396 search results - page 13 / 80 » Lossy Reduction for Very High Dimensional Data |
KDD
2001
ACM
16 years 3 days 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...
128
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BMCBI
2010
14 years 12 months ago
2010
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
101
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ICML
2010
IEEE
15 years 24 days ago
2010
IEEE
We propose a new dimensionality reduction method, the elastic embedding (EE), that optimises an intuitive, nonlinear objective function of the low-dimensional coordinates of the d...
ICANN
2009
Springer
15 years 4 months ago
2009
Springer
Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
CVPR
2010
IEEE
15 years 7 months ago
2010
IEEE
We introduce a parametric version (pDRUR) of the recently proposed Dimensionality Reduction by Unsupervised Regression algorithm. pDRUR alternately minimizes reconstruction error ...