: Tang, Zhenheng, et al.
Published: (2024)
by: Tang, Zhenheng, et al.
Published: (2024)
A deep cut into Split Federated Self-supervised Learning
by: Przewięźlikowski, Marcin, et al.
Published: (2024)
by: Przewięźlikowski, Marcin, et al.
Published: (2024)
Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable
by: Ying, Bicheng, et al.
Published: (2025)
by: Ying, Bicheng, et al.
Published: (2025)
LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data
by: Zhang, Yuxin, et al.
Published: (2025)
by: Zhang, Yuxin, et al.
Published: (2025)
Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data
by: Liu, Ji, et al.
Published: (2024)
by: Liu, Ji, et al.
Published: (2024)
FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data
by: Zhang, Yuxin, et al.
Published: (2024)
by: Zhang, Yuxin, et al.
Published: (2024)
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
by: Chen, Zihan, et al.
Published: (2025)
by: Chen, Zihan, et al.
Published: (2025)
Collaborative Split Federated Learning with Parallel Training and Aggregation
by: Papageorgiou, Yiannis, et al.
Published: (2025)
by: Papageorgiou, Yiannis, et al.
Published: (2025)
Federated Graph Learning with Structure Proxy Alignment
by: Fu, Xingbo, et al.
Published: (2024)
by: Fu, Xingbo, et al.
Published: (2024)
Hierarchical Split Federated Learning: Convergence Analysis and System Optimization
by: Lin, Zheng, et al.
Published: (2024)
by: Lin, Zheng, et al.
Published: (2024)
FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks
by: Lin, Zheng, et al.
Published: (2023)
by: Lin, Zheng, et al.
Published: (2023)
PubSub-VFL: Towards Efficient Two-Party Split Learning in Heterogeneous Environments via Publisher/Subscriber Architecture
by: Liu, Yi, et al.
Published: (2025)
by: Liu, Yi, et al.
Published: (2025)
A Resource-Adaptive Approach for Federated Learning under Resource-Constrained Environments
by: Zhang, Ruirui, et al.
Published: (2024)
by: Zhang, Ruirui, et al.
Published: (2024)
Stragglers Can Contribute More: Uncertainty-Aware Distillation for Asynchronous Federated Learning
by: Wang, Yujia, et al.
Published: (2025)
by: Wang, Yujia, et al.
Published: (2025)
Lightweight Federated Learning with Differential Privacy and Straggler Resilience
by: Hong, Shu, et al.
Published: (2024)
by: Hong, Shu, et al.
Published: (2024)
CommunityAI: Towards Community-based Federated Learning
by: Murturi, Ilir, et al.
Published: (2023)
by: Murturi, Ilir, et al.
Published: (2023)
SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework
by: Zhang, Yuxin, et al.
Published: (2024)
by: Zhang, Yuxin, et al.
Published: (2024)
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
by: Zhuang, Weiming, et al.
Published: (2023)
by: Zhuang, Weiming, et al.
Published: (2023)
DFML: Decentralized Federated Mutual Learning
by: Khalil, Yasser H., et al.
Published: (2024)
by: Khalil, Yasser H., et al.
Published: (2024)
Incentivizing Multi-Tenant Split Federated Learning for Foundation Models at the Network Edge
by: Li, Songyuan, et al.
Published: (2025)
by: Li, Songyuan, et al.
Published: (2025)
Parallel Split Learning with Global Sampling
by: Kohankhaki, Mohammad, et al.
Published: (2024)
by: Kohankhaki, Mohammad, et al.
Published: (2024)
StreamSplit: Continuous Audio Representation Learning via Uncertainty-Guided Adaptive Splitting
by: Quan, Minh K., et al.
Published: (2026)
by: Quan, Minh K., et al.
Published: (2026)
P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices
by: Fan, Wei, et al.
Published: (2025)
by: Fan, Wei, et al.
Published: (2025)
Towards One-shot Federated Learning: Advances, Challenges, and Future Directions
by: Amato, Flora, et al.
Published: (2025)
by: Amato, Flora, et al.
Published: (2025)
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
by: Li, Zhe, et al.
Published: (2024)
by: Li, Zhe, et al.
Published: (2024)
HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models
by: Lin, Zheng, et al.
Published: (2025)
by: Lin, Zheng, et al.
Published: (2025)
CG-FedLLM: How to Compress Gradients in Federated Fune-tuning for Large Language Models
by: Wu, Huiwen, et al.
Published: (2024)
by: Wu, Huiwen, et al.
Published: (2024)
PNCS:Power-Norm Cosine Similarity for Diverse Client Selection in Federated Learning
by: Li, Liangyan, et al.
Published: (2025)
by: Li, Liangyan, et al.
Published: (2025)
Similar Items
-
FedCore: Straggler-Free Federated Learning with Distributed Coresets
by: Guo, Hongpeng, et al.
Published: (2024) -
Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates
by: Xiong, Guojun, et al.
Published: (2023) -
Gradient Correction in Federated Learning with Adaptive Optimization
by: Chen, Evan, et al.
Published: (2025) -
HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems
by: Lin, Zheng, et al.
Published: (2025) -
Efficient Federated Learning with Timely Update Dissemination
by: Jia, Juncheng, et al.
Published: (2025)