Provides tight FPT-time (3+ε)-approximations for capacitated general-norm k-clustering and (1 + 2/(e c) + ε) for top-cn norm k-clustering, plus a bicriteria result.
Turning big data into tiny data: Constant-size coresets fork-means, pca, and projective clustering.SIAM Journal on Computing, 49(3):601–657
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On Tight FPT Time Approximation Algorithms for k-Clustering Problems
Provides tight FPT-time (3+ε)-approximations for capacitated general-norm k-clustering and (1 + 2/(e c) + ε) for top-cn norm k-clustering, plus a bicriteria result.