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Tags

#computation #social-choice

Question

Formally, an algorithm is* polynomial* if ^{}[...] Here, O(n^{ k} ) denotes the class of all functions that, for large values of n, grow no faster than c · n^{ k} for some constant number c (this is the “Big-O notation”). For instance, when k = 1, the running time is linear, and when k = 2, the running time is quadratic in n.

Answer

there exists a k ∈\(\mathbb{N}\) such that its running time is in O(n^{ k} ), where n is the size of the input.

Tags

#computation #social-choice

Question

Formally, an algorithm is* polynomial* if ^{}[...] Here, O(n^{ k} ) denotes the class of all functions that, for large values of n, grow no faster than c · n^{ k} for some constant number c (this is the “Big-O notation”). For instance, when k = 1, the running time is linear, and when k = 2, the running time is quadratic in n.

Answer

?

Tags

#computation #social-choice

Question

Formally, an algorithm is* polynomial* if ^{}[...] Here, O(n^{ k} ) denotes the class of all functions that, for large values of n, grow no faster than c · n^{ k} for some constant number c (this is the “Big-O notation”). For instance, when k = 1, the running time is linear, and when k = 2, the running time is quadratic in n.

Answer

there exists a k ∈\(\mathbb{N}\) such that its running time is in O(n^{ k} ), where n is the size of the input.

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Formally, an algorithm is polynomial if there exists a k ∈\(\mathbb{N}\) such that its running time is in O(n k ), where n is the size of the input. Here, O(n k ) denotes the class of all functions that, for large values of n, grow no faster than c · n k for some constant number c (this is the “Big-O notation”). For instance, wh

Formally, an algorithm is polynomial if there exists a k ∈\(\mathbb{N}\) such that its running time is in O(n k ), where n is the size of the input. Here, O(n k ) denotes the class of all functions that, for large values of n, grow no faster than c · n k for some constant number c (this is the “Big-O notation”). For instance, wh

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

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