图信号粗化:不规则域的降维

Pengfei Liu, Xiaohan Wang, Yuantao Gu
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引用次数: 11

摘要

图信号粗化是一种不规则域的降维方法。给定一个图信号,它的目标是同时获得图的粗版本和新图上的粗版本信号。在这项工作中,我们探索了图形信号粗化问题的设计空间,并表明解决方案可以分为四类。本文提出了一种采用逐次方法和基于谱域的信号粗化的有效方法来解决这一问题,这是第一个属于四类问题之一的方法。实验结果表明了该方法的有效性。
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Graph signal coarsening: Dimensionality reduction in irregular domain
Graph signal coarsening is a kind of dimensionality reduction in irregular domain. Given a graph signal, it aims to simultaneously obtain a coarser version of the graph and a coarsened signal on the new graph. In this work, we explore the design space for the graph signal coarsening problem and show that solutions can be split into four categories. We propose an effective method that uses a successive approach and spectral-domain-based signal coarsening for solving the problem, which is the first that falls into one of the four categories. Experiments are conducted to show the effectiveness of the proposed method.
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