117 search results - page 2 / 24 » Dimension Reduction for Supervised Ordering |
DAC
2007
ACM
14 years 6 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...
Publication
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
IJON
2010
13 years 4 months ago
2010
Due to the tremendous increase of electronic information with respect to the size of data sets as well as their dimension, dimension reduction and visualization of high-dimensiona...
IDEAL
2010
Springer
13 years 4 months ago
2010
Springer
Dimension reduction for regression (DRR) deals with the problem of finding for high-dimensional data such low-dimensional representations, which preserve the ability to predict a ...
JMLR
2010
13 years 9 days ago
2010
The goal of sufficient dimension reduction in supervised learning is to find the lowdimensional subspace of input features that is `sufficient' for predicting output values. ...