468 search results - page 59 / 94 » Riemannian Manifold Learning |
COLT
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. The regularization functional induced by the graph Laplacian of a random neighborhood graph based on the data is adaptive in two ways. First it adapts to an underlying ma...
NIPS
2001
13 years 9 months ago
2001
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
MM
2009
ACM
14 years 2 months ago
2009
ACM
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
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...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to use...