148 search results - page 2 / 30 » Riemannian Manifold Learning for Nonlinear Dimensionality Re... |
PAMI
2006
13 years 4 months ago
2006
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Non-linear dimensionality reduction of noisy data is a challenging problem encountered in a variety of data analysis applications. Recent results in the literature show that spect...
ECCV
2006
Springer
14 years 6 months ago
2006
Springer
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
BMVC
2010
13 years 2 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
CVPR
2006
IEEE
14 years 6 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...