Latest Articles for Federated Learning

This study explores Federated Learning's role in Document Visual Question Answering.

A new approach to enhance client availability in federated learning.

A new method improves security and privacy in continuous authentication for devices.

A look into how Sparse Models improve Federated Learning efficiency.

A new method for detecting vehicle misbehavior while protecting privacy.

A new approach enhances intrusion detection in decentralized systems.

Improving mobile sensing applications through a novel framework for managing missing data.

Research improves ECG interpretation while ensuring patient data privacy.

A new framework enhances federated learning and prevents forgetfulness in AI models.

Exploring how Federated Learning can enhance data privacy in healthcare.

A novel approach improves performance and fairness in federated learning.

AdaFedFR improves face recognition while safeguarding user privacy.

Learn how distributed learning can improve machine learning efficiency and model training.

FedSC improves model training while maintaining user privacy in federated learning.

Cohort-based approach improves efficiency and accuracy in Federated Learning systems.

Discover how Federated Behavioral Planes improve understanding of client actions in federated learning.

Research shows vulnerabilities in federated learning's approach to text privacy.

Exploring AI's impact on efficiency, privacy, and security in vital systems.

A new method lowers communication loads in federated learning while enhancing privacy.

Client2Vec enhances federated learning by creating unique identifiers for user data.

Exploring the blend of privacy-focused learning and data generation techniques.

Harnessing early-exit models for efficient federated learning in ASR systems.

FedHPL enhances federated learning efficiency while ensuring data privacy across devices.

Fast-FedUL provides quick data removal methods for federated learning while ensuring privacy.

FeMLoc improves indoor localization using federated and meta-learning techniques.

FedGELA tackles challenges in federated learning with partially class-disjoint data.

FedLESAM tackles data challenges in federated learning for better model performance.

A global challenge highlights federated learning for breast density classification.

Federated and transfer learning enhance efficiency and accuracy in cancer detection.

Federated Learning trains models while keeping user data private and secure.

A new approach enhances security and performance in federated learning with blockchain.

Examining client contributions and vulnerabilities in federated learning systems.

SpaFL enhances communication and computation in Federated Learning while securing personal data.

LayerCAM-AE enhances detection of malicious updates in federated learning while preserving data privacy.

A new method tackles wireless errors in federated learning for IoT devices.

A new multi-server approach improves federated learning efficiency and speed.

New approach improves machine learning privacy and resilience against attacks.

New method improves federated learning while protecting user privacy.

Increasing communication rounds reduces costs and improves model performance in federated learning.

This article addresses how to simulate client data for faster federated learning.