Examples of using Computational complexity theory in English and their translations into Greek
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The geometrical construct of that game has applications in Computational Complexity Theory.
The field of computational complexity theory categorizes decidable decision problems by how difficult they are to solve.
The set of all recursive functions is known as R in computational complexity theory.
Goldwasser's research areas include computational complexity theory, cryptography and computational number theory. .
This was proven by Gabriel Lamé in 1844, andmarks the beginning of computational complexity theory.
In particular, computational complexity theory determines the practical limits on what computers can and cannot do.
The Blum axioms can be used to define an abstract computational complexity theory on the set of computable functions.
In computational complexity theory and computability theory, a counting problem is a type of computational problem.
The expressive power of various forms of second-order logic on finite structures is intimately tied to computational complexity theory.
In computational complexity theory, the problem of determining the complexity of a computable function is known as a function problem.
This proof, published by Gabriel Lamé in 1844,represents the beginning of computational complexity theory, and also the first practical application of the Fibonacci numbers.
In computational complexity theory, it is usually implicitly assumed that any string in{0, 1}* represents an instance of the computational problem in question.
It started as a part of combinatorics and graph theory, but is now viewed as a branch of applied mathematics and computer science, related to operations research,algorithm theory and computational complexity theory.
In computational complexity theory and computability theory, a search problem is a type of computational problem represented by a binary relation.
Computer science has many sub-fields; some emphasize the computation of specific results(such as computer graphics),while others relate to properties of computational problems(such as computational complexity theory).
In computational complexity theory, a computational resource is a resource used by some computational model in the solution of computational problems….
The relation between the complexity classes P andNP is studied in computational complexity theory, the part of the theory of computation dealing with the resources required during computation to solve a given problem.
In computational complexity theory, a promise problem is a generalization of a decision problem where the input is promised to belong to a subset of all possible inputs.[1] Unlike decision problems, the yes instances(the inputs for which an algorithm must return yes) and no instances do not exhaust the set of all inputs.
In computability theory and computational complexity theory, a model of computation is the definition of the set of allowable operations used in computation and their respective costs.
In computational complexity theory the Blum axioms or Blum complexity axioms are axioms that specify desirable properties of complexity measures on the set of computable functions.
In computational complexity theory, computer algorithms of exponential complexity require an exponentially increasing amount of resources(e.g. time, computer memory) for only a constant increase in problem size.
Some, such as computational complexity theory, which studies fundamental properties of computational problems, are highly abstract, while others, such as computer graphics, emphasize real-world applications.
Some fields such as computational complexity theory which explores the fundamental properties of computational problems are highly abstract, whilst fields such as computer graphics emphasise real-world applications.
Some fields, such as computational complexity theory(which explores the fundamental properties of computational and intractable issues), are very abstract, whilst fields such as computer graphics emphasize actual-globe visual applications.
Some fields, such as computational complexity theory(which explores the basic properties of computational and intractable problems), are extremely abstract, although fields such as computer graphics emphasize real-globe visual applications.
Some fields, such as computational complexity theory(which explores the basic properties of computational and intractable difficulties), are highly abstract, while fields such as personal computer graphics emphasize true-planet visual applications.
Some fields, such as computational complexity theory(which explores the fundamental properties of computational and intractable troubles), are extremely abstract, even though fields such as computer graphics emphasize real-world visual applications.
Some areas, such as computational complexity theory(which explores the intractable problems and fundamental properties of computational and intractable), are highly theoretical, while areas such as computer graphics highlight real-world visual implementation.