AAAI
2012
11 years 6 months ago
2012
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
AAAI
2012
11 years 6 months ago
2012
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
PAMI
2012
11 years 7 months ago
2012
—Cross-domain learning methods have shown promising results by leveraging labeled patterns from the auxiliary domain to learn a robust classifier for the target domain which has ...
JMLR
2012
11 years 7 months ago
2012
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
CVPR
2011
IEEE
12 years 12 months ago
2011
IEEE
Kernel methods have been popular over the last decade to solve many computer vision, statistics and machine learning problems. An important, both theoretically and practically, op...
CIARP
2010
Springer
13 years 1 months ago
2010
Springer
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
ML
2007
ACM
13 years 4 months ago
2007
ACM
In many learning problems prior knowledge about pattern variations can be formalized and beneficially incorporated into the analysis system. The corresponding notion of invarianc...
IJON
2002
13 years 4 months ago
2002
Kernel methods have become an increasingly popular tool for machine learning tasks such as classi
SIGKDD
2000
13 years 4 months ago
2000
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
PRL
2006
13 years 4 months ago
2006
This paper presents a general method for incorporating prior knowledge into kernel methods such as Support Vector Machines. It applies when the prior knowledge can be formalized b...