Cover Image

A Secure and Private Distributed Bayesian Federated Learning Design

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Nuocheng, Wang, Sihua, Yang, Zhaohui, Chen, Mingzhe, Yin, Changchuan, Huang, Kaibin
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

Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA
by: Yang, Nuocheng, et al.
Published: (2026)

Digital Over-the-Air Federated Learning in Multi-Antenna Systems
by: Wang, Sihua, et al.
Published: (2023)

Collaborative Reinforcement Learning Based Unmanned Aerial Vehicle (UAV) Trajectory Design for 3D UAV Tracking
by: Zhu, Yujiao, et al.
Published: (2024)

Contrastive Language-Image Pre-Training Model based Semantic Communication Performance Optimization
by: Yang, Shaoran, et al.
Published: (2025)

Video Semantic Communication with Major Object Extraction and Contextual Video Encoding
by: Li, Haopeng, et al.
Published: (2024)

LoLaFL: Low-Latency Federated Learning via Forward-only Propagation
by: Zhang, Jierui, et al.
Published: (2024)

QMGeo: Differentially Private Federated Learning via Stochastic Quantization with Mixed Truncated Geometric Distribution
by: Wang, Zixi, et al.
Published: (2023)

Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2025)

Differentially Private Federated Clustering with Random Rebalancing
by: Yang, Xiyuan, et al.
Published: (2025)

Decentralized Federated Learning: A Survey on Security and Privacy
by: Hallaji, Ehsan, et al.
Published: (2024)

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

Buffered Asynchronous Secure Aggregation for Cross-Device Federated Learning
by: Wang, Kun, et al.
Published: (2024)

Deep Efficient Private Neighbor Generation for Subgraph Federated Learning
by: Zhang, Ke, et al.
Published: (2024)

FedGRec: Dynamic Spatio-Temporal Federated Graph Learning for Secure and Efficient Cross-Border Recommendations
by: Tan, Zhizhong, et al.
Published: (2025)

A Simple Data Augmentation for Feature Distribution Skewed Federated Learning
by: Yan, Yunlu, et al.
Published: (2023)

FedPSA: Modeling Behavioral Staleness in Asynchronous Federated Learning
by: Lu, Chaoyi, et al.
Published: (2026)

Learning Critically: Selective Self Distillation in Federated Learning on Non-IID Data
by: He, Yuting, et al.
Published: (2025)

Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
by: Li, Yuecheng, et al.
Published: (2024)

Bayesian Federated Learning for Continual Training
by: Milasheuski, Usevalad, et al.
Published: (2025)

A Robust Framework for Secure Cardiovascular Risk Prediction: An Architectural Case Study of Differentially Private Federated Learning
by: Tertulino, Rodrigo, et al.
Published: (2026)

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

Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning
by: Ye, Tiandi, et al.
Published: (2025)

A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning
by: Bian, Jieming, et al.
Published: (2025)

Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms
by: Peng, Yuanzhe, et al.
Published: (2025)

Federated Learning with New Knowledge: Fundamentals, Advances, and Futures
by: Wang, Lixu, et al.
Published: (2024)

FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
by: Lee, Seanie, et al.
Published: (2025)

Tazza: Shuffling Neural Network Parameters for Secure and Private Federated Learning
by: Lee, Kichang, et al.
Published: (2024)

Multi-View Wireless Sensing via Conditional Generative Learning: Framework and Model Design
by: Xing, Ziqing, et al.
Published: (2025)

VGFL-SA: Vertical Graph Federated Learning Structure Attack Based on Contrastive Learning
by: Chen, Yang, et al.
Published: (2025)

On the Fairness of Privacy Protection: Measuring and Mitigating the Disparity of Group Privacy Risks for Differentially Private Machine Learning
by: Yang, Zhi, et al.
Published: (2025)

BubbleSpec: Turning Long-Tail Bubbles into Speculative Rollout Drafts for Synchronous Reinforcement Learning
by: Xu, Yuhang, et al.
Published: (2026)

Privacy-Preserving Federated Learning with Differentially Private Hyperdimensional Computing
by: Piran, Fardin Jalil, et al.
Published: (2024)

Multi-Objective Optimization for Privacy-Utility Balance in Differentially Private Federated Learning
by: Ranaweera, Kanishka, et al.
Published: (2025)

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
by: Auddy, Arnab, et al.
Published: (2026)

Byzantine-Robust Aggregation for Securing Decentralized Federated Learning
by: Cajaraville-Aboy, Diego, et al.
Published: (2024)

SecureBoost+: Large Scale and High-Performance Vertical Federated Gradient Boosting Decision Tree
by: Fan, Tao, et al.
Published: (2021)

Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities
by: Lin, Zheng, et al.
Published: (2023)

Adaptive Guidance for Local Training in Heterogeneous Federated Learning
by: Zhang, Jianqing, et al.
Published: (2024)

Coding-Enforced Resilient and Secure Aggregation for Hierarchical Federated Learning
by: Weng, Shudi, et al.
Published: (2026)

Bayesian Neural Network For Personalized Federated Learning Parameter Selection
by: Luo, Mengen, et al.
Published: (2024)