169 search results - page 2 / 34 » Reductions among high dimensional proximity problems |
PODS
2001
ACM
14 years 5 months ago
2001
ACM
The dimensionality curse has profound e ects on the effectiveness of high-dimensional similarity indexing from the performance perspective. One of the well known techniques for im...
MCS
2001
Springer
13 years 10 months ago
2001
Springer
Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many machine learning problems [4, 16]. However, the exten...
CCGRID
2010
IEEE
13 years 6 months ago
2010
IEEE
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...
ICML
2005
IEEE
14 years 6 months ago
2005
IEEE
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
This paper proposes a new map building framework for mobile robot named Localization-Free Mapping by Dimensionality Reduction (LFMDR). In this framework, the robot map building is...