240 search results - page 9 / 48 » The Kernel Trick for Distances |
80
Voted
ECAI
2008
Springer
14 years 11 months ago
2008
Springer
We extend the resistance distance kernel to the domain of signed dissimilarity values, and show how it can be applied to collaborative rating prediction. The resistance distance is...
84
Voted
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
CORR
2006
Springer
14 years 9 months ago
2006
Springer
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
NIPS
2008
14 years 11 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
CPAIOR
2006
Springer
15 years 1 months ago
2006
Springer
We define the timetable constrained distance minimization problem (TCDMP) which is a sports scheduling problem applicable for tournaments where the total travel distance must be mi...