Reformulating Problems: Tools and Intuition

Related lectures (30)

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Explores expanders, Ramanujan graphs, eigenvalues, Laplacian matrices, and spectral properties.

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

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

Explores interlacing families of polynomials and 1-sided Ramanujan graphs, focusing on their properties and construction methods.

Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Explores the construction of Ramanujan graphs using polynomials and addresses challenges with the probabilistic method.

Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.

Explores spectral clustering theory, eigenvalue decomposition, Laplacian matrix, and practical applications in identifying clusters.

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.