576 search results - page 17 / 116 » Structured metric learning for high dimensional problems |
CVPR
2004
IEEE
15 years 11 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...
102
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NIPS
2008
14 years 11 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 ...
107
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ICCSA
2003
Springer
15 years 2 months 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
14 years 9 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
14 years 11 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...