119 search results - page 12 / 24 » Constrained Projection Approximation Algorithms for Principa... |
FTML
2010
13 years 6 months ago
2010
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
ICPR
2006
IEEE
14 years 9 months ago
2006
IEEE
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
SADM
2010
13 years 2 months ago
2010
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
GECCO
2008
Springer
13 years 9 months ago
2008
Springer
This paper studies the issue of space coordinate change in genetic algorithms, based on two methods: convex quadratic approximations, and principal component analysis. In both met...
MM
2006
ACM
14 years 1 months ago
2006
ACM
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...