Lectures related to Matching in hypergraphs

Explores linear programming duality, covering constraints, variables, solutions, and the relationship between primal and dual LP.

Introduces hypergraphs, generalizing graphs by allowing subsets of nodes to form edges and exploring their applications in various fields.

Covers hypergraphs, complete hypergraphs, link prediction, and scoring methods in network data analysis.

Explores directed networks with asymmetric relationships and hypergraphs that generalize graphs by allowing edges to connect any subset of nodes.

Covers the Erdős-Ko-Rado problem, intersecting set families, and selecting valid winners.

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

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

Explores tactical configurations, covering the minimal size of subsets needed to cover element sets and the concept of K-sets and base points.

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

Explores set coverings and uniformity theorems in hypergraphs, revealing insights into their structures.

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

Explores AI applications in chemistry, hypergraphs, single-step ritual synthesis, and retro-synthetic models evaluation.

Covers the independence polynomial of a dependency graph and related concepts such as graph coloring and directed graph properties.

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

Explores matching polynomials, emphasizing their real-rooted property and related bounds.

Explores statistical analysis of network data, covering graph structures, models, statistics, and sampling methods.

Explores Markov's theorem, Chernoff bound, and probability theory fundamentals, including good coloring, 2-colorable graphs, and rare events.

Covers recent advancements in the dimer model, emphasizing its applications in probability and conformal field theory.

Covers probabilistic methods in combinatorics, monochromatic edges, 2-colorable graphs, and good 2-colorings.

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