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» Boosting margin based distance functions for clustering
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KAIS
2006
110views more  KAIS 2006»
13 years 5 months ago
Multi-step density-based clustering
Abstract. Data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. In many areas, complex dista...
Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfei...
ICASSP
2011
IEEE
12 years 9 months ago
Similarity learning for semi-supervised multi-class boosting
In semi-supervised classification boosting, a similarity measure is demanded in order to measure the distance between samples (both labeled and unlabeled). However, most of the e...
Q. Y. Wang, Pong Chi Yuen, Guo-Can Feng
CIBCB
2005
IEEE
13 years 11 months ago
Functional Distances for Genes Based on GO Feature Maps and their Application to Clustering
— With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data, the need for a functiona...
Nora Speer, Holger Fröhlich, Christian Spieth...
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
13 years 2 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu
ML
2002
ACM
167views Machine Learning» more  ML 2002»
13 years 5 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...