Lectures related to Edge cover

Covers the Simplex algorithm for function minimization with linear constraints.

Explores the Cartesian product operation on graphs and introduces the concept of cubes.

Covers linear programming duality and complementary slackness condition.

Covers soft graphs and induced subgraphs in graph theory.

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

Distinguishes between subgraphs and induced subgraphs in graph theory, illustrating the construction of minimal spanning trees.

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

Covers the basics of graph algorithms, focusing on modeling and representation of graphs in memory.

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