Lingjuan Lyu

A method for personalized machine learning in federated learning environments.

An overview of copyright issues in generative AI and its impact.

A new model efficiently targets nodes in GNNs with minimal changes.

Examining issues of memorization in AI-generated images and its implications.

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

A novel approach for identifying hidden watermarks without prior knowledge.

FedMR tackles challenges in federated learning with partial class data, enhancing model performance.

A new method to safeguard datasets against unauthorized usage in generative models.

A new dataset aims to improve the safety of text-to-image models against harmful content.

A new framework improves federated learning while ensuring data privacy.

Explore cost-effective techniques for training text-to-image generative models.

New methods tackle issues of copying in image generation models.

A new method to enhance data variety for improved model performance.

A system for secure AI learning in healthcare without sharing patient data.

Revolutionizing robot training with a focus on language-based instructions.

RefSD offers a smart way to create synthetic images while protecting privacy.

Innovative methods help rural clinics access advanced healthcare solutions.