43 search results - page 2 / 9 » On Low Distortion Embeddings of Statistical Distance Measure... |
DAGM
2009
Springer
13 years 11 months ago
2009
Springer
This paper describes a new approach for detecting objects based on measuring the spatial consistency between different parts of an object. These parts are pre-defined on a set of...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
COMPGEOM
2007
ACM
13 years 9 months ago
2007
ACM
In this paper we show that dimensionality reduction (i.e., Johnson-Lindenstrauss lemma) preserves not only the distances between static points, but also between moving points, and...
CIKM
2008
Springer
13 years 7 months ago
2008
Springer
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. However, many si...
SODA
2008
ACM
13 years 6 months ago
2008
ACM
We consider the problem of embedding a metric into low-dimensional Euclidean space. The classical theorems of Bourgain, and of Johnson and Lindenstrauss say that any metric on n p...