119 search results - page 1 / 24 » Sparse kernel methods for high-dimensional survival data |
UAI
2000
13 years 6 months ago
2000
This paper is about the use of metric data structures in high-dimensionalor non-Euclidean space to permit cached sufficientstatisticsaccelerationsof learning algorithms. It has re...
BIOINFORMATICS
2008
13 years 5 months ago
2008
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
ICONIP
2007
13 years 6 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
ICDE
2008
IEEE
14 years 6 months ago
2008
IEEE
Abstract-- Existing research on privacy-preserving data publishing focuses on relational data: in this context, the objective is to enforce privacy-preserving paradigms, such as ka...