1224 search results - page 62 / 245 » On the Optimality of the Dimensionality Reduction Method |
167
Voted
ICPR
2008
IEEE
16 years 18 days ago
2008
IEEE
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
172
Voted
ICPR
2006
IEEE
16 years 7 months ago
2006
IEEE
We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually non...
174
Voted
ICML
2006
IEEE
16 years 7 months ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
182
Voted
SIGIR
2005
ACM
15 years 11 months ago
2005
ACM
Latent semantic indexing (LSI) is a well-known unsupervised approach for dimensionality reduction in information retrieval. However if the output information (i.e. category labels...
180
Voted
TNN
2008
15 years 6 months ago
2008
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...