Co-Clustering with Generative Models

In this paper, we present a generative model for co-clustering and develop algorithms based on the mean field approximation for the corresponding modeling problem. These algorithms can be viewed as generalizations of the traditional model-based clustering; they extend hard co-clustering algorithms s...

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Bibliographic Details
Main Authors: Golland, Polina, Lashkari, Danial
Other Authors: Polina Golland
Published: 2009
Online Access:http://hdl.handle.net/1721.1/49526
Description
Summary:In this paper, we present a generative model for co-clustering and develop algorithms based on the mean field approximation for the corresponding modeling problem. These algorithms can be viewed as generalizations of the traditional model-based clustering; they extend hard co-clustering algorithms such as Bregman co-clustering to include soft assignments. We show empirically that these model-based algorithms offer better performance than their hard-assignment counterparts, especially with increasing problem complexity.