Concept

Complement graph

Related lectures (29)

Graph Algorithms: Modeling and Traversal

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

Graph Algorithms: BFS and DFS

Explores graph algorithms like BFS and DFS, discussing shortest paths, spanning trees, and data structures' role.

Stochastic Block Model: Community Detection

Covers the Stochastic Block Model for community detection.

Linear Algebra: Matrix Representation

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.

Vector Algebra: Scalar Product

Explores the scalar product of vectors, including properties and calculation methods.

Linear Transformations: Matrices and Kernels

Covers linear transformations, matrices, kernels, and properties of invertible matrices.

Geometry of the Triangle

Covers the geometry of the triangle, including inequalities, heights, and centers.

Counterfactuals: SEM and D-Separation

Explores counterfactuals in SEMs and D-Separation in graphical models.

Stochastic Block Model: Community Detection

Covers the Stochastic Block Model for community detection, focusing on the detection of communities, clusters, and groups.

Parts and Vectors in Coordinates

Covers landmarks, coordinate systems, frames, and terminology in coordinates, emphasizing geometric angles and orthogonal vectors.

Mathematical Analysis: Functions and Composition

Covers the analysis of functions, composition, and mathematical induction.

Projections and Symmetries

Explores projections on lines and symmetries in 2D space, emphasizing fixed points and symmetric matrices.

Graph Algorithms: Basics

Introduces the basics of graph algorithms, covering traversal, representation, and data structures for BFS and DFS.

Connectivity in Graph Theory

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

Graph Processing: Oracle Labs PGX

Covers graph processing with a focus on Oracle Labs PGX, discussing graph analytics, databases, algorithms, and distributed analytics challenges.

Derivatives and Continuity in Multivariable Functions

Covers derivatives and continuity in multivariable functions, emphasizing the importance of partial derivatives.

Graphs: BFS

Introduces elementary graph algorithms, focusing on Breadth-First Search and Depth-First Search.

Differentiable Functions and Lagrange Multipliers

Covers differentiable functions, extreme points, and the Lagrange multiplier method for optimization.

Graph Neural Networks: Interconnected World

Explores learning from interconnected data with graphs, covering modern ML research goals, pioneering methods, interdisciplinary applications, and democratization of graph ML.

Union-Find and Prim's Algorithm

Introduces Union-Find data structure and Prim's algorithm for minimum spanning trees in graphs, exploring cuts and historical origins.