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I am aware that there is already a similar question here, but unfortunately I find the discussion there to be beyond my grasp.

I am looking for an intuitive explanation of spectral graph theory, as well as some examples of its applications in practice. Specifically, I want to know how it might or might not be relevant to image processing and machine learning.

I am comfortable with freshman-level mathematics (such as linear algebra and partial differential equations), but I will be lost if you invoke more advanced concepts in your answer.

Thank you in advance for your help!

M.Y. Babt
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    Lecture notes (introduction) from a big name in the area (Dan Spielman): http://www.cs.yale.edu/homes/spielman/eigs/lect1.pdf – Clement C. Feb 23 '16 at 17:18
  • @ClementC. I tried reading the document you linked to, but unfortunately I think it went over my head :-( – M.Y. Babt Feb 24 '16 at 17:21
  • https://www.youtube.com/watch?v=8XJes6XFjxM This video is a great introduction and really shows how amazing this area of mathematics is! – EHH Mar 04 '16 at 12:18

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