对“包围投影半监督图像分类“一文的评论
Comment on "Ensemble Projection for Semi-supervised Image Classification"
摘要：
在Dai及其同事的一系列论文[1，2]中，为半监督和无监督学习引入了特征映射（或内核）。该特征图是从在不使用地面真实类标签的情况下训练的分类器集合的输出构建的。在这篇评论中，我们分析了这一系列论文的最新版本，即所谓的包围投影[2]。我们证明了[2]中报道的结果没有很好地进行，并且包围投影对于半监督学习表现不佳。
英文摘要：
In a series of papers by Dai and colleagues [1,2], a feature map (or kernel) was introduced for semi- and unsupervised learning. This feature map is build from the output of an ensemble of classifiers trained without using the ground-truth class labels. In this critique, we analyze the latest version of this series of papers, which is called Ensemble Projections [2]. We show that the results reported in [2] were not well conducted, and that Ensemble Projections performs poorly for semi-supervised learning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
