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Analysis of Commute Time Embedding Based on Spectral Graph

스펙트럴 그래프 기반 Commute Time 임베딩 특성 분석

  • Received : 2013.09.04
  • Accepted : 2013.11.29
  • Published : 2014.01.31

Abstract

In this paper an embedding algorithm based on commute time is implemented by organizing patches according to the graph-based metric, and its performance is analyzed by comparing with the results of principal component analysis embedding. It is usual that the dimensionality reduction be done within some acceptable approximation error. However this paper shows the proposed manifold embedding method generates the intrinsic geometry corresponding to the signal despite severe approximation error, so that it can be applied to the areas such as pattern classification or machine learning.

Keywords

Commute time;Embedding;Manifold learning;Spectral graph;Graph Laplacian

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Cited by

  1. Proposing the Methods for Accelerating Computational Time of Large-Scale Commute Time Embedding vol.52, pp.2, 2015, https://doi.org/10.5573/ieie.2015.52.2.162