57 search results - page 6 / 12 » Convergence and Rate of Convergence of a Manifold-Based Dime... |
JMLR
2010
13 years 2 months ago
2010
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
JGO
2010
13 years 5 months ago
2010
In this paper, the global optimization problem with an objective function that is multiextremal that satisfies the Lipschitz condition over a hypercube is considered. An algorithm...
IJON
2008
13 years 7 months ago
2008
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...
COLT
2004
Springer
14 years 23 days ago
2004
Springer
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...