扩散图符合Nyström
Diffusion Maps meet Nyström
摘要：
扩散映射是一种新兴的数据驱动的非线性降维技术，对于分析动力系统的相干结构和非线性嵌入特别有用。然而，扩散映射算法的计算复杂度与观测的数量成比例。因此，长时间序列数据对快速有效的嵌入提出了重大挑战。我们建议将Nyström方法与扩散映射相结合，以减轻计算需求。我们实现了大约两到四倍的加速时，近似占主导地位的扩散图组件。
英文摘要：
Diffusion maps are an emerging data-driven technique for non-linear dimensionality reduction, which are especially useful for the analysis of coherent structures and nonlinear embeddings of dynamical systems. However, the computational complexity of the diffusion maps algorithm scales with the number of observations. Thus, long time-series data presents a significant challenge for fast and efficient embedding. We propose integrating the Nyström method with diffusion maps in order to ease the computational demand. We achieve a speedup of roughly two to four times when approximating the dominant diffusion map components.
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