<p>Two sources: The <a href="http://rads.stackoverflow.com/amzn/click/0821803158">Fan Chung book on spectral graph theory</a>  and <a href="http://www.cs.yale.edu/homes/spielman/sgta/">Dan Spielman's notes</a> on the same.</p>

CC BY-SA 2.5
2010-09-10T20:51:31.260Z
2010-09-10T20:51:31.260Z
Suresh Venkat
<p>I really like <a href="http://www.cs.elte.hu/~lovasz/erdos.pdf">L. Lovász: Random walks on graphs: a survey</a></p>

CC BY-SA 2.5
2010-09-10T21:04:31.407Z
2010-09-10T21:04:31.407Z
Ryan Williams
<p>There is a new upcoming book on <a href="http://www.cc.gatech.edu/~vempala/spectralbook.html">Spectral Algorithms</a> by Ravi Kannan and Santosh Vempala covering several latest developments. It covers several applications of spectral methods, algorithms for estimating spectral parameters and low rank approximation of matrices.</p>

CC BY-SA 2.5
2010-09-10T21:41:44.553Z
2010-09-10T21:41:44.553Z
Shiva Kintali
<p>Beside Fan Chung's book, I also like <a href="http://rads.stackoverflow.com/amzn/click/0521458978">Biggs'</a>; it's short and sweet. I heard that <a href="http://rads.stackoverflow.com/amzn/click/3527296859">Cvetković-Doob-Sachs</a> is supposed to be encyclopedic but I haven't had a chance to check it out yet. Yes, I agree with Ryan than Lovasz' survey is a pleasure to read (so do most of his surveys).</p>

CC BY-SA 2.5
2010-09-10T21:13:22.880Z
I have seen Cvetković-Doob-Sachs and agree that it is encyclopedic. Lots of examples worked out. Expensive though...
Ryan Williams
CC BY-SA 2.5
2010-09-10T21:06:04.543Z
2010-09-10T21:06:04.543Z
Hung Q. Ngo
<p>Godsil and Royle's Algebraic Graph Theory is a good book too, though it has more than just spectral graph theory.</p>

CC BY-SA 2.5
2010-09-10T21:18:47.920Z
2010-09-10T21:18:47.920Z
Robin Kothari
<p>I found this lecture note to be of great help <a href="https://arxiv.org/pdf/1608.04845.pdf" rel="nofollow noreferrer">Michael W. Mahoney</a></p>

CC BY-SA 3.0
2018-04-06T11:10:40.680Z
2018-04-06T11:10:40.680Z
Subhadeep
<p>What are the basic references? Are there any good, high-level surveys of SGT and its applications to CS in general and machine learning more specifically?</p>

<reference-request><spectral-graph-theory>
Introduction to spectral graph theory
Alexandre Passos
# Introduction to spectral graph theory

(Asked by: username_0 on 2010-09-10)

What are the basic references? Are there any good, high-level surveys of SGT and its applications to CS in general and machine learning more specifically?

**Tags:** reference-request, spectral-graph-theory

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## 6 answers

### Answer by username_1 on 2010-09-10. Score: 19

Two sources: The [Fan Chung book on spectral graph theory](http://rads.stackoverflow.com/amzn/click/0821803158) and [Dan Spielman's notes](http://www.cs.yale.edu/homes/spielman/sgta/) on the same.


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### Answer by username_3 on 2010-09-10. Score: 15

There is a new upcoming book on [Spectral Algorithms](http://www.cc.gatech.edu/~vempala/spectralbook.html) by Ravi Kannan and Santosh Vempala covering several latest developments. It covers several applications of spectral methods, algorithms for estimating spectral parameters and low rank approximation of matrices.


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### Answer by username_2 on 2010-09-10. Score: 12

I really like [L. Lovász: Random walks on graphs: a survey](http://www.cs.elte.hu/~lovasz/erdos.pdf)


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### Answer by username_4 on 2010-09-10. Score: 10

Beside Fan Chung's book, I also like [Biggs'](http://rads.stackoverflow.com/amzn/click/0521458978); it's short and sweet. I heard that [Cvetković-Doob-Sachs](http://rads.stackoverflow.com/amzn/click/3527296859) is supposed to be encyclopedic but I haven't had a chance to check it out yet. Yes, I agree with Ryan than Lovasz' survey is a pleasure to read (so do most of his surveys).

> **Comments:**
> **username_2**: I have seen Cvetković-Doob-Sachs and agree that it is encyclopedic. Lots of examples worked out. Expensive though...  

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### Answer by username_5 on 2010-09-10. Score: 9

Godsil and Royle's Algebraic Graph Theory is a good book too, though it has more than just spectral graph theory.


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### Answer by username_6 on 2018-04-06. Score: 0

I found this lecture note to be of great help [Michael W. Mahoney](https://arxiv.org/pdf/1608.04845.pdf)


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