A Variational Inference Procedure Allowing Internal Structure for Overlapping Clusters and Deterministic Constraints

Dan Geiger, Christopher Meek, and Ydo Wexler

Abstract

We develop a novel algorithm, called VIP*, for structured variational approximate inference. This algorithm extends known algorithms to allow efficient multiple potential updates for overlapping clusters, and overcomes the difficulties imposed by deterministic constraints. The algorithms convergence is proven and its applicability demonstrated for genetic linkage analysis.

Details

Publication typeArticle
Published inJournal of Artificial Intelligence Research
Pages1-23
Volume27
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