159 search results - page 9 / 32 » Margin Maximizing Loss Functions |
137
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JMLR
2010
14 years 6 months ago
2010
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
115
Voted
VLSM
2005
Springer
15 years 5 months ago
2005
Springer
We present a computationally efficient segmentationrestoration method, based on a probabilistic formulation, for the joint estimation of the label map (segmentation) and the para...
COLT
2004
Springer
15 years 5 months ago
2004
Springer
Abstract. We study two boosting algorithms, Coordinate Ascent Boosting and Approximate Coordinate Ascent Boosting, which are explicitly designed to produce maximum margins. To deri...
87
Voted
PKDD
2009
Springer
15 years 6 months ago
2009
Springer
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
132
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CVPR
2009
IEEE
16 years 6 months ago
2009
IEEE
Feature selection plays a fundamental role in many pattern
recognition problems. However, most efforts have been
focused on the supervised scenario, while unsupervised feature
s...