Parameterized Approximation Algorithms and Lower Bounds for k-Center Clustering and Variants

Author:

Bandyapadhyay Sayan,Friggstad Zachary,Mousavi Ramin

Publisher

Springer Science and Business Media LLC

Reference29 articles.

1. Agarwal, P.K., Procopiuc, C.M.: Exact and approximation algorithms for clustering. Algorithmica 33(2), 201–226 (2002)

2. Awasthi, P., Charikar, M., Krishnaswamy, R., Sinop, A. K. The hardness of approximation of euclidean k-means. arXiv preprint arXiv:1502.03316 (2015)

3. Badoiu, M., Clarkson, K. L.: Smaller core-sets for balls. In: Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms, Baltimore, Maryland. ACM/SIAM, pp. 801–802 (2003)

4. Badoiu, M., Har-Peled, S., Indyk, P.: Approximate clustering via core-sets. In: Proceedings on 34th Annual ACM Symposium on Theory of Computing. Montréal, Québec, Canada, J. H. Reif, Ed., ACM, pp. 250–257 (2002)

5. Bandyapadhyay, S.: On perturbation resilience of non-uniform k-center. In: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020). Schloss Dagstuhl-Leibniz-Zentrum für Informatik (2020)

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