Latest Articles for Data Privacy

A new framework tackles unlearning challenges in decentralized machine learning environments.

A new method enhances the use of large language models on mobile devices.

FAM enhances AI model training while maintaining patient data privacy.

A new method improves pose estimation using only target domain data.

Explore strategies for ensuring data privacy in various fields.

New techniques improve disease diagnosis while ensuring patient privacy.

Discover how federated learning optimizes data training while maintaining privacy.

Exploring the imperfect shuffle model for enhanced data privacy.

Examining privacy risks in federated learning and the need for improved defenses.

Zeal enhances data protection while simplifying sharing and storage.

Generative AI is transforming medical imaging with new data generation techniques.

Examining hidden data concerns in machine learning models and their security implications.

A new approach personalizes model training while protecting data privacy.

Ensuring equitable suggestions in recommendation systems for all users.

New detailed Wikipedia pageview statistics released using privacy measures.

Exploring the importance and challenges of pseudonymization in research data sharing.

A look at combining split learning and encryption for better data privacy.

Exploring the dangers of image hijacks affecting vision-language models.

Exploring the ethical implications of AI in healthcare and the need for fairness.

Exploring the use of deep learning in blockchain consensus mechanisms.

Learn how federated analysis keeps medical data secure while offering insights.

A study on user choices regarding data privacy and cookie consent.

New framework links Client Drift and Catastrophic Forgetting for better model performance.

FedLADA improves model training speed and accuracy while ensuring data privacy.

Federated learning improves AI while safeguarding data privacy across devices.

A new method enhances machine learning for medical imaging while protecting patient privacy.

This paper discusses machine unlearning and its connection to differential privacy.

Equitable-FL enables efficient federated learning in devices with varied resources.

Discover how Local Differential Privacy protects user data while enabling analysis.

Exploring the rise of decentralized language models and their benefits over centralized systems.

FedSecure speeds up satellite data analysis while ensuring privacy and security.

FCCA improves model accuracy while ensuring user privacy in federated learning.

A look at how federated learning and model pruning enhance wireless network performance.

LDP-Auditor framework estimates privacy loss in Local Differential Privacy methods.

Federated Learning improves speech recognition while keeping user data private.

A new approach balances privacy and performance in GNN training.

A new protocol aims to enhance privacy in card transactions.

This article explores a method to enhance federated learning with efficient communication.

This method improves brain disorder detection while keeping patient data secure.

EdgeFL simplifies federated learning while ensuring data privacy and efficiency.