Cover Image

Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rahman, Ratun, Nguyen, Dinh C.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

False Data Injection Attack Detection in Edge-based Smart Metering Networks with Federated Learning
by: Uddin, Md Raihan, et al.
Published: (2024)

Sporadic Federated Learning Approach in Quantum Environment to Tackle Quantum Noise
by: Rahman, Ratun, et al.
Published: (2025)

Federated Learning: A Survey on Privacy-Preserving Collaborative Intelligence
by: Rahman, Ratun
Published: (2025)

Electrical Load Forecasting in Smart Grid: A Personalized Federated Learning Approach
by: Rahman, Ratun, et al.
Published: (2024)

Towards Personalized Quantum Federated Learning for Anomaly Detection
by: Rahman, Ratun, et al.
Published: (2025)

Towards Heterogeneous Quantum Federated Learning: Challenges and Solutions
by: Rahman, Ratun, et al.
Published: (2025)

Quantum Federated Learning for Multimodal Data: A Modality-Agnostic Approach
by: Pokharel, Atit, et al.
Published: (2025)

Escaping Barren Plateaus in Variational Quantum Algorithms Using Negative Learning Rate in Quantum Internet of Things
by: Rahman, Ratun, et al.
Published: (2025)

Latency-aware Multimodal Federated Learning over UAV Networks
by: Shaon, Shaba, et al.
Published: (2025)

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)

Multiple-Input Variational Auto-Encoder for Anomaly Detection in Heterogeneous Data
by: Dinh, Phai Vu, et al.
Published: (2025)

Personalized Federated Dictionary Learning for Modeling Heterogeneity in Multi-site fMRI Data
by: Zhang, Yipu, et al.
Published: (2025)

Electrical Load Forecasting over Multihop Smart Metering Networks with Federated Learning
by: Rahman, Ratun, et al.
Published: (2025)

Differentially Private Federated Quantum Learning via Quantum Noise
by: Pokharel, Atit, et al.
Published: (2025)

SimQFL: A Quantum Federated Learning Simulator with Real-Time Visualization
by: Rahman, Ratun, et al.
Published: (2025)

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

Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data
by: Zhou, Tailin, et al.
Published: (2023)

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

Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data
by: Weng, Pei-Yau, et al.
Published: (2025)

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

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

Quantum Federated Learning: A Comprehensive Survey
by: Nguyen, Dinh C., et al.
Published: (2025)

Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors
by: Huang, Chun-Yin, et al.
Published: (2024)

Privacy-Preserving Personalized Federated Learning for Distributed Photovoltaic Disaggregation under Statistical Heterogeneity
by: Chen, Xiaolu, et al.
Published: (2025)

Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models
by: Arya, Shivvrat, et al.
Published: (2024)

Federated Learning with Differential Privacy: An Utility-Enhanced Approach
by: Ranaweera, Kanishka, et al.
Published: (2025)

Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data
by: Nguyen, Duong M., et al.
Published: (2025)

Federated Learning on Virtual Heterogeneous Data with Local-global Distillation
by: Huang, Chun-Yin, et al.
Published: (2023)

Towards Layer-Wise Personalized Federated Learning: Adaptive Layer Disentanglement via Conflicting Gradients
by: Nguyen, Minh Duong, et al.
Published: (2024)

Learning to Guide Local Search for MPE Inference in Probabilistic Graphical Models
by: Malhotra, Brij, et al.
Published: (2026)

HARMONY: Bridging the Personalization-Generalization Gap by Mitigating Representation Skew in Heterogeneous Split Federated Learning
by: Youn, Jiseok, et al.
Published: (2026)

Federated Split Learning for Human Activity Recognition with Differential Privacy
by: Ndeko, Josue, et al.
Published: (2024)

From Federated Learning to Quantum Federated Learning for Space-Air-Ground Integrated Networks
by: Quy, Vu Khanh, et al.
Published: (2024)

Aggregation Alignment for Federated Learning with Mixture-of-Experts under Data Heterogeneity
by: Fang, Zihan, et al.
Published: (2026)

On the Impact of Data Heterogeneity in Federated Learning Environments with Application to Healthcare Networks
by: Milasheuski, Usevalad, et al.
Published: (2024)

Federated Causal Discovery from Heterogeneous Data
by: Li, Loka, et al.
Published: (2024)

Feature Distillation is the Better Choice for Model-Heterogeneous Federated Learning
by: Li, Yichen, et al.
Published: (2025)

Rethinking LoRA for Data Heterogeneous Federated Learning: Subspace and State Alignment
by: Peng, Hongyi, et al.
Published: (2026)