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» Clustering with the Connectivity Kernel
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PR
2010
156views more  PR 2010»
13 years 5 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...
ICPR
2002
IEEE
14 years 13 days ago
A Large Scale Clustering Scheme for Kernel K-Means
Kernel functions can be viewed as a non-linear transformation that increases the separability of the input data by mapping them to a new high dimensional space. The incorporation ...
Rong Zhang, Alexander I. Rudnicky
ICPR
2008
IEEE
14 years 1 months ago
Kernel Bisecting k-means clustering for SVM training sample reduction
This paper presents a new algorithm named Kernel Bisecting k-means and Sample Removal (KBK-SR) as a sampling preprocessing for SVM training to improve the scalability. The novel c...
Xiao-Zhang Liu, Guo-Can Feng
ECML
2004
Springer
14 years 27 days ago
The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
Marco Saerens, François Fouss, Luh Yen, Pie...
ICML
2008
IEEE
14 years 8 months ago
Active kernel learning
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Steven C. H. Hoi, Rong Jin