Abstract
hierarchical clustering is an important problem with wide applications. In this paper, we approach the problem with a formulation based on weighted graphs and introduce new algorithmic techniques. Our new formulation and techniques lead to new kernelization algorithms and parameterized algorithms for the problem, which significantly improve previous algorithms for the problem.
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Supported in part by the US NSF under the Grants CCF-0830455 and CCF-0917288.
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Cao, Y., Chen, J. (2013). On Parameterized and Kernelization Algorithms for the Hierarchical Clustering Problem. In: Chan, TH.H., Lau, L.C., Trevisan, L. (eds) Theory and Applications of Models of Computation. TAMC 2013. Lecture Notes in Computer Science, vol 7876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38236-9_29
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DOI: https://doi.org/10.1007/978-3-642-38236-9_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38235-2
Online ISBN: 978-3-642-38236-9
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