Latest Articles for Federated Learning

Examining privacy dangers in Federated Learning and large language models.

Asyn2F improves asynchronous federated learning for better model training and data privacy.

A new method enhances federated learning efficiency using client update strategies.

Examining federated unlearning and its challenges in machine learning privacy.

A look into the risks of data poisoning in federated learning systems.

Exploring privacy-preserving techniques in machine learning and their significance.

A look at federated learning and its impact on business decision-making.

Federated learning improves face recognition while protecting user privacy.

A new framework to improve learning in Federated Incremental Learning while ensuring data privacy.

New JAX-based library simplifies federated learning for better model training.

A new method enhances privacy in federated learning against gradient inversion attacks.

Introducing a framework to enhance anomaly detection in Federated Learning systems.

New methods enhance model learning by including slower devices in federated learning.

Revolutionizing data sharing and safety in vehicle networks with new learning frameworks.

A proposed framework enhances security for federated learning against adversarial attacks.

A new method improves 3D modeling efficiency using federated learning.

Federated learning enhances cooperation between autonomous vehicles in challenging weather.

FedMef improves federated learning for low-resource devices through innovative pruning techniques.

A new approach to optimize video streaming while ensuring user privacy.

Data Mesh transforms data management by fostering team ownership and collaboration.

New methods improve model adaptability for diverse user tasks.

Exploring the intersection of blockchain and federated learning for data privacy and security.

FedD2S enhances Federated Learning by personalizing models while preserving data privacy.

A novel method improves decision tree aggregation while maintaining interpretability and privacy.

Examining federated learning protocols to enhance privacy while improving model accuracy.

A new approach to medical image analysis using federated learning and weak supervision.

Exploring privacy risks and solutions in large language models.

An overview of ASR and its advancements in modern applications.

A new method enhances data security for IoT devices while preserving privacy.

A new method enhances device communication efficiency in federated learning networks.

A new approach to enhance e-health through improved data management and patient privacy.

A new algorithm enhances federated learning by addressing client diversity and efficiency.

Introducing FedFisher, an innovative algorithm for efficient federated learning.

A new method to fine-tune models while ensuring data privacy.

Exploring how machine learning improves human activity recognition from sensor data.

This study enhances federated learning by boosting model diversity while protecting privacy.

A new method enhances security in federated learning through intermediate outputs analysis.

A framework to enhance collaboration in healthcare while ensuring patient privacy.

This article discusses the integration of Bayesian deep learning into federated learning approaches.

The role of machine learning in analyzing medical images is rapidly growing.