119 search results - page 10 / 24 » Sparse kernel methods for high-dimensional survival data |
TSP
2008
13 years 8 months ago
2008
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
IWANN
2009
Springer
14 years 3 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 ...
TSP
2008
13 years 8 months ago
2008
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
KDD
2004
ACM
14 years 8 months ago
2004
ACM
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
ICANN
2007
Springer
14 years 9 days ago
2007
Springer
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...