Latest Articles for Data Privacy

Examining methods for machine learning domain adaptation: UDA vs. SFDA.

A look at how FedAlign enhances learning without compromising data privacy.

PEFT methods enhance language models while safeguarding private data.

This guide discusses keeping data safe while training AI effectively.

Ensuring AI in energy is safe, fair, and reliable for everyone.

Privacy auditing is vital for safeguarding personal data in today's information age.

A look into private prediction methods and the DaRRM algorithm.

Learn how federated learning keeps your data safe while improving machine learning models.

A look at domain adaptation, privacy, and federated learning in data science.

Examining the benefits and risks of Federated Parameter-Efficient Fine-Tuning.

HAI-DEF provides tools to simplify AI development for healthcare applications.

A new dataset and model aim to improve medical image generation for AI applications.

Using rephrased clinical notes to create synthetic data for healthcare models.

Study reveals privacy fact sheets improve EHR engagement among patients.

Learn how the linear-transformation model protects data privacy during analysis.

FedGR improves federated learning by refining noisy labels for better collaboration.

Federated learning protects brain data while improving motor imagery classification.

Learn how Confidential Computing protects sensitive information in today's digital world.

TruncFormer speeds up private inference for large language models while keeping data safe.

Explore the importance of guiding AI model usage responsibly.

Discover how EnFed enhances activity monitoring while ensuring privacy and saving battery life.

Learn how machines can forget unnecessary data for better privacy.

AI agents learn together while preserving individual techniques for better results.

A look at federated learning and its role in data privacy.

New methods ensure data privacy protection while utilizing machine learning.

Discover how federated learning protects your data while enhancing technology.

Federated Learning transforms machine learning while protecting sensitive data.

Explore how L2 regularization can enhance privacy in AI models.

Learn how the Shapley Value helps distribute contributions in data analysis.

Combining personalized models with global insights for enhanced privacy in data sharing.

FedPAW uses federated learning to enhance vehicle speed predictions while ensuring privacy.

A new approach to safeguarding sensitive health data while enabling valuable insights.

New methods aim to protect sensitive data while keeping it useful.

New methods combine quantum computing and federated learning to enhance data privacy.

SupportBot offers a tech-based approach to overcoming mental health challenges.

Explore how data sharing can improve conditions for gig workers.

Learn how federated learning trains AI while protecting personal data.

Innovative methods ensure privacy while generating realistic synthetic data.

Federated Learning transforms data sharing while protecting personal information.

FedMetaMed transforms personalized healthcare through innovative data collaboration techniques.