604 search results - page 1 / 121 » Regularization and feature selection for networked features |
CIKM
2010
Springer
13 years 2 months ago
2010
Springer
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
CIKM
2011
Springer
12 years 4 months ago
2011
Springer
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
IWANN
2009
Springer
13 years 11 months ago
2009
Springer
This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
JMLR
2010
12 years 11 months ago
2010
We propose a novel group regularization which we call exclusive lasso. Unlike the group lasso regularizer that assumes covarying variables in groups, the proposed exclusive lasso ...