Image de couverture de livre

FedPSA: Modeling Behavioral Staleness in Asynchronous Federated Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lu, Chaoyi, Sun, Yiding, Yang, Zhichuan, Chen, Jinqian, Yin, Dongfu, Zhu, Jihua
Format:	Preprint
Publié:	2026
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

AFBS:Buffer Gradient Selection in Semi-asynchronous Federated Learning
par: Lu, Chaoyi, et autres
Publié: (2025)

Beyond Factor Aggregation: Gauge-Aware Low-Rank Server Representations for Federated LoRA
par: Chen, Jinqian, et autres
Publié: (2026)

Corrected with the Latest Version: Make Robust Asynchronous Federated Learning Possible
par: Lu, Chaoyi, et autres
Publié: (2025)

HFedCKD: Toward Robust Heterogeneous Federated Learning via Data-free Knowledge Distillation and Two-way Contrast
par: Zheng, Yiting, et autres
Publié: (2025)

Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models
par: Chen, Jinqian, et autres
Publié: (2024)

Revisiting Gradient Staleness: Evaluating Distance Metrics for Asynchronous Federated Learning Aggregation
par: Wilhelm, Patrick, et autres
Publié: (2026)

FedStale: leveraging stale client updates in federated learning
par: Rodio, Angelo, et autres
Publié: (2024)

Degree of Staleness-Aware Data Updating in Federated Learning
par: Liu, Tao, et autres
Publié: (2025)

TPFL: A Trustworthy Personalized Federated Learning Framework via Subjective Logic
par: Chen, Jinqian, et autres
Publié: (2024)

FedStaleWeight: Buffered Asynchronous Federated Learning with Fair Aggregation via Staleness Reweighting
par: Ma, Jeffrey, et autres
Publié: (2024)

FedSA-GCL: A Semi-Asynchronous Federated Graph Learning Framework with Personalized Aggregation and Cluster-Aware Broadcasting
par: Yuan, Zhongzheng, et autres
Publié: (2025)

Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation
par: Jung, Hyunji, et autres
Publié: (2026)

FedFa: A Fully Asynchronous Training Paradigm for Federated Learning
par: Xu, Haotian, et autres
Publié: (2024)

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

Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning
par: Ma, Hui, et autres
Publié: (2025)

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

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

FedEL: Federated Elastic Learning for Heterogeneous Devices
par: Zhang, Letian, et autres
Publié: (2025)

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

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

FedKRSO: Communication and Memory Efficient Federated Fine-Tuning of Large Language Models
par: Yang, Guohao, et autres
Publié: (2026)

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

Privacy Preserved Blood Glucose Level Cross-Prediction: An Asynchronous Decentralized Federated Learning Approach
par: Piao, Chengzhe, et autres
Publié: (2024)

Mitigating Participation Imbalance Bias in Asynchronous Federated Learning
par: Chang, Xiangyu, et autres
Publié: (2025)

A-3PO: Accelerating Asynchronous LLM Training with Staleness-aware Proximal Policy Approximation
par: Li, Xiaocan, et autres
Publié: (2025)

FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model
par: Shao, Shuo, et autres
Publié: (2022)

AdaFed: Fair Federated Learning via Adaptive Common Descent Direction
par: Hamidi, Shayan Mohajer, et autres
Publié: (2024)

FedDRL: A Trustworthy Federated Learning Model Fusion Method Based on Staged Reinforcement Learning
par: Chen, Leiming, et autres
Publié: (2023)

Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users
par: Yang, Hantao, et autres
Publié: (2024)

FedUAF: Uncertainty-Aware Fusion with Reliability-Guided Aggregation for Multimodal Federated Sentiment Analysis
par: Zhu, Xianxun, et autres
Publié: (2026)

FedPFT: Federated Proxy Fine-Tuning of Foundation Models
par: Peng, Zhaopeng, et autres
Publié: (2024)

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

FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning
par: Tamirisa, Rishub, et autres
Publié: (2023)

FedBWO: Enhancing Communication Efficiency in Federated Learning
par: Hayyolalam, Vahideh, et autres
Publié: (2025)

FedMuon: Accelerating Federated Learning with Matrix Orthogonalization
par: Liu, Junkang, et autres
Publié: (2025)

Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
par: Liang, Chen, et autres
Publié: (2026)

FedSDWC: Federated Synergistic Dual-Representation Weak Causal Learning for OOD
par: Huang, Zhenyuan, et autres
Publié: (2025)

GuardFed: A Trustworthy Federated Learning Framework Against Dual-Facet Attacks
par: Li, Yanli, et autres
Publié: (2025)

pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning
par: Lai, Jiahao, et autres
Publié: (2024)

ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
par: Wang, Hui-Po, et autres
Publié: (2021)