federated learning

Training Without Gathering the Data: A Interdisciplinary Mapping Review of Federated Learning and Privacy-Preserving AI

This article presents a narrative review of Federated Learning and Privacy-Preserving AI in the context of Artificial Intelligence. The literature on this topic has expanded substantially over recent decades, yet it remains fragmented across subfields, methods, and national research traditions. Drawing on an interpreti...

Private Computation Space: Experience with Trusted Multi-Cluster Federated Learning for Agriculture

The Private Computation Space (PCS), a deployed, open-source Machine Learning system to provision and process farmer data securely and improve the worst single-site model accuracy by 22.4% and 9.1%, respectively, while preserving privacy.

CACTUS: Mask-Guided Semantic Clean-Label Backdoors in Decentralized Federated Learning

Results indicate that CACTUS can propagate backdoors through repeated DFL aggregation and show that ASR varies with network topology and increases with the malicious-node ratio.

Similarity-Aware Personalized Federated Learning in Heterogeneous Environments

This work proposes SAPE-FL (Similarity-Aware Personalized Federated Learning), a novel personalization framework that anchors each client's model to both the global model and a similarity-weighted peer averaged model that mitigates negative transfer and enhances robustness in heterogeneous settings.

D-FROST: Decentralized Federated pRompt-tuning via Optimal tranSporT for Non-IID and Imbalanced Data

This work forms decentralized prompt tuning as a Wasserstein-based optimization problem over prompt measures, which captures the set-valued structure of prompts and proposes D-FROST, an optimal-transport-based (OT-based) decentralized prompt-tuning algorithm that merges neighborhood prompts into compact representative...

Federated LoRA Adaptation of BiomedCLIP Across Four International Chest X-Ray Cohorts

Federated LoRA adaptation improves shared-class AUC on all four cohorts over the unadapted BiomedCLIP backbone over the unadapted BiomedCLIP backbone, showing that the gains come from federated adaptation rather than from the pretrained model's zero-shot ability.

Agentic GAN-driven federated resource orchestration for music streaming in edge-cloud collaborative consumer electronics networks

Review of: "Advancing Personal Health Data Spaces: Governance, Interoperability, and Real-World Evidence for Learning Healthcare Systems"

This manuscript presents a timely, ambitious, and highly relevant commentary on the role of Personal Health Data Spaces in the future development of healthcare.I appreciate its patient-centred perspective and its recognition that personalised medicine cannot be achieved through isolated technological solutions, fragmen...

Decentralized Verification of Federated Learning Models

Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on decentralized data sources without direct data sharing. However, ensuring the integrity and accuracy of these models remains a significant challenge. Traditional verification methods often rely on centralized aggregation...

Replication package for Flows and Rounds: benchmark and retrieval scripts for distributed neurodynamic optimization and federated learning

This package contains the code and generated data behind the quantitative results of the survey "Flows and Rounds: A Survey of Distributed Neurodynamic Optimization and Federated Learning", submitted to Neurocomputing. It reproduces every number, table, and figure in Sections 2.3 and 8 of the article. No third-party, p...

A proactive defense framework for federated learning: A framework integrating verified piecewise perturbation and quantum-enhanced encryption

Land subsidence hazard mapping using a federated learning architecture with satellite and local environmental data

Land subsidence has become one of the most critical environmental and geomorphological hazards in recent years, threatening groundwater resources, urban infrastructure, and ecosystem stability. This study presents a novel Federated Learning (FL)-based framework for land subsidence hazard mapping in Poldokhtar County, I...