36 search results - page 5 / 8 » Connecting spectral and spring methods for manifold learning |
NIPS
2003
13 years 7 months ago
2003
Spectral methods for nonlinear dimensionality reduction (NLDR) impose a neighborhood graph on point data and compute eigenfunctions of a quadratic form generated from the graph. W...
ICASSP
2009
IEEE
13 years 3 months ago
2009
IEEE
Digital compensation of nonlinear systems is an important topic in many practical applications. This paper considers the problem of predistortion of nonlinear systems described us...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
We consider the problem of dimensionality reduction, where given high-dimensional data we want to estimate two mappings: from high to low dimension (dimensionality reduction) and f...
MM
2009
ACM
14 years 4 days 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 ...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
This paper introduces a new approach to actionvalue function approximation by learning basis functions from a spectral decomposition of the state-action manifold. This paper exten...