Concept

Duality (mathematics)

Related lectures (31)

Explores Linear Programming Duality, covering weak duality, strong duality, Lagrange multipliers interpretation, and optimization constraints.

Covers linear programming duality and complementary slackness condition.

Explains the process of finding an initial Basic Feasible Solution for linear optimization problems using the Simplex Algorithm.

Covers weak and strong duality in optimization problems, focusing on Lagrange multipliers and KKT conditions.

Explores duality in linear programming, strong duality, complementary slackness, and the economic interpretation of dual variables as prices.

Covers the application of the two-phase Simplex algorithm to solve linear programming problems.

Covers the recap of Support Vector Regression with a focus on convex optimization and its equivalence to Gaussian Process Regression.

Covers Lagrangian, dual function, dual problem, weak duality, and optimality.

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

Explores duality in network optimization problems with examples and step-by-step explanations.

Explores the concept of duality in linear programming, discussing the relationship between primal and dual problems.

Covers the application of Serre Duality in the general case, focusing on line bundles and core concepts.

Explains the cup and cap product in algebraic topology and their relation to homology groups.

Discusses the Fresnel coefficients for TM polarization and their application to the solution.

Explores the applications of Serre duality in Enriques-Severi-Zariski lemma, foliations, and Riemann-Roch theorem.

Explores duality theorems in linear programming, emphasizing optimal solutions and degeneracies.

Explores the formulation of the auxiliary problem in linear optimization and its role in optimal decision-making.

Explores dual translations in linear programming, emphasizing primal and dual formulations and the significance of invertible submatrices.

Delves into duality in optimization, weak duality, cost certificates, and transforming non-linear programs into linear ones.

Covers the proof of strong duality in optimization problems and provides examples of Rayleigh quotient optimization.