21 search results - page 2 / 5 » Analyzing High-Dimensional Data by Subspace Validity |
NPL
1998
13 years 5 months ago
1998
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
IJCAI
2007
13 years 7 months ago
2007
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
ICCV
2011
IEEE
12 years 6 months ago
2011
IEEE
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
KDD
2005
ACM
13 years 11 months ago
2005
ACM
The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
DMIN
2008
13 years 7 months ago
2008
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...