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ICDM
2007
IEEE
170views Data Mining» more  ICDM 2007»
15 years 4 months ago
Consensus Clusterings
In this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. This process is known in the literature as clustering...
Nam Nguyen, Rich Caruana
NIPS
2003
14 years 11 months ago
Clustering with the Connectivity Kernel
Clustering aims at extracting hidden structure in dataset. While the problem of finding compact clusters has been widely studied in the literature, extracting arbitrarily formed ...
Bernd Fischer, Volker Roth, Joachim M. Buhmann
JNW
2006
74views more  JNW 2006»
14 years 9 months ago
Mobility Resistant Clustering in Multi-Hop Wireless Networks
This paper presents a Distributed Efficient Clustering Approach (DECA) for mobility-resistant and energy-efficient clustering in multi-hop wireless networks. The clusterheads cover...
Miao Yu, Jason H. Li, Renato Levy
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
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
15 years 1 months ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles