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Spectral Graph Theory, the field of analyzing graphs based on the eigenvalues and eigenvectors associated to adjacency matrix, or the (normalized) Laplacian matrix have found abundance of applications in computing from Pseudorandomness, and Coding theory, all the way to approximation algorithms, hardness of approximation and approximate counting and sampling. In this course, I plan to have a modern take on spectral graph theory. There will be a few sections in the course where in each part I intend to start with classical results and then talk about more recent developments. Administrative Information
Instructor: Shayan Oveis Gharan
Assignments
Class Mailing list: cse599s_wi22 Related CoursesSimilar courses at other schools
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Tentative Schedule:
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