Cover Image

Hypernetworks for Model-Heterogeneous Personalized Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Chen, Li, Husheng, Liu, Xiang, Jiang, Linshan, Wang, Danxin
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

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

Effective Heterogeneous Federated Learning via Efficient Hypernetwork-based Weight Generation
by: Shin, Yujin, et al.
Published: (2024)

Sentinel: Dynamic Knowledge Distillation for Personalized Federated Intrusion Detection in Heterogeneous IoT Networks
by: Singh, Gurpreet, et al.
Published: (2025)

Robust Model Aggregation for Heterogeneous Federated Learning: Analysis and Optimizations
by: Shao, Yumeng, et al.
Published: (2024)

Knowledge-Driven Federated Graph Learning on Model Heterogeneity
by: Wu, Zhengyu, et al.
Published: (2025)

Addressing Skewed Heterogeneity via Federated Prototype Rectification with Personalization
by: Guo, Shunxin, et al.
Published: (2024)

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

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

FedMOA: Federated GRPO for Personalized Reasoning LLMs under Heterogeneous Rewards
by: Wang, Ziyao, et al.
Published: (2026)

Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
by: Zhang, Jiaojiao, et al.
Published: (2024)

FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning
by: Tastan, Nurbek, et al.
Published: (2024)

MAP: Model Aggregation and Personalization in Federated Learning with Incomplete Classes
by: Li, Xin-Chun, et al.
Published: (2024)

A Unified Solution to Diverse Heterogeneities in One-shot Federated Learning
by: Bai, Jun, et al.
Published: (2024)

Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting
by: Tian, Chunlin, et al.
Published: (2024)

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

FedORGP: Guiding Heterogeneous Federated Learning with Orthogonality Regularization on Global Prototypes
by: Guo, Fucheng, et al.
Published: (2025)

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

Multimodal Online Federated Learning with Modality Missing in Internet of Things
by: Wang, Heqiang, et al.
Published: (2025)

Asynchronous Personalized Federated Learning through Global Memorization
by: Wan, Fan, et al.
Published: (2025)

Personalized Interpretation on Federated Learning: A Virtual Concepts approach
by: Yan, Peng, et al.
Published: (2024)

STHFL: Spatio-Temporal Heterogeneous Federated Learning
by: Guo, Shunxin, et al.
Published: (2025)

An Efficient Subspace Algorithm for Federated Learning on Heterogeneous Data
by: Zhang, Jiaojiao, et al.
Published: (2025)

Fed-GAME: Personalized Federated Learning with Graph Attention Mixture-of-Experts For Time-Series Forecasting
by: Li, Yi, et al.
Published: (2026)

AdaptiveFL: Adaptive Heterogeneous Federated Learning for Resource-Constrained AIoT Systems
by: Jia, Chentao, et al.
Published: (2023)

Convergence Analysis of Split Federated Learning on Heterogeneous Data
by: Han, Pengchao, et al.
Published: (2024)

Tackling Privacy Heterogeneity in Differentially Private Federated Learning
by: Xu, Ruichen, et al.
Published: (2026)

Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models
by: Yuan, Tianjun, et al.
Published: (2025)

Local Gradient Regulation Stabilizes Federated Learning under Client Heterogeneity
by: Luo, Ping, et al.
Published: (2026)

Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching
by: Li, Yichen, et al.
Published: (2024)

PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark
by: Zhang, Jianqing, et al.
Published: (2023)

The Diversity Bonus: Learning from Dissimilar Distributed Clients in Personalized Federated Learning
by: Wu, Xinghao, et al.
Published: (2024)

SAFL: Structure-Aware Personalized Federated Learning via Client-Specific Clustering and SCSI-Guided Model Pruning
by: Li, Nan, et al.
Published: (2025)

Breaking the Memory Wall for Heterogeneous Federated Learning via Progressive Training
by: Wu, Yebo, et al.
Published: (2024)

Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation
by: Wang, Jiaqi, et al.
Published: (2024)

Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning
by: Zhao, Xiyu, et al.
Published: (2025)

Tackling Resource-Constrained and Data-Heterogeneity in Federated Learning with Double-Weight Sparse Pack
by: Yang, Qiantao, et al.
Published: (2026)

Analytic Personalized Federated Meta-Learning
by: Gu, Shunxian, et al.
Published: (2025)