Lectures related to Optimization of Pseudometrics in Graphs

Approximation Algorithms

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

Automorphism groups: Trees and Graphs

Explores automorphism groups in trees and graphs, focusing on ends and types of automorphisms.

Automorphism Groups: Trees and Graphs III

Explores automorphism groups of trees and graphs, including actions on trees and group homomorphisms.

Calibration Resolution: Hydrologic Parameters Optimization

Covers the calibration of hydrologic models through parameter optimization and post-simulation analysis.

Graphical Models: Representing Probabilistic Distributions

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

Graphs: Properties and Representations

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

Sparsest Cut: Bourgain's Theorem

Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.

Automorphism groups of trees and graphs II

Explores the uniqueness of trees, automorphism groups, Cayley-Abels graphs, and constructing vertex-transitive subgroups with prescribed local actions.

Automorphism groups of trees and graphs

Explores automorphisms of graphs, focusing on automorphism groups, Cayley-Abels graphs, and quasi-isometry.

Convex Functions

Covers the properties and operations of convex functions.

Real Functions: Graphs and Properties

Explores real functions, their graphs, properties, and transformations, including symmetry and surjection.

Graphs in Deep Learning: Applications and Techniques

Explores the role of graphs in deep learning, focusing on their structure, applications, and techniques for processing graph data.

Pseudorandomness: Theory and Applications

Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.

Graphs and Networks: Basics and Applications

Introduces the basics of graphs and networks, covering definitions, paths, trees, flows, circulation, and spanning trees.

Iterated Integrals: Order and Domains

Explores iterated integrals, order, domains, and symmetrical roles of variables in 2D space.

Applications between Sets: Functions and Graphs

Covers applications between sets, functions, and graphs, exploring injectivity, surjectivity, and bijectivity.

Handling Network Data

Explores handling network data, including types of graphs, real-world network properties, and node importance measurement.

Topological Scattering: From Graphs to Networks

Covers defining topological phases for photonic systems using unitary scattering matrices, transitioning from graphs to networks.

Partial Derivatives: Understanding Tangents

Explores partial derivatives and their role in determining tangents to graphs.

Renormalization: AQFT

Covers the concept of renormalization in Algebraic Quantum Field Theory.