Image de couverture de livre

FedEL: Federated Elastic Learning for Heterogeneous Devices

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Letian, Chen, Bo, Bian, Jieming, Wang, Lei, Xu, Jie
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning
par: Bian, Jieming, et autres
Publié: (2026)

FedALT: Federated Fine-Tuning through Adaptive Local Training with Rest-of-World LoRA
par: Bian, Jieming, et autres
Publié: (2025)

Accelerating Asynchronous Federated Learning Convergence via Opportunistic Mobile Relaying
par: Bian, Jieming, et autres
Publié: (2022)

A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning
par: Bian, Jieming, et autres
Publié: (2025)

Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms
par: Peng, Yuanzhe, et autres
Publié: (2025)

Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains
par: Wang, Lei, et autres
Publié: (2024)

Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning
par: Wang, Lei, et autres
Publié: (2025)

FedCCA: Client-Centric Adaptation against Data Heterogeneity in Federated Learning on IoT Devices
par: Wang, Kaile, et autres
Publié: (2026)

LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement
par: Bian, Jieming, et autres
Publié: (2024)

FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning
par: Ji, Xinyuan, et autres
Publié: (2024)

FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation
par: Peng, Zihao, et autres
Publié: (2025)

FedCoSR: Personalized Federated Learning with Contrastive Shareable Representations for Label Heterogeneity in Non-IID Data
par: Huang, Chenghao, et autres
Publié: (2024)

FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices
par: Yao, Dezhong, et autres
Publié: (2025)

FedRD: Reducing Divergences for Generalized Federated Learning via Heterogeneity-aware Parameter Guidance
par: Wang, Kaile, et autres
Publié: (2026)

FedConv: A Learning-on-Model Paradigm for Heterogeneous Federated Clients
par: Shen, Leming, et autres
Publié: (2025)

Accurate Forgetting for Heterogeneous Federated Continual Learning
par: Wuerkaixi, Abudukelimu, et autres
Publié: (2025)

FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients
par: Wen, Tian, et autres
Publié: (2026)

Robust Federated Learning on Edge Devices with Domain Heterogeneity
par: Le, Huy Q., et autres
Publié: (2025)

FedModule: A Modular Federated Learning Framework
par: Chen, Chuyi, et autres
Publié: (2024)

FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data
par: Zhang, Yuxin, et autres
Publié: (2024)

FedDiverse: Tackling Data Heterogeneity in Federated Learning with Diversity-Driven Client Selection
par: Németh, Gergely D., et autres
Publié: (2025)

Fed-Credit: Robust Federated Learning with Credibility Management
par: Chen, Jiayan, et autres
Publié: (2024)

Federated Learning with Instance-Dependent Noisy Label
par: Wang, Lei, et autres
Publié: (2023)

FedMTFI: Feature Importance Based Optimized Multi Teacher Knowledge Distillation in Heterogeneous Federated Learning Environment
par: Shadin, Nazmus Shakib, et autres
Publié: (2026)

FedMP: Tackling Medical Feature Heterogeneity in Federated Learning from a Manifold Perspective
par: Zhou, Zhekai, et autres
Publié: (2025)

FedCLF -- Towards Efficient Participant Selection for Federated Learning in Heterogeneous IoV Networks
par: Wijethilake, Kasun Eranda, et autres
Publié: (2025)

FedConPE: Efficient Federated Conversational Bandits with Heterogeneous Clients
par: Li, Zhuohua, et autres
Publié: (2024)

FedUV: Uniformity and Variance for Heterogeneous Federated Learning
par: Son, Ha Min, et autres
Publié: (2024)

Prioritizing Modalities: Flexible Importance Scheduling in Federated Multimodal Learning
par: Bian, Jieming, et autres
Publié: (2024)

FedAPA: Federated Learning with Adaptive Prototype Aggregation Toward Heterogeneous Wi-Fi CSI-based Crowd Counting
par: Guo, Jingtao, et autres
Publié: (2025)

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion
par: Fan, Tao, et autres
Publié: (2026)

FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks
par: Lin, Zheng, et autres
Publié: (2023)

FedMABench: Benchmarking Mobile Agents on Decentralized Heterogeneous User Data
par: Wang, Wenhao, et autres
Publié: (2025)

FedClust: Tackling Data Heterogeneity in Federated Learning through Weight-Driven Client Clustering
par: Islam, Md Sirajul, et autres
Publié: (2024)

FedEGG: Federated Learning with Explicit Global Guidance
par: Zhai, Kun, et autres
Publié: (2024)

Federated Generative Learning with Foundation Models
par: Zhang, Jie, et autres
Publié: (2023)

FedHPD: Heterogeneous Federated Reinforcement Learning via Policy Distillation
par: Jiang, Wenzheng, et autres
Publié: (2025)

FedEmb: A Vertical and Hybrid Federated Learning Algorithm using Network And Feature Embedding Aggregation
par: Meng, Fanfei, et autres
Publié: (2023)

FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity
par: Sun, Zhaobin, et autres
Publié: (2024)

FedPSA: Modeling Behavioral Staleness in Asynchronous Federated Learning
par: Lu, Chaoyi, et autres
Publié: (2026)