98 search results - page 6 / 20 » Regression on manifolds using kernel dimension reduction |
DAC
2007
ACM
14 years 7 months ago
2007
ACM
The ability to account for the growing impacts of multiple process variations in modern technologies is becoming an integral part of nanometer VLSI design. Under the context of ti...
AMR
2007
Springer
14 years 27 days ago
2007
Springer
Distance measures, along with shape features, are the most critical components in a shape-based 3D model retrieval system. Given a shape feature, an optimal distance measure will v...
FLAIRS
2004
13 years 8 months ago
2004
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
CVPR
2010
IEEE
14 years 2 months ago
2010
IEEE
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...
BMVC
2010
13 years 4 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...