59 search results - page 6 / 12 » REDUS: finding reducible subspaces in high dimensional data |
ICANN
2007
Springer
14 years 7 days ago
2007
Springer
In the field of computer vision feature matching in high dimensional feature spaces is a commonly used technique for object recognition. One major problem is to find an adequate s...
DEXA
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. Nearest neighbor search has a wide variety of applications. Unfortunately, the majority of search methods do not scale well with dimensionality. Recent efforts have been ...
CVPR
2007
IEEE
14 years 8 months ago
2007
IEEE
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
BMCBI
2006
13 years 6 months ago
2006
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
TKDE
2010
13 years 23 days ago
2010
The sparse data is becoming increasingly common and available in many real-life applications. However, relative little attention has been paid to effectively model the sparse data ...