576 search results - page 17 / 116 » Structured metric learning for high dimensional problems |
CVPR
2004
IEEE
14 years 9 months ago
2004
IEEE
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
NIPS
2008
13 years 9 months ago
2008
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
ICCSA
2003
Springer
14 years 24 days ago
2003
Springer
The finite difference discretization of the Poisson equation in three dimensions results in a large, sparse, and highly structured system of linear equations. This prototype prob...
JEA
2008
13 years 7 months ago
2008
The Spatial Approximation Tree (sa-tree) is a recently proposed data structure for searching in metric spaces. It has been shown that it compares favorably against alternative data...
NIPS
2004
13 years 9 months ago
2004
Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...