3097 search results - page 3 / 620 » Adaptive Manifold Learning |
NIPS
2004
13 years 7 months ago
2004
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
ECCV
2002
Springer
14 years 8 months ago
2002
Springer
Abstract. In many vision problems, the observed data lies in a nonlinear manifold in a high-dimensional space. This paper presents a generic modelling scheme to characterize the no...
MM
2010
ACM
13 years 6 months ago
2010
ACM
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
COLT
2006
Springer
13 years 10 months ago
2006
Springer
Abstract. The regularization functional induced by the graph Laplacian of a random neighborhood graph based on the data is adaptive in two ways. First it adapts to an underlying ma...
FGR
2004
IEEE
13 years 10 months ago
2004
IEEE
Faces under varying illumination, pose and non-rigid deformation are empirically thought of as a highly nonlinear manifold in the observation space. How to discover intrinsic low-...