66 search results - page 3 / 14 » Learning Sparse SVM for Feature Selection on Very High Dimen... |
UAI
2008
13 years 6 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...
ICML
2009
IEEE
14 years 6 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...
SDM
2008
SIAM
13 years 6 months ago
2008
SIAM
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
SDM
2011
SIAM
12 years 8 months ago
2011
SIAM
Latent semantic analysis (LSA), as one of the most popular unsupervised dimension reduction tools, has a wide range of applications in text mining and information retrieval. The k...
JMLR
2012
11 years 7 months ago
2012
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...