A Variational Approach to Semi-Supervised Clustering

Li Peng, Ying Yiming, ICG Campbell

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

4 Citations (Scopus)


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.
Translated title of the contributionA Variational Approach to Semi-Supervised Clustering
Original languageEnglish
Title of host publicationESANN
Pages11 - 16
Number of pages5
Publication statusPublished - 2009

Bibliographical note

Name and Venue of Event: ESANN2009, Bruges Belgium
Conference Proceedings/Title of Journal: Proceedings ESANN2009


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