334 search results - page 21 / 67 » Local Dimensionality Reduction: A New Approach to Indexing H... |
ECCV
2010
Springer
14 years 19 days ago
2010
Springer
This paper presents algorithms for efficiently computing the covariance matrix for features that form sub-windows in a large multidimensional image. For example, several image proc...
SAC
2006
ACM
14 years 1 months ago
2006
ACM
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
NPL
1998
13 years 7 months ago
1998
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
ICPR
2008
IEEE
14 years 8 months ago
2008
IEEE
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
IJON
2010
13 years 4 months ago
2010
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...