Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning
Fuente:
arXiv
Guardado en:
| Autores principales: | Wang, Jiaqi, Zhao, Chenxu, Lyu, Lingjuan, You, Quanzeng, Huai, Mengdi, Ma, Fenglong |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis
por: Wang, Jiaqi, et al.
Publicado: (2024)
por: Wang, Jiaqi, et al.
Publicado: (2024)
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
por: Che, Liwei, et al.
Publicado: (2024)
por: Che, Liwei, et al.
Publicado: (2024)
Stragglers Can Contribute More: Uncertainty-Aware Distillation for Asynchronous Federated Learning
por: Wang, Yujia, et al.
Publicado: (2025)
por: Wang, Yujia, et al.
Publicado: (2025)
Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation
por: Wang, Jiaqi, et al.
Publicado: (2024)
por: Wang, Jiaqi, et al.
Publicado: (2024)
Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping
por: Fan, Ziqing, et al.
Publicado: (2024)
por: Fan, Ziqing, et al.
Publicado: (2024)
Bridging Memory Gaps: Scaling Federated Learning for Heterogeneous Clients
por: Wu, Yebo, et al.
Publicado: (2024)
por: Wu, Yebo, et al.
Publicado: (2024)
Breaking the Capacity Bottleneck in Model-Heterogeneous Federated Learning via Gradual Model Restoration
por: Ma, Chengjie, et al.
Publicado: (2025)
por: Ma, Chengjie, et al.
Publicado: (2025)
FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
por: Wang, Ziyao, et al.
Publicado: (2024)
por: Wang, Ziyao, et al.
Publicado: (2024)
Heterogeneity-Aware Memory Efficient Federated Learning via Progressive Layer Freezing
por: Yebo, Wu, et al.
Publicado: (2024)
por: Yebo, Wu, et al.
Publicado: (2024)
Exploring System-Heterogeneous Federated Learning with Dynamic Model Selection
por: Yao, Dixi
Publicado: (2024)
por: Yao, Dixi
Publicado: (2024)
FedMef: Towards Memory-efficient Federated Dynamic Pruning
por: Huang, Hong, et al.
Publicado: (2024)
por: Huang, Hong, et al.
Publicado: (2024)
Federated Learning as a Service for Hierarchical Edge Networks with Heterogeneous Models
por: Gao, Wentao, et al.
Publicado: (2024)
por: Gao, Wentao, et al.
Publicado: (2024)
Reducing Communication for Split Learning by Randomized Top-k Sparsification
por: Zheng, Fei, et al.
Publicado: (2023)
por: Zheng, Fei, et al.
Publicado: (2023)
Data Heterogeneity-Aware Client Selection for Federated Learning in Wireless Networks
por: Yang, Yanbing, et al.
Publicado: (2025)
por: Yang, Yanbing, et al.
Publicado: (2025)
COALA: A Practical and Vision-Centric Federated Learning Platform
por: Zhuang, Weiming, et al.
Publicado: (2024)
por: Zhuang, Weiming, et al.
Publicado: (2024)
Managing Federated Learning on Decentralized Infrastructures as a Reputation-based Collaborative Workflow
por: Wang, Yuandou, et al.
Publicado: (2025)
por: Wang, Yuandou, et al.
Publicado: (2025)
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
por: Zhuang, Weiming, et al.
Publicado: (2023)
por: Zhuang, Weiming, et al.
Publicado: (2023)
ALANINE: A Novel Decentralized Personalized Federated Learning For Heterogeneous LEO Satellite Constellation
por: Zhao, Liang, et al.
Publicado: (2024)
por: Zhao, Liang, et al.
Publicado: (2024)
Analysis and Optimization of Wireless Multimodal Federated Learning on Modal Heterogeneity
por: Han, Xuefeng, et al.
Publicado: (2025)
por: Han, Xuefeng, et al.
Publicado: (2025)
Hypernetworks for Model-Heterogeneous Personalized Federated Learning
por: Zhang, Chen, et al.
Publicado: (2025)
por: Zhang, Chen, et al.
Publicado: (2025)
Federated Model Heterogeneous Matryoshka Representation Learning
por: Yi, Liping, et al.
Publicado: (2024)
por: Yi, Liping, et al.
Publicado: (2024)
FlexFL: Heterogeneous Federated Learning via APoZ-Guided Flexible Pruning in Uncertain Scenarios
por: Chen, Zekai, et al.
Publicado: (2024)
por: Chen, Zekai, et al.
Publicado: (2024)
FedWon: Triumphing Multi-domain Federated Learning Without Normalization
por: Zhuang, Weiming, et al.
Publicado: (2023)
por: Zhuang, Weiming, et al.
Publicado: (2023)
DFPL: Decentralized Federated Prototype Learning Across Heterogeneous Data Distributions
por: Zhang, Hongliang, et al.
Publicado: (2025)
por: Zhang, Hongliang, et al.
Publicado: (2025)
Personalized Federated Learning on Data with Dynamic Heterogeneity under Limited Storage
por: Tan, Sixing, et al.
Publicado: (2024)
por: Tan, Sixing, et al.
Publicado: (2024)
Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting
por: Tian, Chunlin, et al.
Publicado: (2024)
por: Tian, Chunlin, et al.
Publicado: (2024)
BFLN: A Blockchain-based Federated Learning Model for Non-IID Data
por: Li, Yang, et al.
Publicado: (2024)
por: Li, Yang, et al.
Publicado: (2024)
HLoRA: Efficient Federated Learning System for LLM Heterogeneous Fine-Tuning
por: Liu, Qianli, et al.
Publicado: (2025)
por: Liu, Qianli, et al.
Publicado: (2025)
Federated Learning within Global Energy Budget over Heterogeneous Edge Accelerators
por: Banerjee, Roopkatha, et al.
Publicado: (2025)
por: Banerjee, Roopkatha, et al.
Publicado: (2025)
Knowledge-Driven Federated Graph Learning on Model Heterogeneity
por: Wu, Zhengyu, et al.
Publicado: (2025)
por: Wu, Zhengyu, et al.
Publicado: (2025)
Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge Networks
por: Wang, Shuai, et al.
Publicado: (2025)
por: Wang, Shuai, et al.
Publicado: (2025)
Asymmetric Grid Quorum Systems for Heterogeneous Processes
por: Senn, Michael, et al.
Publicado: (2025)
por: Senn, Michael, et al.
Publicado: (2025)
Age-Aware Partial Gradient Update Strategy for Federated Learning Over the Air
por: Du, Ruihao, et al.
Publicado: (2025)
por: Du, Ruihao, et al.
Publicado: (2025)
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients
por: Wang, Mengdi, et al.
Publicado: (2024)
por: Wang, Mengdi, et al.
Publicado: (2024)
Decentralized Proactive Model Offloading and Resource Allocation for Split and Federated Learning
por: Huang, Binbin, et al.
Publicado: (2024)
por: Huang, Binbin, et al.
Publicado: (2024)
SuperSFL: Resource-Heterogeneous Federated Split Learning with Weight-Sharing Super-Networks
por: Asif, Abdullah Al, et al.
Publicado: (2026)
por: Asif, Abdullah Al, et al.
Publicado: (2026)
Memory-Efficient Split Federated Learning for LLM Fine-Tuning on Heterogeneous Mobile Devices
por: Chen, Xiaopei, et al.
Publicado: (2025)
por: Chen, Xiaopei, et al.
Publicado: (2025)
ParallelSFL: A Novel Split Federated Learning Framework Tackling Heterogeneity Issues
por: Liao, Yunming, et al.
Publicado: (2024)
por: Liao, Yunming, et al.
Publicado: (2024)
Effective Heterogeneous Federated Learning via Efficient Hypernetwork-based Weight Generation
por: Shin, Yujin, et al.
Publicado: (2024)
por: Shin, Yujin, et al.
Publicado: (2024)
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning
por: Yi, Liping, et al.
Publicado: (2023)
por: Yi, Liping, et al.
Publicado: (2023)
Ejemplares similares
-
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis
por: Wang, Jiaqi, et al.
Publicado: (2024) -
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
por: Che, Liwei, et al.
Publicado: (2024) -
Stragglers Can Contribute More: Uncertainty-Aware Distillation for Asynchronous Federated Learning
por: Wang, Yujia, et al.
Publicado: (2025) -
Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation
por: Wang, Jiaqi, et al.
Publicado: (2024) -
Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping
por: Fan, Ziqing, et al.
Publicado: (2024)