:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hu, Yuhan, Fang, Xiaolei
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2604.19451
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals
by: Su, Yuqi, et al.
Published: (2024)

Dynamic Clustering for Personalized Federated Learning on Heterogeneous Edge Devices
by: Liu, Heting, et al.
Published: (2025)

Personalized One-shot Federated Graph Learning for Heterogeneous Clients
by: Yan, Guochen, et al.
Published: (2024)

A Multi-head Attention Fusion Network for Industrial Prognostics under Discrete Operational Conditions
by: Su, Yuqi, et al.
Published: (2026)

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

Personalized Federated Learning for Statistical Heterogeneity
by: Firdaus, Muhammad, et al.
Published: (2024)

CO-PFL: Contribution-Oriented Personalized Federated Learning for Heterogeneous Networks
by: Xing, Ke, et al.
Published: (2025)

Lightweight Industrial Cohorted Federated Learning for Heterogeneous Assets
by: Amarlingam, Madapu, et al.
Published: (2024)

Heterogeneous Federated Learning via Personalized Generative Networks
by: Taghiyarrenani, Zahra, et al.
Published: (2023)

Deep Learning-Based Residual Useful Lifetime Prediction for Assets with Uncertain Failure Modes
by: Su, Yuqi, et al.
Published: (2024)

Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics
by: Chu, Yun-Wei, et al.
Published: (2022)

Factor-Assisted Federated Learning for Personalized Optimization with Heterogeneous Data
by: Wang, Feifei, et al.
Published: (2023)

PPFL: A Personalized Federated Learning Framework for Heterogeneous Population
by: Di, Hao, et al.
Published: (2023)

On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness
by: Zhu, Shengkun, et al.
Published: (2024)

Hypernetworks for Model-Heterogeneous Personalized Federated Learning
by: Zhang, Chen, et al.
Published: (2025)

Heterogeneity-Aware Knowledge Sharing for Graph Federated Learning
by: Yu, Wentao, et al.
Published: (2026)

A Federated Data Fusion-Based Prognostic Model for Applications with Multi-Stream Incomplete Signals
by: Arabi, Madi, et al.
Published: (2023)

Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization
by: Rahman, Ratun, et al.
Published: (2026)

Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning
by: Li, Zhilong, et al.
Published: (2024)

Lazy But Effective: Collaborative Personalized Federated Learning with Heterogeneous Data
by: Rokvic, Ljubomir, et al.
Published: (2025)

Risk-Aware Accelerated Wireless Federated Learning with Heterogeneous Clients
by: Ads, Mohamed, et al.
Published: (2024)

Federated Online Learning for Heterogeneous Multisource Streaming Data
by: Li, Jingmao, et al.
Published: (2025)

Personalized Federated Learning on Heterogeneous and Long-Tailed Data via Expert Collaborative Learning
by: Lv, Fengling, et al.
Published: (2024)

FedMoE: Personalized Federated Learning via Heterogeneous Mixture of Experts
by: Mei, Hanzi, et al.
Published: (2024)

Personalized Observation Normalization for Federated Reinforcement Learning in Simulation Environments with Heterogeneity
by: Pang, Yiran, et al.
Published: (2026)

A Comprehensive View of Personalized Federated Learning on Heterogeneous Clinical Datasets
by: Tavakoli, Fatemeh, et al.
Published: (2023)

Personalized Federated Learning via Gaussian Generative Modeling
by: Hu, Peng, et al.
Published: (2026)

APFL: Analytic Personalized Federated Learning via Dual-Stream Least Squares
by: Fan, Kejia, et al.
Published: (2025)

Fed-Meta-Align: A Similarity-Aware Aggregation and Personalization Pipeline for Federated TinyML on Heterogeneous Data
by: Macharla, Hemanth, et al.
Published: (2025)

Heterogeneity-Aware Client Sampling for Optimal and Efficient Federated Learning
by: Weng, Shudi, et al.
Published: (2025)

CA-HFP: Curvature-Aware Heterogeneous Federated Pruning with Model Reconstruction
by: Hu, Gang, et al.
Published: (2026)

Heterogeneity-aware Personalized Federated Learning via Adaptive Dual-Agent Reinforcement Learning
by: Chen, Xi, et al.
Published: (2025)

Federated Multilinear Principal Component Analysis with Applications in Prognostics
by: Zhou, Chengyu, et al.
Published: (2023)

Drift-Aware Federated Learning: A Causal Perspective
by: Fang, Yunjie, et al.
Published: (2025)

Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers
by: Bose, Shourya, et al.
Published: (2024)

Heterogeneous Federated Learning System for Sparse Healthcare Time-Series Prediction
by: Syu, Jia-Hao, et al.
Published: (2025)

Federated Learning for Epileptic Seizure Prediction Across Heterogeneous EEG Datasets
by: Baykara, Cem Ata, et al.
Published: (2025)

Tackling Heterogeneity in Quantum Federated Learning: An Integrated Sporadic-Personalized Approach
by: Rahman, Ratun, et al.
Published: (2026)

FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions
by: Tang, Jianheng, et al.
Published: (2025)

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