一种快速的流形降维学习算法

Yu Liang, S. Furao, Jinxi Zhao, Yi Yang
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引用次数: 1

摘要

本文提出了一种新的流形学习方法——“soinmanifold”。传统的流形学习方法需要大量的计算量和合适的先验参数。这在一定程度上限制了流形学习可能应用的领域。然而,对于高维输入,我们的方法可以在高维空间中生成低维流形并自动确定其固有维数。然后我们会用这个流形快速地进行降维。实验结果表明,该方法能够以较少的时间和内存获得较好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fast Manifold Learning Algorithm for Dimensionality Reduction
This paper proposes a new manifold learning method called "Soinnmanifold". Traditional manifold learning method needs a lot of computation and appropriate priori parameters. This has somewhat restricted the domains in which manifold learning can potentially be applied. However, with the high-dimensional inputs, our method can generate a lowdimensional manifold in the high-dimensional space and determine the intrinsic dimension automatically. Then we will use this manifold to do dimensionality reduction quickly. Experiments demonstrate that our method can get promising results with less time and memory.
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