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PKDD
2009
Springer
153views Data Mining» more  PKDD 2009»
15 years 4 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»
15 years 3 months 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»
15 years 4 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»
15 years 3 months 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
15 years 3 months 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