Kernel-based Cluster Detection
Kernel-Based Cluster Detection is a cluster detection method that employs kernel functions to map data into higher-dimensional spaces where clusters are more discernible, distinguishing itself from other methods by leveraging kernel-induced similarity measures to identify non-linearly separable groupings.
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Asa Ben‐Hur, D. Horn, Hava T. Siegelmann et al. · 2002 · 1.4K citations
Robust multiple kernel K-means using ℓ 2;1 -norm
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KU Leuven
Leuven, Belgium
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6 publications
207 citations
University of Pittsburgh
Pittsburgh, United States
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2 publications
156 citations
Institute of Software
Beijing, China
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6 publications
789 citations
University of Technology Malaysia
Johor Bahru, Malaysia
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4 publications
85 citations

University of Electronic Science and Technology of China
Chengdu, China
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3 publications
105 citations
Harvard University
Cambridge, United States
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3 publications
269 citations

Xi'an Jiaotong University
Xi'an, China
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9 publications
375 citations
University of Calcutta
Kolkata, India
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4 publications
78 citations
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