Theory of Computation: NP Complexity

Related lectures (28)

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Covers quantum algorithms, complexity classes, Grover's algorithm, and quantum information in computational complexity.

Examines NP problems, graph coloring, path optimization, and computational complexity distinctions in P and NP classes.

Explores cryptanalysis in public-key systems and the power of interaction in interactive proofs, covering CO-NP, NP classes, P vs. NP, and more.

Covers complexity classes, tractable problems, the class NP, NP-complete problems, and summarizes the concept of tractable problems.

Covers complexity classes, effect on computer time, tractable problems, class NP, and NP-complete problems.

Introduces complexity classes, including P and NP, and explores examples of easy and hard problems.

Explores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.

Covers the basics of computational complexity, including big O notation and complexity classes.

Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.

Covers algorithmic complexity and travel time analysis, focusing on measuring the time taken by algorithms and evaluating their performance.