Kernel-based Clustering
Kernel-Based Clustering is a spatial clustering method that employs kernel functions to map input data into a higher-dimensional feature space, where non-linearly separable clusters in the original space become linearly separable through implicit density estimation and mode detection in the transformed space.
459
Publications
29.8K
Citations
1.2K
Authors
533
Institutions
Publications per year
2017–2026
194
Parents
459
Dlib-ml: A Machine Learning Toolkit
Davis E. King · 2009 · 2.9K citations
Asa Ben‐Hur, D. Horn, Hava T. Siegelmann et al. · 2002 · 1.4K citations
Mercer kernel-based clustering in feature space
Mark Girolami · IEEE Transactions on Neural Networks · 2002 · 904 citations
A survey of kernel and spectral methods for clustering
Maurizio Filippone, Francesco Camastra, Francesco Masulli et al. · Pattern Recognition · 2007 · 829 citations
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533

National University of Defense Technology
Changsha, China
22 h-index
119 publications
7.6K citations
Nanjing University of Science and Technology
Nanjing, China
13 h-index
34 publications
2.3K citations
Southwest University of Science and Technology
Mianyang, China
12 h-index
35 publications
1.6K citations
KU Leuven
Leuven, Belgium
11 h-index
37 publications
2.7K citations

Nanjing University of Aeronautics and Astronautics
Nanjing, China
9 h-index
24 publications
4.1K citations

Chinese Academy of Sciences
Beijing, China
8 h-index
17 publications
2.3K citations

University of Macau
Macao, Macao
7 h-index
12 publications
229 citations

Zhejiang Normal University
Jinhua, China
7 h-index
8 publications
452 citations
1–8 of 533
19 publications · 1.9K citations
15
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17 publications · 866 citations
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13 publications · 544 citations
13
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Conference · 13 publications · 841 citations
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TPAMI · 10 publications · 1.5K citations
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