43 search results - page 2 / 9 » On Low Distortion Embeddings of Statistical Distance Measure... |
DAGM
2009
Springer
14 years 3 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 9 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
14 years 14 days 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 10 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 10 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...