no code implementations • 9 Mar 2024 • Rui Yang, Haoran Liu, Edison Marrese-Taylor, Qingcheng Zeng, Yu He Ke, Wanxin Li, Lechao Cheng, Qingyu Chen, James Caverlee, Yutaka Matsuo, Irene Li
Large Language Models (LLMs) have significantly advanced healthcare innovation on generation capabilities.
no code implementations • 23 Oct 2023 • Hao Guo, Collin Meese, Wanxin Li, Chien-Chung Shen, Mark Nejad
The results indicate that the proposed system can facilitate secure and decentralized federated learning for real-world traffic prediction tasks.
no code implementations • 31 May 2023 • Maryam Shaygan, Collin Meese, Wanxin Li, Xiaolong Zhao, Mark Nejad
Traffic prediction plays a crucial role in alleviating traffic congestion which represents a critical problem globally, resulting in negative consequences such as lost hours of additional travel time and increased fuel consumption.