Computational complexityIn computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements. The complexity of a problem is the complexity of the best algorithms that allow solving the problem. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.
Complexity classIn computational complexity theory, a complexity class is a set of computational problems "of related resource-based complexity". The two most commonly analyzed resources are time and memory. In general, a complexity class is defined in terms of a type of computational problem, a model of computation, and a bounded resource like time or memory. In particular, most complexity classes consist of decision problems that are solvable with a Turing machine, and are differentiated by their time or space (memory) requirements.
Time complexityIn computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Thus, the amount of time taken and the number of elementary operations performed by the algorithm are taken to be related by a constant factor.
Randomized algorithmA randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performance in the "average case" over all possible choices of random determined by the random bits; thus either the running time, or the output (or both) are random variables.
Computational complexity theoryIn theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used.
Parameterized complexityIn computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according to their inherent difficulty with respect to multiple parameters of the input or output. The complexity of a problem is then measured as a function of those parameters. This allows the classification of NP-hard problems on a finer scale than in the classical setting, where the complexity of a problem is only measured as a function of the number of bits in the input.
Analysis of algorithmsIn computer science, the analysis of algorithms is the process of finding the computational complexity of algorithms—the amount of time, storage, or other resources needed to execute them. Usually, this involves determining a function that relates the size of an algorithm's input to the number of steps it takes (its time complexity) or the number of storage locations it uses (its space complexity). An algorithm is said to be efficient when this function's values are small, or grow slowly compared to a growth in the size of the input.
Space complexityThe space complexity of an algorithm or a computer program is the amount of memory space required to solve an instance of the computational problem as a function of characteristics of the input. It is the memory required by an algorithm until it executes completely. This includes the memory space used by its inputs, called input space, and any other (auxiliary) memory it uses during execution, which is called auxiliary space. Similar to time complexity, space complexity is often expressed asymptotically in big O notation, such as etc.
Reduction (complexity)In computability theory and computational complexity theory, a reduction is an algorithm for transforming one problem into another problem. A sufficiently efficient reduction from one problem to another may be used to show that the second problem is at least as difficult as the first. Intuitively, problem A is reducible to problem B, if an algorithm for solving problem B efficiently (if it existed) could also be used as a subroutine to solve problem A efficiently. When this is true, solving A cannot be harder than solving B.
AlgorithmIn mathematics and computer science, an algorithm (ˈælɡərɪðəm) is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can use conditionals to divert the code execution through various routes (referred to as automated decision-making) and deduce valid inferences (referred to as automated reasoning), achieving automation eventually.
Communication complexityIn theoretical computer science, communication complexity studies the amount of communication required to solve a problem when the input to the problem is distributed among two or more parties. The study of communication complexity was first introduced by Andrew Yao in 1979, while studying the problem of computation distributed among several machines. The problem is usually stated as follows: two parties (traditionally called Alice and Bob) each receive a (potentially different) -bit string and .
Philippe de VilmorinJoseph-Marie-Philippe Lévêque de Vilmorin (21 May 1872 – 29 June 1917), generally known as Philippe de Vilmorin, was a noted French botanist and plant collector, and a member of the celebrated Vilmorin family of horticulturists. In 1903 Vilmorin began the Arboretum de Pézanin, an arboretum located in Dompierre-les-Ormes, Saône-et-Loire, Bourgogne, France. He also collected plants in Egypt and Sudan that now form part of the herbarium of the National Botanic Garden of Belgium.
Mapie de Toulouse-LautrecMarie Pierre "Mapie" de Toulouse-Lautrec (1901–1972) was a French journalist and food writer, born Marie Pierre Adélaïde Lévêque de Vilmorin in Verrières-le-Buisson, scion of the Vilmorin seed company. Her horticulturalist father was Joseph Marie Philippe Lévêque de Vilmorin (1872-1917), and her mother was the former Bertha Marie Mélanie de Gaufridy de Dortan (1876-1937). The writer Louise de Vilmorin (1902–1969) was her younger sister, while one of her younger brothers, Roger, was the result of an affair between her mother and Alfonso XIII of Spain.
VilmorinVilmorin is a French seed producer. The company has a long history in France, where it was family-controlled for almost two centuries, and today exists as a publicly traded company owned principally by agro-industrial cooperative Groupe Limagrain, the largest plant breeding and seed company in the European Union. Vilmorin was founded as a plant and seed boutique in 1743 by seed expert Claude Geoffroy and her husband Pierre Andrieux, the chief seed supplier and botanist to King Louis XV.
French School at AthensThe French School at Athens (École française d’Athènes, EfA; Γαλλική Σχολή Αθηνών Gallikí Scholí Athinón) is one of the seventeen foreign archaeological institutes operating in Athens, Greece. Founded in 1846, the EfA is the oldest foreign institute in Athens. Its early foundation, still a source of considerable prestige, is to be seen culturally connected with French philhellenism and politically with the French East Mediterranean strategy of the time.
Crédit LyonnaisThe Crédit Lyonnais (kʁedi ljɔnɛ, "Lyon Credit [Company]") was a major French bank, created in 1863 and absorbed by former rival Crédit Agricole in 2003. Its head office was initially in Lyon but moved to Paris in 1882. In the early years of the 20th century, it was the world's largest bank by total assets. Its former French retail network survives as LCL S.A., a fully owned subsidiary of Crédit Agricole, under the brand LCL adopted in 2005 with reference to "Le Crédit Lyonnais".
