Lectures related to Dense Graphs: From Theory to Applications

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

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

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

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.

Covers graphical models for probability distributions and factor graphs representation.

Explores the Stein algorithm for polynomial identity testing and the minimization of a cut problem.

Explores the Cavity Method in Mean Field Theory, analyzing spins in an external field within a graph.

Explores graph coloring, directed cycles, LLL algorithm applications, and element dependencies in graphs.

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

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

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

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

Covers the Leighton-Rao algorithm for finding the sparsest cut in a graph, focusing on its steps and theoretical foundations.

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

Covers graph properties, representations, and traversal algorithms using BFS and DFS.

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

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

Covers the fundamentals of connectivity in graph theory, including paths, cycles, and spanning trees.

Explores Breadth-First Search and Dijkstra's algorithm for finding shortest paths in graphs.

Covers Cayley graphs, generators, group examples, and graph structures.