Iterative Spectral Method for Alternative Clustering


Chieh Wu, Stratis Ioannidis, Mario Sznaier, Xiangyu Li, David Kaeli, Jennifer Dy ;
Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:115-123, 2018.


Given a dataset and an existing clustering as input, alternative clustering aims to find an alternative partition. One of the state-of-the-art approaches is Kernel Dimension Alternative Clustering (KDAC). We propose a novel Iterative Spectral Method (ISM) that greatly improves the scalability of KDAC. Our algorithm is intuitive, relies on easily implementable spectral decompositions, and comes with theoretical guarantees. Its computation time improves upon existing implementations of KDAC by as much as 5 orders of magnitude.

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