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Related lectures (28)
Approximation Algorithms
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Linear Programming Duality
Covers linear programming duality and complementary slackness condition.
Unweighted Bipartite Matching
Introduces unweighted bipartite matching and its solution using linear programming and the simplex method.
Differential Forms Integration
Covers the integration of differential forms on smooth manifolds, including the concepts of closed and exact forms.
Set Cover: Integrality Gap
Explores the integrality gap concept in set cover and multiplicative weights algorithms.
Linear Programming: Weighted Bipartite Matching
Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.
Optimization Methods: Theory Discussion
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.
Functions: Definitions and Notations
Covers the generalities of functions, including the definition of an application between sets and the uniqueness of elements in the image set.
Cartesian Product and Induction
Introduces Cartesian product and induction for proofs using integers and sets.
Primal-dual Optimization: Fundamentals
Explores primal-dual optimization, minimax problems, and gradient descent-ascent methods for optimization algorithms.
Primal-dual optimization: Theory and Computation
Explores primal-dual optimization, conjugation of functions, strong duality, and quadratic penalty methods in data mathematics.
Optimality Conditions in Linear Optimization
MOOC: Optimization: principles and algorithms - Linear optimization
Covers optimality conditions, strong duality, and complementarity slackness in linear optimization.
Linear Programming: Two-phase Simplex Algorithm
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Covers the application of the two-phase Simplex algorithm to solve linear programming problems.
Optimal Decision Making: Sensitivity Analysis
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Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.
Network Flows Meets Simplex
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Explores network flows, simplex method, linear programming, tree solutions, and dual solutions in optimization problems.
Lagrangian Duality: Theory and Applications
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Explores Lagrangian duality in convex optimization, discussing strong duality, dual solutions, and practical applications in second-order cone programs.
Relations Between Events
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Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.
Optimization Problems: Path Finding and Portfolio Allocation
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Covers optimization problems in path finding and portfolio allocation.
Duality in Linear Programming
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Explores the concept of duality in linear programming, discussing the relationship between primal and dual problems.
Duality: Economic Interpretation
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Explores duality in linear programming, strong duality, complementary slackness, and the economic interpretation of dual variables as prices.
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