Lectures related to Message passing in graphical models

Introduces unweighted bipartite matching and its solution using linear programming and the simplex method.

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

Covers the Stochastic Block Model and its application in community detection, exploring its mathematical formulation and challenges.

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

Covers graphical models for probability distributions and factor graphs representation.

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

Covers polynomial identity testing using oracles and random point evaluation, with applications in graph theory and algorithmic aspects.

Covers the concept of matroids, focusing on matroid intersection and the properties of subsets of a ground set.

Explores Belief Propagation for graph coloring and its convergence properties.

Discusses the Ford-Fulkerson method and strongly connected components in graph algorithms.

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

Introduces the probabilistic method to prove existence results in graph theory.

Discusses Union-Find data structures and Minimum Spanning Trees, covering algorithms and their applications in network design and optimization.

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Covers the basics of information theory, entropy, and fixed points in graph colorings and the Ising model.

Covers stochastic properties, network structures, models, statistics, centrality measures, and sampling methods in network data analysis.

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

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

Covers linear programming duality and complementary slackness condition.

Explores the Szemerédi Regularity Lemma, e-regularity in bipartite graphs, supergraph structure, and induction techniques.