Please use this identifier to cite or link to this item:
http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7281
Title: | Risk Bounds for Mixture Density Estimation |
Keywords: | AI density estimation MLE |
Issue Date: | 9-Oct-2013 |
Description: | In this paper we focus on the problem of estimating a bounded density using a finite combination of densities from a given class. We consider the Maximum Likelihood Procedure (MLE) and the greedy procedure described by Li and Barron. Approximation and estimation bounds are given for the above methods. We extend and improve upon the estimation results of Li and Barron, and in particular prove an $O(\\frac{1}{\\sqrt{n}})$ bound on the estimation error which does not depend on the number of densities in the estimated combination. |
URI: | http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
Other Identifiers: | AIM-2004-001 CBCL-233 http://hdl.handle.net/1721.1/7281 |
Appears in Collections: | MIT Items |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.