minimizes
1minimizes — minimize (Amer.) min·i·mize || mɪnɪmaɪz v. make small, reduce; reduce as much as possible; make less important; play down; (Computers) make a window smaller to the point that only an icon remains in its place (also minimise) …
2Bayes estimator — In decision theory and estimation theory, a Bayes estimator is an estimator or decision rule that maximizes the posterior expected value of a utility function or minimizes the posterior expected value of a loss function (also called posterior… …
3Info-gap decision theory — is a non probabilistic decision theory that seeks to optimize robustness to failure – or opportuneness for windfall – under severe uncertainty,[1][2] in particular applying sensitivity analysis of the stability radius type[3] to perturbations in… …
4Median — This article is about the statistical concept. For other uses, see Median (disambiguation). In probability theory and statistics, a median is described as the numerical value separating the higher half of a sample, a population, or a probability… …
5Generalized minimal residual method — In mathematics, the generalized minimal residual method (usually abbreviated GMRES) is an iterative method for the numerical solution of a system of linear equations. The method approximates the solution by the vector in a Krylov subspace with… …
6Absolute deviation — In statistics, the absolute deviation of an element of a data set is the absolute difference between that element and a given point. Typically the point from which the deviation is measured is a measure of central tendency, most often the median… …
7Artificial neural network — An artificial neural network (ANN), usually called neural network (NN), is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an… …
8Calculus of variations — is a field of mathematics that deals with extremizing functionals, as opposed to ordinary calculus which deals with functions. A functional is usually a mapping from a set of functions to the real numbers. Functionals are often formed as definite …
9Shape context — is the term given by Serge Belongie and Jitendra Malik to the feature descriptor they first proposed in their paper Matching with Shape Contexts in 2000cite conference author = S. Belongie and J. Malik title = Matching with Shape Contexts url =… …
10Conditioning (probability) — Beliefs depend on the available information. This idea is formalized in probability theory by conditioning. Conditional probabilities, conditional expectations and conditional distributions are treated on three levels: discrete probabilities,… …
