Cover Image

FedRE: A Representation Entanglement Framework for Model-Heterogeneous Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yao, Yuan, Wang, Lixu, Wu, Jiaqi, Song, Jin, Chen, Simin, Wang, Zehua, Tian, Zijian, Chen, Wei, Li, Huixia, Li, Xiaoxiao
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FedRE: Robust and Effective Federated Learning with Privacy Preference
by: Xiao, Tianzhe, et al.
Published: (2025)

FedDTPT: Federated Discrete and Transferable Prompt Tuning for Black-Box Large Language Models
by: Wu, Jiaqi, et al.
Published: (2024)

Efficient Detection Framework Adaptation for Edge Computing: A Plug-and-play Neural Network Toolbox Enabling Edge Deployment
by: Wu, Jiaqi, et al.
Published: (2024)

Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deployment
by: Wu, Jiaqi, et al.
Published: (2024)

A Closer Look at Personalized Fine-Tuning in Heterogeneous Federated Learning
by: Chen, Minghui, et al.
Published: (2025)

A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks
by: Wu, Jiaqi, et al.
Published: (2025)

FedClust: Tackling Data Heterogeneity in Federated Learning through Weight-Driven Client Clustering
by: Islam, Md Sirajul, et al.
Published: (2024)

Fed-REACT: Federated Representation Learning for Heterogeneous and Evolving Data
by: Chen, Yiyue, et al.
Published: (2025)

Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domain
by: Yao, Yuan, et al.
Published: (2026)

FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data
by: Zhang, Yuxin, et al.
Published: (2024)

pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
by: Yi, Liping, et al.
Published: (2023)

FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation
by: Peng, Zihao, et al.
Published: (2025)

Federated Model Heterogeneous Matryoshka Representation Learning
by: Yi, Liping, et al.
Published: (2024)

FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
by: Li, Li, et al.
Published: (2021)

FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning
by: Yi, Liping, et al.
Published: (2023)

pFedAFM: Adaptive Feature Mixture for Batch-Level Personalization in Heterogeneous Federated Learning
by: Yi, Liping, et al.
Published: (2024)

FedEAT: A Robustness Optimization Framework for Federated LLMs
by: Pang, Yahao, et al.
Published: (2025)

FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks
by: Lin, Zheng, et al.
Published: (2023)

FedFair^3: Unlocking Threefold Fairness in Federated Learning
by: Javaherian, Simin, et al.
Published: (2024)

Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients
by: Wang, Xiaolu, et al.
Published: (2024)

pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning
by: Yi, Liping, et al.
Published: (2024)

FedEL: Federated Elastic Learning for Heterogeneous Devices
by: Zhang, Letian, et al.
Published: (2025)

Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning
by: Chen, Minghui, et al.
Published: (2024)

FedCoSR: Personalized Federated Learning with Contrastive Shareable Representations for Label Heterogeneity in Non-IID Data
by: Huang, Chenghao, et al.
Published: (2024)

SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework
by: Zhang, Yuxin, et al.
Published: (2024)

Exploring Federated Unlearning: Review, Comparison, and Insights
by: Zhao, Yang, et al.
Published: (2023)

FedClust: Optimizing Federated Learning on Non-IID Data through Weight-Driven Client Clustering
by: Islam, Md Sirajul, et al.
Published: (2024)

Contribution Evaluation of Heterogeneous Participants in Federated Learning via Prototypical Representations
by: Guo, Qi, et al.
Published: (2024)

FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources
by: Islam, Md Sirajul, et al.
Published: (2026)

Anomalous Decay of Quantum Resources: The Entanglement Sudden Death Mpemba Effect
by: Liu, Zhilong, et al.
Published: (2026)

FedDifRC: Unlocking the Potential of Text-to-Image Diffusion Models in Heterogeneous Federated Learning
by: Wang, Huan, et al.
Published: (2025)

AutoFed: Personalized Federated Traffic Prediction via Adaptive Prompt
by: Zhao, Zijian, et al.
Published: (2025)

FedEM: A Privacy-Preserving Framework for Concurrent Utility Preservation in Federated Learning
by: Xu, Mingcong, et al.
Published: (2025)

HeteroFedSyn: Differentially Private Tabular Data Synthesis for Heterogeneous Federated Settings
by: Li, Xiaochen, et al.
Published: (2026)

FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization
by: Ning, Zhiyuan, et al.
Published: (2024)

FedHUG: Federated Heterogeneous Unsupervised Generalization for Remote Physiological Measurements
by: Yang, Xiao, et al.
Published: (2025)

FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning
by: Ji, Xinyuan, et al.
Published: (2024)

Foundation Models in Federated Learning: Assessing Backdoor Vulnerabilities
by: Li, Xi, et al.
Published: (2024)

FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs
by: Han, Shanshan, et al.
Published: (2023)

FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning
by: Yang, Zhiqin, et al.
Published: (2025)