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IPS273 Tomoki Tokuda et al.

6. Muller, E., Gunnemann. S., Farber. I. & Seidl, T. (2012). Discovering
multiple clustering solutions: Grouping objects in different views of the
data. In: Data Engineering (ICDE), 2012 IEEE 28th International
Conference, 1207–1210.
7. Niu, D., Dy, J.G. & Jordan, M.I. (2010). Multiple non-redundant spectral
clustering views. In: Proceedings of the 27th International Conference on
Machine Learning (ICML-10), 831–838.
8. Shan, H. & Banerjee, A. (2008). Bayesian co-clustering. In: Data Mining,
2008. ICDM’08, Eighth IEEE International Conference, 530–539.
9. Tokuda, T., Yoshimoto, J., Shimizu, Y., Okada, G., Takamura, M., Okamoto,
Y., Yamawaki, S. & Doya, K. (2017). Multiple co-clustering based on
nonparametric mixture models with heterogeneous marginal
distributions. PloS ONE, 12, 0186566.
10. Tokuda, T., Yoshimoto, J., Shimizu, Y., Okada, G., Takamura, M., Okamoto,
Y., Yamawaki, S. & Doya, K. (2018). Identification of depression subtypes
and relevant brain regions using a data-driven approach. Scientific
Reports, 8, 14082.

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