AsyncFedGAN: An Efficient and Staleness-aware Asynchronous Federated Learning Framework for Generative Adversarial Networks
Generative Adversarial Networks (GANs) are deep learning models that learn and generate
new samples similar to existing ones. Traditionally, GANs are trained in centralized data …
new samples similar to existing ones. Traditionally, GANs are trained in centralized data …
Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models
Federated learning (FL) enables multiple parties to collaboratively fine-tune an large
language model (LLM) without the need of direct data sharing. Ideally, by training on …
language model (LLM) without the need of direct data sharing. Ideally, by training on …
[PDF][PDF] WW-FL: Secure and Private Large-Scale Federated Learning
Federated learning (FL) is an efficient approach for large-scale distributed machine learning
that promises data privacy by keeping training data on client devices. However, recent …
that promises data privacy by keeping training data on client devices. However, recent …