140 search results - page 2 / 28 » Dimensionality Reduction with Adaptive Kernels |
ICDM
2003
IEEE
13 years 9 months ago
2003
IEEE
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
TNN
2008
13 years 4 months ago
2008
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...
ICDE
2003
IEEE
14 years 5 months ago
2003
IEEE
The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well known approach to o...
PAMI
2011
12 years 11 months ago
2011
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
NIPS
2003
13 years 5 months ago
2003
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...