267 search results - page 2 / 54 » New Algorithms for Efficient High-Dimensional Nonparametric ... |
CVPR
2004
IEEE
14 years 6 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...
SIGMOD
2009
ACM
14 years 4 months ago
2009
ACM
Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational data...
KDD
2001
ACM
14 years 5 months ago
2001
ACM
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
SIAMSC
2008
13 years 4 months ago
2008
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...