descent algorithm
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Descent — Not to be confused with Dissent. Descent may refer to: In genealogy and inheritance: Common descent, concept in evolutionary biology Kinship and descent, one of the major concepts of cultural anthropology Pedigree chart or family tree Ancestry… … Wikipedia
Gradient descent — For the analytical method called steepest descent see Method of steepest descent. Gradient descent is an optimization algorithm. To find a local minimum of a function using gradient descent, one takes steps proportional to the negative of the… … Wikipedia
Gauss–Newton algorithm — The Gauss–Newton algorithm is a method used to solve non linear least squares problems. It can be seen as a modification of Newton s method for finding a minimum of a function. Unlike Newton s method, the Gauss–Newton algorithm can only be used… … Wikipedia
Levenberg–Marquardt algorithm — In mathematics and computing, the Levenberg–Marquardt algorithm (LMA)[1] provides a numerical solution to the problem of minimizing a function, generally nonlinear, over a space of parameters of the function. These minimization problems arise… … 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
Expectation-maximization algorithm — An expectation maximization (EM) algorithm is used in statistics for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. EM alternates between performing an… … Wikipedia
Shunting yard algorithm — The shunting yard algorithm is a method for parsing mathematical equations specified in infix notation. It can be used to produce output in Reverse Polish notation (RPN) or as an abstract syntax tree (AST). The algorithm was invented by Edsger… … Wikipedia
Method of steepest descent — For the optimization algorithm, see Gradient descent. In mathematics, the method of steepest descent or stationary phase method or saddle point method is an extension of Laplace s method for approximating an integral, where one deforms a contour… … Wikipedia
Computational complexity of mathematical operations — The following tables list the running time of various algorithms for common mathematical operations. Here, complexity refers to the time complexity of performing computations on a multitape Turing machine.[1] See big O notation for an explanation … Wikipedia
Backpropagation — Backpropagation, or propagation of error, is a common method of teaching artificial neural networks how to perform a given task. It was first described by Paul Werbos in 1974, but it wasn t until 1986, through the work of David E. Rumelhart,… … Wikipedia
Least absolute deviations — (LAD), also known as Least Absolute Errors (LAE), Least Absolute Value (LAV), or the L1 norm problem, is a mathematical optimization technique similar to the popular least squares technique that attempts to find a function which closely… … Wikipedia
