无监督深度嵌入聚类分析

Nov, 2015

Unsupervised Deep Embedding for Clustering Analysis

Junyuan Xie, Ross Girshick, Ali Farhadi

TL;DR本文提出了一种同时学习特征表示和聚类分配的深度神经网络方法——深度嵌入聚类（DEC），该方法可将数据空间映射到低维特征空间，并在此优化聚类目标函数，实验结果表明，DEC在图像和文本语料库方面的表现显著超过现有的最先进方法。

Abstract

clustering is central to many data-driven application domains and has been studied extensively in terms of distance functions and grouping algorithms. Relatively little work has focused on learning representations for c