133 search results - page 3 / 27 » Adaptive metric dimensionality reduction |
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
ACL
2010
13 years 3 months ago
2010
We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by ...
ACMSE
2005
ACM
13 years 10 months ago
2005
ACM
This paper explores a method for re-sequencing an existing set of animation, specifically motion capture data, to generate new motion. Re-using animation is helpful in designing ...
SIAMSC
2008
13 years 4 months ago
2008
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...