摘要
Robotics&Machine Learning Daily News的一位新闻记者兼工作人员新闻编辑每日新闻-机器学习的新数据在一份新的报告中呈现。根据NewsRx编辑在中国郑州的新闻报道，研究表明：“垂直联合学习NG(VFL)可以在垂直分区的D Ataset上学习一个通用的机器学习模型。然而，VFL面临着以下棘手的问题：(1)训练和预测都非常容易受到脱节的影响；(2)大多数VFL方法都能支持特定的机器学习模型。”本研究的资金来源包括广西科技重点项目、国家自然科学基金(NSFC)、河南省高校重点科研项目。
Abstract
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.
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