94 search results - page 7 / 19 » Variable Sparsity Kernel Learning |
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
CVPR
2004
IEEE
15 years 1 months ago
2004
IEEE
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
NIPS
2008
14 years 11 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...
ECAI
2010
Springer
14 years 6 months ago
2010
Springer
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
111
click to vote
NIPS
2004
14 years 11 months ago
2004
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...