91 search results - page 16 / 19 » Kernel Dimensionality Reduction for Supervised Learning |
ISDA
2009
IEEE
15 years 7 months ago
2009
IEEE
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
103
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ICML
2006
IEEE
16 years 1 months ago
2006
IEEE
Dimensionality reduction is an important pre-processing step for many applications. Linear Discriminant Analysis (LDA) is one of the well known methods for supervised dimensionali...
164
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CVPR
2012
IEEE
13 years 2 months ago
2012
IEEE
In this article, we focus on the problem of large-scale instance-level image retrieval. For efficiency reasons, it is common to represent an image by a fixed-length descriptor w...
141
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TSMC
2010
14 years 7 months ago
2010
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
100
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ICCV
2009
IEEE
16 years 5 months ago
2009
IEEE
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...