Space Complexity in Polynomial Calculus

In current, there are complex relationship between the assets of information security product. According to this characteristic, we propose a new asset recognition algorithm (ART) on the improvement of the C4.5 decision tree algorithm, and analyze the computational complexity and space complexity of the proposed algorithm. Finally, we demonstrate that our algorithm is more precise than C4.5 algorithm in asset recognition by an application example whose result verifies the availability of our algorithm.Keywordsdecision tree, information security product, asset recognition, C4.5

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On the time and space complexity of randomized test-and-set

Proceedings of the 2012 ACM symposium on Principles of distributed computing - PODC '12 ◽

10.1145/2332432.2332436 ◽

2012 ◽

Cited By ~ 14

Author(s):

George Giakkoupis ◽

Philipp Woelfel

Keyword(s):

Space Complexity ◽

Time And Space ◽

Time And Space Complexity ◽

Randomized Test

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On the Time-Space Complexity of Geometric Elimination Procedures

Applicable Algebra in Engineering Communication and Computing ◽

10.1007/s002000000046 ◽

2001 ◽

Vol 11 (4) ◽

pp. 239-296 ◽

Cited By ~ 16

Author(s):

Joos Heintz ◽

Guillermo Matera ◽

Ariel Waissbein

Keyword(s):

Space Complexity ◽

Time Space

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How significant are the known collision and element distinctness quantum algorithms?

Quantum Information and Computation ◽

10.26421/qic4.3-5 ◽

2004 ◽

Vol 4 (3) ◽

pp. 201-206

Author(s):

L. Grover ◽

T. Rudolph

Keyword(s):

Search Algorithm ◽

Quantum Algorithms ◽

Search Space ◽

Space Complexity ◽

Quantum Search ◽

Quantum Search Algorithm ◽

Time Space ◽

Simple Quantum ◽

Structured Problems ◽

Better Than

Quantum search is a technique for searching $N$ possibilities for a desired target in $O(\sqrt{N})$ steps. It has been applied in the design of quantum algorithms for several structured problems. Many of these algorithms require significant amount of quantum hardware. In this paper we propose the criterion that an algorithm which requires $O(S)$ hardware should be considered significant if it produces a speedup of better than $O\left(\sqrt{S}\right)$ over a simple quantum search algorithm. This is because a speedup of $O\left(\sqrt{S}\right)$ can be trivially obtained by dividing the search space into $S$ separate parts and handing the problem to $S$ independent processors that do a quantum search (in this paper we drop all logarithmic factors when discussing time/space complexity). Known algorithms for collision and element distinctness exactly saturate the criterion.

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