Interlacing Families and Ramanujan Graphs

Related lectures (29)

Page 3 of 3

Covers graphical models for probability distributions and factor graphs representation.

Explores the application of matrices and eigendecompositions in networks.

Explores Ramanujan graphs, generating functions, non-backtracking walks, and expander graphs in relation to NP-hard problems.

Explores properties of matrices, irreducibility, and graph connectivity in networked control systems.

Covers sparsest cut, NP-completeness, Bougains Theorem, and concurrent flow in graphs.

Explores coordination in networked control systems, graph theory, and consensus algorithms.

Covers girth, independence, probability, union bound, sets, and hypergraph recoloring.

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.

Explores Markov chains, focusing on the coloring problem and algorithm analysis.