28 search results - page 3 / 6 » An SVD and Derivative Kernel Approach to Learning from Geome... |
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
Proportional data (normalized histograms) have been frequently occurring in various areas, and they could be mathematically abstracted as points residing in a geometric simplex. A...
JCP
2008
13 years 5 months ago
2008
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
ICCV
2005
IEEE
14 years 7 months ago
2005
IEEE
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
BMCBI
2007
13 years 5 months ago
2007
Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...