A Co-training Approach for Multi-view Spectral Clustering

@inproceedings{Kumar2011ACA,
  title={A Co-training Approach for Multi-view Spectral Clustering},
  author={Abhishek Kumar and Hal Daum{\'e}},
  booktitle={ICML},
  year={2011}
}
We propose a spectral clustering algorithm for the multi-view setting where we have access to multiple views of the data, each of which can be independently used for clustering. Our spectral clustering algorithm has a flavor of co-training, which is already a widely used idea in semi-supervised learning. We work on the assumption that the true underlying clustering would assign a point to the same cluster irrespective of the view. Hence, we constrain our approach to only search for the… CONTINUE READING
Highly Influential
This paper has highly influenced 47 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 390 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 228 extracted citations

390 Citations

020406080'12'14'16'18
Citations per Year
Semantic Scholar estimates that this publication has 390 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 23 references

, Ulrike , Belkin , Mikhail , and Bousquet , Olivier . Consistency of Spectral Clustering

  • von Luxburg
  • IEEE International Conference on Data Mining…
  • 2007
Highly Influential
3 Excerpts

A Tutorial on Spectral Clustering

  • von Luxburg, Ulrike
  • Statistics and Computing,
  • 2007