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58 relations: Advice (complexity), Alternating Turing machine, Boolean circuit, BPP (complexity), Charles E. Leiserson, Clifford Stein, Co-NP, Cobham's thesis, Complement (complexity), Complexity class, Computational complexity theory, Computational resource, Concatenation, Constructive proof, Decision problem, Descriptive complexity theory, Dexter Kozen, DTIME, EXPTIME, First-order logic, FO (complexity), Forbidden graph characterization, FP (complexity), Function problem, Greatest common divisor, Henry Cabourn Pocklington, Homomorphism, Intersection (set theory), Introduction to Algorithms, Jack Edmonds, Kleene star, L (complexity), Least fixed point, Linear programming, Logarithm, Low (complexity), Matching (graph theory), Non-deterministic Turing machine, NP (complexity), P versus NP problem, P-complete, P/poly, Polynomial, Polynomial hierarchy, Prime number, PSPACE, Random access, Range concatenation grammars, Reachability, Robertson–Seymour theorem, ..., Ron Rivest, Sparse language, St-connectivity, Thomas H. Cormen, Time complexity, Turing machine, Undecidable problem, Union (set theory). Expand index (8 more) »
Advice (complexity)
In computational complexity theory, an advice string is an extra input to a Turing machine that is allowed to depend on the length n of the input, but not on the input itself.
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Alternating Turing machine
In computational complexity theory, an alternating Turing machine (ATM) is a non-deterministic Turing machine (NTM) with a rule for accepting computations that generalizes the rules used in the definition of the complexity classes NP and co-NP.
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Boolean circuit
In computational complexity theory and circuit complexity, a Boolean circuit is a mathematical model for digital logic circuits.
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BPP (complexity)
In computational complexity theory, BPP, which stands for bounded-error probabilistic polynomial time is the class of decision problems solvable by a probabilistic Turing machine in polynomial time with an error probability bounded away from 1/2 for all instances.
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Charles E. Leiserson
Charles Eric Leiserson is a computer scientist, specializing in the theory of parallel computing and distributed computing, and particularly practical applications thereof.
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Clifford Stein
Clifford Seth Stein (born December 14, 1965), a computer scientist, is a professor of industrial engineering and operations research at Columbia University in New York, NY, where he also holds an appointment in the Department of Computer Science.
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Co-NP
In computational complexity theory, co-NP is a complexity class.
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Cobham's thesis
Cobham's thesis, also known as Cobham–Edmonds thesis (named after Alan Cobham and Jack Edmonds), asserts that computational problems can be feasibly computed on some computational device only if they can be computed in polynomial time; that is, if they lie in the complexity class P (PTIME).
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Complement (complexity)
In computational complexity theory, the complement of a decision problem is the decision problem resulting from reversing the yes and no answers.
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Complexity class
In computational complexity theory, a complexity class is a set of problems of related resource-based complexity.
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Computational complexity theory
Computational complexity theory is a branch of the theory of computation in theoretical computer science that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other.
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Computational resource
In computational complexity theory, a computational resource is a resource used by some computational models in the solution of computational problems.
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Concatenation
In formal language theory and computer programming, string concatenation is the operation of joining character strings end-to-end.
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Constructive proof
In mathematics, a constructive proof is a method of proof that demonstrates the existence of a mathematical object by creating or providing a method for creating the object.
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Decision problem
In computability theory and computational complexity theory, a decision problem is a problem that can be posed as a yes-no question of the input values.
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Descriptive complexity theory
Descriptive complexity is a branch of computational complexity theory and of finite model theory that characterizes complexity classes by the type of logic needed to express the languages in them.
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Dexter Kozen
Dexter Campbell Kozen is an American theoretical computer scientist.
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DTIME
In computational complexity theory, DTIME (or TIME) is the computational resource of computation time for a deterministic Turing machine.
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EXPTIME
In computational complexity theory, the complexity class EXPTIME (sometimes called EXP or DEXPTIME) is the set of all decision problems that have exponential runtime, i.e., that are solvable by a deterministic Turing machine in O(2p(n)) time, where p(n) is a polynomial function of n. In terms of DTIME, We know and also, by the time hierarchy theorem and the space hierarchy theorem, that so at least one of the first three inclusions and at least one of the last three inclusions must be proper, but it is not known which ones are.
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First-order logic
First-order logic—also known as first-order predicate calculus and predicate logic—is a collection of formal systems used in mathematics, philosophy, linguistics, and computer science.
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FO (complexity)
In descriptive complexity, a branch of computational complexity, FO is a complexity class of structures that can be recognized by formulas of first-order logic, and also equals the complexity class AC0.
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Forbidden graph characterization
In graph theory, a branch of mathematics, many important families of graphs can be described by a finite set of individual graphs that do not belong to the family and further exclude all graphs from the family which contain any of these forbidden graphs as (induced) subgraph or minor.
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FP (complexity)
In computational complexity theory, the complexity class FP is the set of function problems which can be solved by a deterministic Turing machine in polynomial time; it is the function problem version of the decision problem class P. Roughly speaking, it is the class of functions that can be efficiently computed on classical computers without randomization.
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Function problem
In computational complexity theory, a function problem is a computational problem where a single output (of a total function) is expected for every input, but the output is more complex than that of a decision problem.
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Greatest common divisor
In mathematics, the greatest common divisor (gcd) of two or more integers, which are not all zero, is the largest positive integer that divides each of the integers.
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Henry Cabourn Pocklington
Henry Cabourn Pocklington FRS (28 January 1870, Exeter – 15 May 1952, Leeds) was an English physicist and mathematician.
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Homomorphism
In algebra, a homomorphism is a structure-preserving map between two algebraic structures of the same type (such as two groups, two rings, or two vector spaces).
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Intersection (set theory)
In mathematics, the intersection A ∩ B of two sets A and B is the set that contains all elements of A that also belong to B (or equivalently, all elements of B that also belong to A), but no other elements.
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Introduction to Algorithms
Introduction to Algorithms is a book by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein.
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Jack Edmonds
Jack R. Edmonds (born April 5, 1934) is an American computer scientist, regarded as one of the most important contributors to the field of combinatorial optimization.
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Kleene star
In mathematical logic and computer science, the Kleene star (or Kleene operator or Kleene closure) is a unary operation, either on sets of strings or on sets of symbols or characters.
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L (complexity)
In computational complexity theory, L (also known as LSPACE or DLOGSPACE) is the complexity class containing decision problems that can be solved by a deterministic Turing machine using a logarithmic amount of writable memory space.
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Least fixed point
In order theory, a branch of mathematics, the least fixed point (lfp or LFP, sometimes also smallest fixed point) of a function from a partially ordered set to itself is the fixed point which is less than each other fixed point, according to the set's order.
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Linear programming
Linear programming (LP, also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships.
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Logarithm
In mathematics, the logarithm is the inverse function to exponentiation.
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Low (complexity)
In computational complexity theory, a language B (or a complexity class B) is said to be low for a complexity class A (with some reasonable relativized version of A) if AB.
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Matching (graph theory)
In the mathematical discipline of graph theory, a matching or independent edge set in a graph is a set of edges without common vertices.
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Non-deterministic Turing machine
In theoretical computer science, a Turing machine is a theoretical machine that is used in thought experiments to examine the abilities and limitations of computers.
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NP (complexity)
In computational complexity theory, NP (for nondeterministic polynomial time) is a complexity class used to describe certain types of decision problems.
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P versus NP problem
The P versus NP problem is a major unsolved problem in computer science.
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P-complete
In complexity theory, a decision problem is P-complete (complete for the complexity class '''P''') if it is in P and every problem in P can be reduced to it by an appropriate reduction.
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P/poly
In computational complexity theory, P/poly is the complexity class of languages recognized by a polynomial-time Turing machine with a polynomial-bounded advice function.
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Polynomial
In mathematics, a polynomial is an expression consisting of variables (also called indeterminates) and coefficients, that involves only the operations of addition, subtraction, multiplication, and non-negative integer exponents of variables.
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Polynomial hierarchy
In computational complexity theory, the polynomial hierarchy (sometimes called the polynomial-time hierarchy) is a hierarchy of complexity classes that generalize the classes P, NP and co-NP to oracle machines.
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Prime number
A prime number (or a prime) is a natural number greater than 1 that cannot be formed by multiplying two smaller natural numbers.
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PSPACE
In computational complexity theory, PSPACE is the set of all decision problems that can be solved by a Turing machine using a polynomial amount of space.
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Random access
In computer science, random access (more precisely and more generally called direct access) is the ability to access any item of data from a population of addressable elements roughly as easily and efficiently as any other, no matter how many elements may be in the set.
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Range concatenation grammars
Range concatenation grammar (RCG) is a grammar formalism developed by Pierre Boullier in 1998 as an attempt to characterize a number of phenomena of natural language, such as Chinese numbers and German word order scrambling, which are outside the bounds of the Mildly context-sensitive languages.
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Reachability
In graph theory, reachability refers to the ability to get from one vertex to another within a graph.
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Robertson–Seymour theorem
In graph theory, the Robertson–Seymour theorem (also called the graph minor theorem) states that the undirected graphs, partially ordered by the graph minor relationship, form a well-quasi-ordering.
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Ron Rivest
Ronald Linn Rivest (born May 6, 1947) is a cryptographer and an Institute Professor at MIT.
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Sparse language
In computational complexity theory, a sparse language is a formal language (a set of strings) such that the complexity function, counting the number of strings of length n in the language, is bounded by a polynomial function of n. They are used primarily in the study of the relationship of the complexity class NP with other classes.
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St-connectivity
In computer science and computational complexity theory, st-connectivity or STCON is a decision problem asking, for vertices s and t in a directed graph, if t is reachable from s. Formally, the decision problem is given by.
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Thomas H. Cormen
Thomas H. Cormen is the co-author of Introduction to Algorithms, along with Charles Leiserson, Ron Rivest, and Cliff Stein.
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Time complexity
In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.
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Turing machine
A Turing machine is a mathematical model of computation that defines an abstract machine, which manipulates symbols on a strip of tape according to a table of rules.
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Undecidable problem
In computability theory and computational complexity theory, an undecidable problem is a decision problem for which it is known to be impossible to construct a single algorithm that always leads to a correct yes-or-no answer.
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Union (set theory)
In set theory, the union (denoted by ∪) of a collection of sets is the set of all elements in the collection.
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AL (complexity), Complexity class P, Nonuniform polynomial time, Nonuniform polynomial-time, P (class), P (complexity class), P-hard, PTIME.
References
[1] https://en.wikipedia.org/wiki/P_(complexity)
