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Average-case complexity and Randomized algorithm

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

Difference between Average-case complexity and Randomized algorithm

Average-case complexity vs. Randomized algorithm

In computational complexity theory, the average-case complexity of an algorithm is the amount of some computational resource (typically time) used by the algorithm, averaged over all possible inputs. A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure.

Similarities between Average-case complexity and Randomized algorithm

Average-case complexity and Randomized algorithm have 10 things in common (in Unionpedia): Algorithm, Computational complexity theory, Cryptography, Donald Knuth, NP (complexity), P (complexity), Probabilistic analysis of algorithms, Quicksort, Randomized algorithm, Worst-case complexity.

Algorithm

In mathematics and computer science, an algorithm is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation.

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Computational complexity theory

In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other.

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Cryptography

Cryptography, or cryptology (from κρυπτός|translit.

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Donald Knuth

Donald Ervin Knuth (born January 10, 1938) is an American computer scientist and mathematician.

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NP (complexity)

In computational complexity theory, NP (nondeterministic polynomial time) is a complexity class used to classify decision problems.

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P (complexity)

In computational complexity theory, P, also known as PTIME or DTIME(nO(1)), is a fundamental complexity class.

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Probabilistic analysis of algorithms

In analysis of algorithms, probabilistic analysis of algorithms is an approach to estimate the computational complexity of an algorithm or a computational problem.

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Quicksort

Quicksort is an efficient, general-purpose sorting algorithm.

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Randomized algorithm

A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure.

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Worst-case complexity

In computer science (specifically computational complexity theory), the worst-case complexity measures the resources (e.g. running time, memory) that an algorithm requires given an input of arbitrary size (commonly denoted as in asymptotic notation).

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The list above answers the following questions

Average-case complexity and Randomized algorithm Comparison

Average-case complexity has 27 relations, while Randomized algorithm has 119. As they have in common 10, the Jaccard index is 6.85% = 10 / (27 + 119).

References

This article shows the relationship between Average-case complexity and Randomized algorithm. To access each article from which the information was extracted, please visit: