Inapproximability of Clustering in Lp Metrics
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/8936052/8948505/08948668.pdf?arnumber=8948668
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Global k-means++: an effective relaxation of the global k-means clustering algorithm;Applied Intelligence;2024-07-05
2. Approximation Algorithms for Robust Clustering Problems Using Local Search Techniques;Lecture Notes in Computer Science;2024
3. Parameterized Approximation Schemes for Clustering with General Norm Objectives;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06
4. Improved approximations for Euclidean k -means and k -median, via nested quasi-independent sets;Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing;2022-06-09
5. Towards optimal lower bounds for k-median and k-means coresets;Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing;2022-06-09
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