159 search results - page 7 / 32 » Regularization in matrix relevance learning |
117
click to vote
SIAMJO
2010
14 years 6 months ago
2010
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
JMLR
2010
14 years 6 months ago
2010
Kernel approximation is commonly used to scale kernel-based algorithms to applications containing as many as several million instances. This paper analyzes the effect of such appr...
CIKM
2009
Springer
15 years 6 months ago
2009
Springer
Relevance Feedback has proven very effective for improving retrieval accuracy. A difficult yet important problem in all relevance feedback methods is how to optimally balance the...
107
click to vote
KDD
2007
ACM
16 years 6 days ago
2007
ACM
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
125
click to vote
PAMI
2011
14 years 6 months ago
2011
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...