- Industry: Technology
- Number of terms: 2742
- Number of blossaries: 0
- Company Profile:
The National Institute of Standards and Technology (NIST) — known between 1901 and 1988 as the National Bureau of Standards (NBS) — is a measurement standards laboratory and a non-regulatory agency of the United States Department of Commerce. The institute's official mission is to promote U.S. ...
A terribly inefficient sort algorithm that randomly swaps items until they are in order.
Industry:Computer science
A terribly inefficient sort algorithm that repeatedly generates a random permutation of the items until the items are in order.
Industry:Computer science
A terribly inefficient sort algorithm that swaps the top and bottom items if needed, then (recursively) sorts the bottom two-thirds, then the top two-thirds, then the bottom two-thirds again.
Industry:Computer science
A theorem giving a solution in asymptotic terms for recurrence relations of the form T(n) = aT(n/b) + f(n) where a ≥ 1 and b > 1 are constants and n/b means either ⌊ n/b⌋ or ⌊ n/b⌋.
Industry:Computer science
A theorem showing that two complexity classes are distinct. Most separation theorems have been proved by diagonalization.
Industry:Computer science
A theoretical agent that uses information about the past moves of an on-line algorithm to choose inputs that force the worst-case cost of the algorithm.
Industry:Computer science
A theoretical measure of the execution of an algorithm, usually the time or memory needed, given the problem size n, which is usually the number of items. Informally, saying some equation f(n) = o(g(n)) means f(n) becomes insignificant relative to g(n) as n approaches infinity. The notation is read, "f of n is little oh of g of n". Formal Definition: f(n) = o(g(n)) means for all c > 0 there exists some k > 0 such that 0 ≤ f(n) < cg(n) for all n ≥ k. The value of k must not depend on n, but may depend on c.
Industry:Computer science
A theoretical measure of the execution of an algorithm, usually the time or memory needed, given the problem size n, which is usually the number of items. Informally, saying some equation f(n) = O(g(n)) means it is less than some constant multiple of g(n). The notation is read, "f of n is big oh of g of n". Formal Definition: f(n) = O(g(n)) means there are positive constants c and k, such that 0 ≤ f(n) ≤ cg(n) for all n ≥ k. The values of c and k must be fixed for the function f and must not depend on n.
Industry:Computer science
A theoretical measure of the execution of an algorithm, usually the time or memory needed, given the problem size n, which is usually the number of items. Informally, saying some equation f(n) = Θ (g(n)) means it is within a constant multiple of g(n). The equation is read, "f of n is theta g of n". Formal Definition: f(n) = Θ (g(n)) means there are positive constants c<sub>1</sub>, c<sub>2</sub>, and k, such that 0 ≤ c<sub>1</sub>g(n) ≤ f(n) ≤ c<sub>2</sub>g(n) for all n ≥ k. The values of c<sub>1</sub>, c<sub>2</sub>, and k must be fixed for the function f and must not depend on n.
Industry:Computer science
A theoretical measure of the execution of an algorithm, usually the time or memory needed, given the problem size n, which is usually the number of items. Informally, saying some equation f(n) = ω (g(n)) means g(n) becomes insignificant relative to f(n) as n goes to infinity. Formal Definition: f(n) = ω (g(n)) means that for any positive constant c, there exists a constant k, such that 0 ≤ cg(n) < f(n) for all n ≥ k. The value of k must not depend on n, but may depend on c.
Industry:Computer science
