1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision
Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman +13
Deep learning methods are transforming research, enabling new techniques, and ultimately leading to new discoveries. As the demand for more capable AI models continues to grow, we…
cs.LG2023★ 1 cited
Hierarchical and Decentralised Federated Learning
Omer Rana, Theodoros Spyridopoulos, Nathaniel Hudson +4
Federated learning has shown enormous promise as a way of training ML models in distributed environments while reducing communication costs and protecting data privacy. However, th…