148 search results - page 1 / 30 » Feature space perspectives for learning the kernel |
ML
2007
ACM
13 years 4 months ago
2007
ACM
In this paper, we continue our study of learning an optimal kernel in a prescribed convex set of kernels, [18]. We present a reformulation of this problem within a feature space e...
ML
2006
ACM
13 years 4 months ago
2006
ACM
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
ICMLC
2010
Springer
13 years 3 months ago
2010
Springer
We review a multiple kernel learning (MKL) technique called p regularised multiple kernel Fisher discriminant analysis (MK-FDA), and investigate the effect of feature space denois...
JMLR
2008
13 years 4 months ago
2008
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
NIPS
2008
13 years 6 months ago
2008
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...