543 search results - page 24 / 109 » Nonlinear principal component analysis of noisy data |
ICRA
2007
IEEE
14 years 2 months ago
2007
IEEE
— This paper presents a technique to improve the data association in the Iterative Closest Point [2] based scan matching. The method is based on a distance-filter constructed on...
PR
2006
13 years 7 months ago
2006
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
IDA
1998
Springer
13 years 7 months ago
1998
Springer
A fast and simple algorithm for approximately calculating the principal components (PCs) of a data set and so reducing its dimensionality is described. This Simple Principal Compo...
NIPS
2003
13 years 9 months ago
2003
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
When performing subspace modelling of data using Principal Component Analysis (PCA) it may be desirable to constrain certain directions to be more meaningful in the context of the...