Clustering Affine Subspaces: Algorithms and Hardness

Clustering Affine Subspaces: Algorithms and Hardness

<p>We study a generalization of the famous k-center problem where each object is an affine subspace of dimension Δ, and give either the first or significantly improved algorithms and hardness results for many combinations of parameters. This generalization from points (Δ=0) is motivated by the...

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Bibliographic Details
Main Author: Lee, Euiwoong
Format: Others
Published: 2012
Online Access:https://thesis.library.caltech.edu/7171/1/Thesis2.pdf
Lee, Euiwoong (2012) Clustering Affine Subspaces: Algorithms and Hardness. Master's thesis, California Institute of Technology. doi:10.7907/VF38-NT60. https://resolver.caltech.edu/CaltechTHESIS:07052012-191337554 <https://resolver.caltech.edu/CaltechTHESIS:07052012-191337554>

Internet

https://thesis.library.caltech.edu/7171/1/Thesis2.pdf
Lee, Euiwoong (2012) Clustering Affine Subspaces: Algorithms and Hardness. Master's thesis, California Institute of Technology. doi:10.7907/VF38-NT60. https://resolver.caltech.edu/CaltechTHESIS:07052012-191337554 <https://resolver.caltech.edu/CaltechTHESIS:07052012-191337554>

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