117 search results - page 4 / 24 » Dimension Reduction for Supervised Ordering |
125
Voted
TSMC
2010
14 years 5 months ago
2010
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
104
Voted
SDM
2009
SIAM
15 years 8 months ago
2009
SIAM
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
112
Voted
SAC
2006
ACM
15 years 4 months ago
2006
ACM
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
CORR
2008
Springer
14 years 11 months ago
2008
Springer
The method of stable random projections is an efficient tool for computing the l distances using low memory, where 0 < 2 may be viewed as a tuning parameter. This method boil...
108
Voted
JMLR
2008
14 years 11 months ago
2008
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...