Examples of using Computational complexity in English and their translations into Korean
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Computational complexity.
Lower bound on computational complexity.
Computational complexity.
The majority of fast IDCT computing still incurs high computational complexity.
Computational complexity theory.
Juris Hartmanis andRichard E. Stearns(computational complexity theory).
Computational complexity classes.
Because of symmetry, and to reduce computational complexity, only one half of the system is modeled.
Computational complexity theory.
Thus, online or MMOG games often limit their memory and/ or computational complexity requirements.
Did you apply computational complexity theory in real life?
The concept of polynomial time leads to several complexity classes in computational complexity theory.
Computational complexity, proof complexity. .
Accordingly, online game or MMOG often limit their requirements to the computational complexity and/or memory.
In computational complexity theory, co-NP is a complexity class.
Accordingly, online games or MMOG games often limit their computational complexity and/ or memory requirements.
In the field of computational complexity, one of the main ideas is minimizing the cost(in terms of computational resources) to solve a problem.
Together with the Turing machine and counter-machine models, the RAM andRASP models are used for computational complexity analysis.
In terms of similar computational complexity, SM2 is much faster than RSA and DSA in processing private keys, thus a higher efficiency in encryption.
Moreover, some conventional security protocols are based on an assumption that high computational complexity is needed to break keys.
Algorithm analysis is an important part of a broader computational complexity theory, which provides theoretical estimates for the resources needed by any algorithm which solves a given computational problem.
An important point is that a data structure will return a model of the most general concept that can be implemented efficiently- computational complexity requirements are explicitly part of the concept definition.
Satisfying any one of the volume, variety, velocity, or computational complexity requirements is enough to make a Big Data infrastructure attractive.
Um, and can we use things like theoretical tools like regret sample complexity, um, as well as things like computational complexity to decide which algorithms are suitable for particular tasks.
To minimize the size of the index and computational complexity, statistics are often rounded.
An important first contribution was Blum's 1989 paper Lectures on a theory of computation and complexity over the reals(or an arbitrary ring) which extended the theories of computation and computational complexity from the standard discrete situation to study how these ideas can be developed in continuous domains such as the real number system.
The term"analysis of algorithms" was coined by Donald Knuth.[1] Algorithm analysis is an important part of a broader computational complexity theory, which provides theoretical estimates for the resources needed by any algorithm which solves a given computational problem.
In 1976, Adleman completed his thesis"Number Theoretic Aspects of Computational Complexities", received his PhD, and immediately secured a job as an assistant professor of mathematics at MIT.