Graphs and matrices

Related lectures (30)

Page 3 of 3

Explores automorphism groups in trees and graphs, focusing on ends and types of automorphisms.

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Introduces the basics of graph algorithms, covering traversal, representation, and data structures for BFS and DFS.

Explores the diagonalization of matrices and the conditions for exact diagonalization, with examples demonstrating the process.

Explores automorphism groups of trees and graphs, including actions on trees and group homomorphisms.

Explores pseudorandomness and the Expander Mixing Lemma in the context of d-regular graphs.

Explores handling network data, including types of graphs, real-world network properties, and node importance measurement.

Covers matrices, linear applications, vector spaces, and bijective functions.

Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.

Explores the Laplacian matrix, time-varying consensus theorems, and balanced graphs in networked control systems.