Unified and View-Specific Multiple Kernel K-Means Clustering

Author:

Zhang YujingORCID,Wang SiweiORCID,Zhu EnORCID

Publisher

Springer International Publishing

Reference21 articles.

1. Chen, J., Zhao, Z., Ye, J., Liu, H.: Nonlinear adaptive distance metric learning for clustering. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 123–132. ACM (2007)

2. Du, L., Zhang, H., Ren, X., Lv, X.: Manifold adaptive multiple kernel k-means for clustering. arXiv preprint arXiv:2009.14389 (2020)

3. Du, L., et al.: Robust multiple kernel k-means using l21-norm. In: Twenty-Fourth International Joint Conference on Artificial Intelligence (2015)

4. Gönen, M., Alpaydin, E.: Localized multiple kernel learning. In: Proceedings of the 25th International Conference on Machine Learning, pp. 352–359. ACM (2008)

5. Gönen, M., Margolin, A.A.: Localized data fusion for kernel k-means clustering with application to cancer biology. In: Advances in Neural Information Processing Systems, pp. 1305–1313 (2014)

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