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PKDD
2009
Springer
153views Data Mining» more  PKDD 2009»
14 years 1 months ago
Subspace Regularization: A New Semi-supervised Learning Method
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-L...
MM
2005
ACM
134views Multimedia» more  MM 2005»
14 years 8 days ago
Graph based multi-modality learning
To better understand the content of multimedia, a lot of research efforts have been made on how to learn from multi-modal feature. In this paper, it is studied from a graph point ...
Hanghang Tong, Jingrui He, Mingjing Li, Changshui ...
FGR
2008
IEEE
304views Biometrics» more  FGR 2008»
14 years 1 months ago
Recovering 3D facial shape via coupled 2D/3D space learning
This paper presents a method for recovering 3D facial shape from single image via learning the relationship between the 2D intensity images and the 3D facial shapes. With a couple...
Annan Li, Shiguang Shan, Xilin Chen, Xiujuan Chai,...
MM
2006
ACM
203views Multimedia» more  MM 2006»
14 years 20 days ago
Learning image manifolds by semantic subspace projection
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
Jie Yu, Qi Tian
ICML
2004
IEEE
14 years 4 days ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul