511 search results - page 17 / 103 » The intrinsic dimensionality of graphs |
ICPR
2010
IEEE
14 years 7 days ago
2010
IEEE
—A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach,...
CIKM
2008
Springer
13 years 12 months ago
2008
Springer
Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
COMSIS
2010
13 years 7 months ago
2010
Dimensionality reduction is an important preprocessing step in high-dimensional data analysis without losing intrinsic information. The problem of semi-supervised nonlinear dimensi...
ICCV
2005
IEEE
14 years 3 months ago
2005
IEEE
Recently, nonrigid shape matching has received more and more attention. For nonrigid shapes, most neighboring points cannot move independently under deformation due to physical co...
ICALP
2011
Springer
13 years 1 months ago
2011
Springer
Given a directed graph G = (V, E) and an integer k ≥ 1, a Steiner k-transitive-closure-spanner (Steiner k-TC-spanner) of G is a directed graph H = (VH , EH ) such that (1) V ⊆ ...