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Poster
Co-regularized Multi-view Spectral Clustering
Abhishek Kumar · Piyush Rai · Hal Daumé III

Mon Dec 12 10:00 AM -- 02:59 PM (PST) @
in Poster Session and Reception »

In many clustering problems, we have access to multiple views of the data each of which could be individually used for clustering. Exploiting information from multiple views, one can hope to find a clustering that is more accurate than the ones obtained using the individual views. Since the true clustering would assign a point to the same cluster irrespective of the view, we can approach this problem by looking for clusterings that are consistent across the views, i.e., corresponding data points in each view should have same cluster membership. We propose a spectral clustering framework that achieves this goal by co-regularizing the clustering hypotheses, and propose two co-regularization schemes to accomplish this. Experimental comparisons with a number of baselines on two synthetic and three real-world datasets establish the efficacy of our proposed approaches.

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Author Information

Abhishek Kumar (Google DeepMind)
Piyush Rai (Duke University)
Hal Daumé III (University of Maryland - College Park)

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