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» Approximate Kernel Clustering
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ICPR
2008
IEEE
15 years 11 months ago
K-means clustering of proportional data using L1 distance
We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
COLT
2004
Springer
15 years 3 months ago
A Statistical Mechanics Analysis of Gram Matrix Eigenvalue Spectra
Abstract. The Gram matrix plays a central role in many kernel methods. Knowledge about the distribution of eigenvalues of the Gram matrix is useful for developing appropriate model...
David C. Hoyle, Magnus Rattray
BMCBI
2008
145views more  BMCBI 2008»
14 years 10 months ago
Directed acyclic graph kernels for structural RNA analysis
Background: Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel ...
Kengo Sato, Toutai Mituyama, Kiyoshi Asai, Yasubum...
CIARP
2010
Springer
14 years 8 months ago
Improving the Dynamic Hierarchical Compact Clustering Algorithm by Using Feature Selection
Abstract. Feature selection has improved the performance of text clustering. In this paper, a local feature selection technique is incorporated in the dynamic hierarchical compact ...
Reynaldo Gil-García, Aurora Pons-Porrata
CVPR
2011
IEEE
14 years 1 months ago
Max-margin Clustering: Detecting Margins from Projections of Points on Lines
Given a unlabelled set of points X ∈ RN belonging to k groups, we propose a method to identify cluster assignments that provides maximum separating margin among the clusters. We...
Raghuraman Gopalan, Jagan Sankaranarayanan