'Spectral graph theory' diaporamas de présentation

Spectral graph theory - PowerPoint PPT Presentation

15-251

15-251

15-251. Great Theoretical Ideas in Computer Science. Anupam Gupta Danny Sleator. Graphs II. Lecture 19, October 26, 2010. Recap. Cayley’s Formula. The number of labeled trees on n nodes is n n-2. A graph is planar if. it can be drawn in the plane without crossing edges.

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593 views • 41 slides
spectral clustering between friends

spectral clustering between friends

spectral clustering between friends. One of these things is not like the other…. spectral clustering (a la Ng-Jordan-Weiss). data. similarity graph. edges have weights w ( i , j ). e.g. the Laplacian. diagonal matrix D. Normalized Laplacian :. energy. Normalized Laplacian :.

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567 views • 22 slides
spectral clustering between friends

spectral clustering between friends

spectral clustering between friends. One of these things is not like the other…. spectral clustering (a la Ng-Jordan-Weiss). data. similarity graph. edges have weights w ( i , j ). e.g. the Laplacian. diagonal matrix D. Normalized Laplacian :. energy. Normalized Laplacian :.

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594 views • 22 slides
Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More*

Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More*

Faster Algorithms for Computing the Stationary Distribution, Simulating Random Walks, and More*. * Directed Spectral Graph Theory 101. Michael Cohen. Jonathan Kelner. John Peebles. Richard Peng. Aaron Sidford. Adrian Vladu. Shortest Paths Spanning Trees Max Flow Min Cost Flow ….

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239 views • 20 slides
Eigenvalues of a Graph

Eigenvalues of a Graph

Eigenvalues of a Graph. Scott Grayson. Adjacency Matrix. source: http://www.stoimen.com/blog/2012/08/31/computer-algorithms-graphs-and-their-representation/. Properties of an Adjancency Matrix. Symmetric n eigenvalues corresponding to n eigenvectors Zero Trace (sum of the diagonal)

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605 views • 18 slides
Large Graph Mining: Power Tools and a Practitioner’s guide

Large Graph Mining: Power Tools and a Practitioner’s guide

Large Graph Mining: Power Tools and a Practitioner’s guide. Christos Faloutsos Gary Miller Charalampos (Babis) Tsourakakis CMU. Outline. Introduction – Motivation Task 1: Node importance Task 2: Community detection Task 3: Recommendations Task 4: Connection sub-graphs

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262 views • 14 slides
Overview of Markov chains

Overview of Markov chains

Overview of Markov chains. David Gleich Purdue University Network & Matrix Computations Computer Science 15 Sept 2011. Lots of words. transient recurrent primitive regular ergodic periodic irreducible P erron root. P erron vector stationary distribution

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216 views • 7 slides

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