Pseudo Randomness in Graphs

Related lectures (28)

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Examines conditions for the existence of invertible matrices satisfying specific matrix equations involving eigenvalues.

Introduces linear combinations in vector spaces, operations, and polynomials of degree 2.

Explores the construction of graphs through martingales and polynomials, offering insights into solving eigenvalue problems with low probabilities.

Introduces Spectral Graph Theory, exploring eigenvalues and eigenvectors' role in graph properties.

Explores polynomial operations, properties, and subspaces in vector spaces.

Covers handling network data, types of graphs, centrality measures, and properties of real-world networks.

Explores complex roots, polynomials, and factorizations, including roots of unity and the fundamental theorem of algebra.

Introduces abstract concepts in linear algebra, focusing on operations with vectors and matrices.

Explores interlacing families, Ramanujan graphs, and their construction using signed adjacency matrices.

Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.