regularization parameter

См. также в других словарях:

• Regularization (mathematics) — For other uses in related fields, see Regularization (disambiguation). In mathematics and statistics, particularly in the fields of machine learning and inverse problems, regularization involves introducing additional information in order to… …   Wikipedia

• Tikhonov regularization — Tikhonov regularization, named for Andrey Tikhonov, is the most commonly used method of regularization of ill posed problems. In statistics, the method is known as ridge regression, and, with multiple independent discoveries, it is also variously …   Wikipedia

• Dimensional regularization — Renormalization and regularization Renormalization Renormalization …   Wikipedia

• Zeta function regularization — In mathematics and theoretical physics, zeta function regularization is a type of regularization or summability method that assigns finite values to superficially divergent sums. The technique is now commonly applied to problems in physics, but… …   Wikipedia

• Contact dynamics — deals with the motion of multibody systems subjected to unilateral contacts and friction. Such systems are omnipresent in many multibody dynamics applications. Consider for example Contacts between wheels and ground in vehicle dynamics Squealing… …   Wikipedia

• Butcher group — In mathematics, the Butcher group, named after the New Zealand mathematician John C. Butcher by Hairer Wanner (1974), is an infinite dimensional group first introduced in numerical analysis to study solutions of non linear ordinary differential… …   Wikipedia

• Shape 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 =… …   Wikipedia

• Radial basis function network — A radial basis function network is an artificial neural network that uses radial basis functions as activation functions. They are used in function approximation, time series prediction, and control.Network architectureRadial basis function (RBF) …   Wikipedia

• Renormalization — Quantum field theory (Feynman diagram) …   Wikipedia

• Linear least squares/Proposed — Linear least squares is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to observations obtained from experiments. Mathematically, it can be stated as the problem of… …   Wikipedia

• Linear least squares — is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to measurements obtained from experiments. The goals of linear least squares are to extract predictions from the… …   Wikipedia