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An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models

Dukkipati, Ambedkar and Manathara, Joel George (2010) An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models. In: 12th CASC International Workshop, SEP 06-12, 2010, Tsakhkadzor, ARMENIA, pp. 85-96.

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Official URL: http://www.springerlink.com/content/w6wn626l063876...

Abstract

In this paper we study representation of KL-divergence minimization, in the cases where integer sufficient statistics exists, using tools from polynomial algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. In particular, we also study the case of Kullback-Csiszar iteration scheme. We present implicit descriptions of these models and show that implicitization preserves specialization of prior distribution. This result leads us to a Grobner bases method to compute an implicit representation of minimum KL-divergence models.

Item Type: Conference Paper
Additional Information: Copyright of this article belongs to Springer.
Keywords: Grobner Bases; statistical models; elimination
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 12 Jan 2011 11:01
Last Modified: 12 Jan 2011 11:01
URI: http://eprints.iisc.ernet.in/id/eprint/34914

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