FedDM: Enhancing Communication Efficiency and Handling Data Heterogeneity in Federated Diffusion Models
J Vora, N Bouacida, A Krishnan… - arXiv preprint arXiv …, 2024 - arxiv.org
We introduce FedDM, a novel training framework designed for the federated training of
diffusion models. Our theoretical analysis establishes the convergence of diffusion models …
diffusion models. Our theoretical analysis establishes the convergence of diffusion models …
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
Federated Learning (FL) offers a promising framework for collaborative and privacy-
preserving machine learning across distributed data sources. However, the substantial …
preserving machine learning across distributed data sources. However, the substantial …
DeComFL: Federated Learning with Dimension-Free Communication
Federated Learning (FL) offers a promising framework for collaborative and privacy-
preserving machine learning across distributed data sources. However, the substantial …
preserving machine learning across distributed data sources. However, the substantial …