299 search results - page 25 / 60 » Multiple kernel learning and feature space denoising |
120
Voted
CORR
2010
Springer
15 years 3 months ago
2010
Springer
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
140
Voted
CORR
2006
Springer
15 years 3 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...
128
Voted
CVPR
2010
IEEE
15 years 1 months ago
2010
IEEE
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
143
Voted
NIPS
2001
15 years 4 months ago
2001
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
128
Voted
CORR
2011
Springer
14 years 7 months ago
2011
Springer
We introduce an algorithm that, given n objects, learns a similarity matrix over all n2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen t...