1416 search results - page 92 / 284 » The Kernel Least-Mean-Square Algorithm |
142
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ICCV
2009
IEEE
16 years 8 months ago
2009
IEEE
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
132
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CVPR
2006
IEEE
16 years 5 months ago
2006
IEEE
Segmentation involves separating an object from the background. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, within...
139
Voted
ICPR
2006
IEEE
16 years 4 months ago
2006
IEEE
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
121
Voted
SYNASC
2007
IEEE
15 years 9 months ago
2007
IEEE
In recent years several models have been proposed for text categorization. Within this, one of the widely applied models is the vector space model (VSM), where independence betwee...
135
Voted
NIPS
2008
15 years 4 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...