stochastic algorithm

стохастический алгоритм

Англо-русский словарь по исследованиям и ноу-хау. . 2015.

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  • Stochastic approximation — methods are a family of iterative stochastic optimization algorithms that attempt to find zeroes or extrema of functions which cannot be computed directly, but only estimated via noisy observations. The first, and prototypical, algorithms of this …   Wikipedia

  • Stochastic optimization — (SO) methods are optimization algorithms which incorporate probabilistic (random) elements, either in the problem data (the objective function, the constraints, etc.), or in the algorithm itself (through random parameter values, random choices,… …   Wikipedia

  • Stochastic gradient descent — is a general optimization algorithm, but is typically used to fit the parameters of a machine learning model.In standard (or batch ) gradient descent, the true gradient is used to update the parameters of the model. The true gradient is usually… …   Wikipedia

  • Stochastic simulation — algorithms and methods were initially developed to analyse chemical reactions involving large numbers of species with complex reaction kinetics [cite journal |last=Bradley |first=Jeremy |authorlink=Jeremy Bradley |coauthors=Stephen Gilmore… …   Wikipedia

  • Stochastic universal sampling — (SUS) is a genetic operator used in genetic algorithms for selecting potentially useful solutions for recombination.First introduced into the literature by Baker [1] , SUS is a development of Fitness proportionate selection which exhibits no bias …   Wikipedia

  • Stochastic volatility — models are used in the field of quantitative finance to evaluate derivative securities, such as options. The name derives from the models treatment of the underlying security s volatility as a random process, governed by state variables such as… …   Wikipedia

  • Stochastic Diffusion Search — (SDS), was first described in 1989 as a population based, pattern matching algorithm [Bishop, 1989] . It belongs to a family of Swarm Intelligence and naturally inspired search and optimisation algorithms which includes Ant Colony Optimization,… …   Wikipedia

  • Stochastic tunneling — (STUN) is an approach to global optimization based on the Monte Carlo method sampling of the function to be minimized. Idea Monte Carlo method based optimization techniques sample the objective function by randomly hopping from the current… …   Wikipedia

  • Stochastic context-free grammar — A stochastic context free grammar (SCFG; also probabilistic context free grammar, PCFG) is a context free grammar in which each production is augmented with a probability. The probability of a derivation (parse) is then the product of the… …   Wikipedia

  • Stochastic process — A stochastic process, or sometimes random process, is the counterpart to a deterministic process (or deterministic system) in probability theory. Instead of dealing with only one possible reality of how the process might evolve under time (as is… …   Wikipedia

  • Stochastic drift — In probability theory, stochastic drift is the change of the average value of a stochastic (random) process. A related term is the drift rate which is the rate at which the average changes. This is in contrast to the random fluctuations about… …   Wikipedia

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