Abstract
We study the spherical k-means problem with outliers, a variant of the classical k-means problem, in which data points are on the unit sphere and a small set of points called outliers (as a constraint, the number of outliers can not be greater than a given integer) can be ignored. Using local search method, we give a constant-factor approximation algorithm that may violate slightly the constraint about the number of outliers.
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Acknowledgements
The second author is supported by National Natural Science Foundation of China (No. 11971349). The third author is supported by National Natural Science Foundation of China (No. 11871081). The fourth author is supported by National Natural Science Foundation of China (No. 11801310).
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Wang, Y., Wu, C., Zhang, D., Zou, J. (2020). Local Search Algorithm for the Spherical k-Means Problem with Outliers. In: Zhang, Z., Li, W., Du, DZ. (eds) Algorithmic Aspects in Information and Management. AAIM 2020. Lecture Notes in Computer Science(), vol 12290. Springer, Cham. https://doi.org/10.1007/978-3-030-57602-8_13
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DOI: https://doi.org/10.1007/978-3-030-57602-8_13
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