PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Variational Approach to Semi-Supervised Clustering
Peng Li, Yiming Ying and Colin Campbell
In: ESANN2009, 23-25th April 2009, Bruges, Belgium.

Abstract

We present a Bayesian variational inference scheme for semi- supervised clustering in which data is supplemented with side information in the form of common labels. There is no mutual exclusion of classes assumption and samples are represented as a combinatorial mixture over multiple clusters. We illustrate performance on six datasets and ¯nd a positive comparison against constrained K-means clustering.

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EPrint Type:Conference or Workshop Item (Talk)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5034
Deposited By:Colin Campbell
Deposited On:24 March 2009