Personal tools
You are here: Home Publications Support Vector Method for Multivariate Density Estimation
Document Actions

V. Vapnik and S. Mukherjee (1999)

Support Vector Method for Multivariate Density Estimation

In: Neural Information Processing Systems.

A new method for multivariate density estimation is developed based on the Support Vector Method (SVM) solution of inverse ill-posed problems. The solution has the form of a mixture of densities. This method with Gaussian kernels compared favorably to both Parzen's method and the Gaussian Mixture Model method. For synthetic data we achieve more accurate estimates for densities of $2$, $6$, $12$, and $40$ dimensions.

by admin last modified 2007-01-31 11:08

Powered by Plone CMS, the Open Source Content Management System