175 search results - page 14 / 35 » A DC-programming algorithm for kernel selection |
MLDM
2007
Springer
14 years 2 months ago
2007
Springer
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
JCP
2008
13 years 8 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...
ECML
2003
Springer
14 years 1 months ago
2003
Springer
We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the origin...
ECML
2006
Springer
14 years 8 days 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...
JMLR
2006
13 years 8 months ago
2006
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...