Cover Image

Explainability and Continual Learning meet Federated Learning at the Network Edge

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tsouparopoulos, Thomas, Koutsopoulos, Iordanis
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Joint Explainability-Performance Optimization With Surrogate Models for AI-Driven Edge Services
by: Charalampakos, Foivos, et al.
Published: (2025)

Split Federated Learning Architectures for High-Accuracy and Low-Delay Model Training
by: Papageorgiou, Yiannis, et al.
Published: (2026)

Personalized Federated Learning with Exact Stochastic Gradient Descent
by: Nikoloutsopoulos, Sotirios, et al.
Published: (2022)

Large Language Model Partitioning for Low-Latency Inference at the Edge
by: Kafetzis, Dimitrios, et al.
Published: (2025)

Collaborative Split Federated Learning with Parallel Training and Aggregation
by: Papageorgiou, Yiannis, et al.
Published: (2025)

Robust Federated Learning on Edge Devices with Domain Heterogeneity
by: Le, Huy Q., et al.
Published: (2025)

LLMs meet Federated Learning for Scalable and Secure IoT Management
by: Otoum, Yazan, et al.
Published: (2025)

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

Federated Continual Learning: Concepts, Challenges, and Solutions
by: Hamedi, Parisa, et al.
Published: (2025)

Accurate Forgetting for Heterogeneous Federated Continual Learning
by: Wuerkaixi, Abudukelimu, et al.
Published: (2025)

Better Generative Replay for Continual Federated Learning
by: Qi, Daiqing, et al.
Published: (2023)

Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review
by: Lopez-Ramos, Luis M., et al.
Published: (2024)

Graph Federated Learning Based Proactive Content Caching in Edge Computing
by: Wang, Rui
Published: (2025)

Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Network
by: Wu, Qiong, et al.
Published: (2024)

Uncertainty-Aware Explainable Federated Learning
by: Zhang, Yanci, et al.
Published: (2025)

Quantum Agents for Algorithmic Discovery
by: Kerenidis, Iordanis, et al.
Published: (2025)

Large-Small Model Collaborative Framework for Federated Continual Learning
by: Yu, Hao, et al.
Published: (2025)

Federated Continual Learning via Knowledge Fusion: A Survey
by: Yang, Xin, et al.
Published: (2023)

Personalized Federated Continual Learning via Multi-granularity Prompt
by: Yu, Hao, et al.
Published: (2024)

MetaCLBench: Meta Continual Learning Benchmark on Resource-Constrained Edge Devices
by: Li, Sijia, et al.
Published: (2025)

Continual Deep Learning on the Edge via Stochastic Local Competition among Subnetworks
by: Christophides, Theodoros, et al.
Published: (2024)

FAuNO: Semi-Asynchronous Federated Reinforcement Learning Framework for Task Offloading in Edge Systems
by: Metelo, Frederico, et al.
Published: (2025)

SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation
by: Zhong, Luying, et al.
Published: (2024)

DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices
by: Jia, Yongzhe, et al.
Published: (2024)

Towards Efficient Federated Learning of Networked Mixture-of-Experts for Mobile Edge Computing
by: Gao, Song, et al.
Published: (2025)

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

Personalizing Federated Learning for Hierarchical Edge Networks with Non-IID Data
by: Lee, Seunghyun, et al.
Published: (2025)

Explainable Reinforcement Learning for Formula One Race Strategy
by: Thomas, Devin, et al.
Published: (2025)

Tensor Networks for Explainable Machine Learning in Cybersecurity
by: Aizpurua, Borja, et al.
Published: (2023)

Shift Happens: Mixture of Experts based Continual Adaptation in Federated Learning
by: Bhope, Rahul Atul, et al.
Published: (2025)

Closed-form merging of parameter-efficient modules for Federated Continual Learning
by: Salami, Riccardo, et al.
Published: (2024)

Federated Learning of Dynamic Bayesian Network via Continuous Optimization from Time Series Data
by: Chen, Jianhong, et al.
Published: (2024)

Explainable Hierarchical Deep Learning Neural Networks (Ex-HiDeNN)
by: Batley, Reza T., et al.
Published: (2025)

Towards Heterogeneity-Aware and Energy-Efficient Topology Optimization for Decentralized Federated Learning in Edge Environment
by: Liu, Yuze, et al.
Published: (2025)

Towards Optimal Customized Architecture for Heterogeneous Federated Learning with Contrastive Cloud-Edge Model Decoupling
by: Chen, Xingyan, et al.
Published: (2024)

Joint Optimization of Resource Allocation and Data Selection for Fast and Cost-Efficient Federated Edge Learning
by: Jia, Yunjian, et al.
Published: (2024)

QuantFL: Sustainable Federated Learning for Edge IoT via Pre-Trained Model Quantisation
by: Herath, Charuka, et al.
Published: (2026)

A Proposal for Networks Capable of Continual Learning
by: Erden, Zeki Doruk, et al.
Published: (2025)

Fast AI Model Partition for Split Learning over Edge Networks
by: Li, Zuguang, et al.
Published: (2025)

Federated Continual Learning for Edge-AI: A Comprehensive Survey
by: Wang, Zi, et al.
Published: (2024)