624 search results - page 17 / 125 » The Tradeoffs of Large Scale Learning |
CVPR
2010
IEEE
13 years 11 months ago
2010
IEEE
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
JMLR
2008
13 years 7 months ago
2008
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
CVPR
2011
IEEE
13 years 3 months ago
2011
IEEE
This paper addresses the problem of similar image retrieval, especially in the setting of large-scale datasets with millions to billions of images. The core novel contribution is ...
SIGIR
2006
ACM
14 years 1 months ago
2006
ACM
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
SAINT
2005
IEEE
14 years 1 months ago
2005
IEEE
Inductive Logic Programming (ILP) is a combination of inductive learning and first-order logic aiming to learn first-order hypotheses from training examples. ILP has a serious b...