Approximation Algorithms

Related lectures (26)

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Explores the integrality gap concept in set cover and multiplicative weights algorithms.

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Covers the concept of graph sketching with a focus on connected components.

Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.

Covers semi-definite programming and optimization over positive semidefinite cones.

Introduces Cartesian product and induction for proofs using integers and sets.

Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.

Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.

Covers the fundamentals of integer optimization, including integer programming, dynamic programming, and approximation algorithms.

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.