首页|Findings from Zhengzhou University of Light Industry in the Area of Machine Lear ning Described (A Fault-tolerant and Scalable Boosting Method Over Vertically Pa rtitioned Data)
Findings from Zhengzhou University of Light Industry in the Area of Machine Lear ning Described (A Fault-tolerant and Scalable Boosting Method Over Vertically Pa rtitioned Data)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting out of Zhengzhou, People’s R epublic of China, by NewsRx editors, research stated, “Vertical federated learni ng (VFL) can learn a common machine learning model over vertically partitioned d atasets. However, VFL are faced with these thorny problems: (1) both the trainin g and prediction are very vulnerable to stragglers; (2) most VFL methods can onl y support a specific machine learning model.” Funders for this research include Guangxi Science and Technology Major Project, National Natural Science Foundation of China (NSFC), Key scientific research pro ject of colleges and universities in Henan Province.
ZhengzhouPeople’s Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningZhengzhou University of L ight Industry
NETL
NSTL
