39 search results - page 3 / 8 » Covariance Regularization for Supervised Learning in High Di... |
ECML
2006
Springer
14 years 6 days ago
2006
Springer
We perform a systematic evaluation of feature selection (FS) methods for support vector machines (SVMs) using simulated high-dimensional data (up to 5000 dimensions). Several findi...
IDEAL
2010
Springer
13 years 7 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 ...
UAI
2008
13 years 10 months ago
2008
Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of linearly ordered features, as one...
SDM
2008
SIAM
13 years 10 months ago
2008
SIAM
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
IJON
2010
13 years 7 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...