625 search results - page 47 / 125 » Large-scale manifold learning |
ECCV
2002
Springer
14 years 11 months ago
2002
Springer
Abstract. In many vision problems, the observed data lies in a nonlinear manifold in a high-dimensional space. This paper presents a generic modelling scheme to characterize the no...
ESANN
2006
13 years 11 months ago
2006
We present an extension to a recent method for learning of nonlinear manifolds, which allows to incorporate general cost functions. We focus on the -insensitive loss and visually d...
PRIB
2009
Springer
14 years 4 months ago
2009
Springer
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
CVPR
2006
IEEE
14 years 12 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
MIR
2005
ACM
14 years 3 months ago
2005
ACM
We propose a new method for automated large scale gathering of Web images relevant to specified concepts. Our main goal is to build a knowledge base associated with as many conce...