Streaming Fair k-Center Clustering over Massive Dataset with Performance Guarantee
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-2259-4_8
Reference16 articles.
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3. Bandyapadhyay, S., Friggstad, Z., Mousavi, R.: Parameterized approximation algorithms for $$k$$-center clustering and variants. In: 36th AAAI Conference on Artificial Intelligence. vol. 36, pp. 3895–3903 (2022)
4. Ceccarello, M., Pietracaprina, A., Pucci, G.: Solving k-center clustering (with outliers) in mapreduce and streaming, almost as accurately as sequentially. In: 45th International Conference on Very Large Databases(VLDB), pp. 766–778 (2019)
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