3006 search results - page 21 / 602 » Dimensionality reduction and generalization |
NIPS
2008
13 years 10 months ago
2008
This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
CIVR
2008
Springer
13 years 10 months ago
2008
Springer
Since the emergence of extensive multimedia data, feature fusion has been more and more important for image and video retrieval, indexing and annotation. Existing feature fusion t...
ICCV
2007
IEEE
14 years 2 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
PR
2006
13 years 8 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...
SISAP
2008
IEEE
14 years 3 months ago
2008
IEEE
There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information...