NP-completeness and Parameterized complexity

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between NP-completeness and Parameterized complexity

NP-completeness vs. Parameterized complexity

In computational complexity theory, an NP-complete decision problem is one belonging to both the NP and the NP-hard complexity classes. In computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according to their inherent difficulty with respect to multiple parameters of the input or output.

Similarities between NP-completeness and Parameterized complexity

NP-completeness and Parameterized complexity have 10 things in common (in Unionpedia): Computational complexity theory, Dominating set, Graph coloring, Independent set (graph theory), NP-hardness, P versus NP problem, Parameterized complexity, Reduction (complexity), Time complexity, Vertex cover.

Computational complexity theory

Computational complexity theory is a branch of the theory of computation in theoretical computer science that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other.

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Dominating set

In graph theory, a dominating set for a graph G.

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Graph coloring

In graph theory, graph coloring is a special case of graph labeling; it is an assignment of labels traditionally called "colors" to elements of a graph subject to certain constraints.

Graph coloring and NP-completeness · Graph coloring and Parameterized complexity · See more »

Independent set (graph theory)

In graph theory, an independent set or stable set is a set of vertices in a graph, no two of which are adjacent.

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NP-hardness

NP-hardness (''n''on-deterministic ''p''olynomial-time hardness), in computational complexity theory, is the defining property of a class of problems that are, informally, "at least as hard as the hardest problems in NP".

NP-completeness and NP-hardness · NP-hardness and Parameterized complexity · See more »

P versus NP problem

The P versus NP problem is a major unsolved problem in computer science.

NP-completeness and P versus NP problem · P versus NP problem and Parameterized complexity · See more »

Parameterized complexity

In computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according to their inherent difficulty with respect to multiple parameters of the input or output.

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Reduction (complexity)

In computability theory and computational complexity theory, a reduction is an algorithm for transforming one problem into another problem.

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Time complexity

In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.

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Vertex cover

In the mathematical discipline of graph theory, a vertex cover (sometimes node cover) of a graph is a set of vertices such that each edge of the graph is incident to at least one vertex of the set.

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The list above answers the following questions

What NP-completeness and Parameterized complexity have in common
What are the similarities between NP-completeness and Parameterized complexity

NP-completeness and Parameterized complexity Comparison

NP-completeness has 107 relations, while Parameterized complexity has 19. As they have in common 10, the Jaccard index is 7.94% = 10 / (107 + 19).

References

This article shows the relationship between NP-completeness and Parameterized complexity. To access each article from which the information was extracted, please visit:

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