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» Learning from Highly Structured Data by Decomposition
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CVPR
2008
IEEE
16 years 5 days ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
JMLR
2010
119views more  JMLR 2010»
14 years 5 months ago
Factorized Orthogonal Latent Spaces
Existing approaches to multi-view learning are particularly effective when the views are either independent (i.e, multi-kernel approaches) or fully dependent (i.e., shared latent ...
Mathieu Salzmann, Carl Henrik Ek, Raquel Urtasun, ...
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MICCAI
2010
Springer
14 years 8 months ago
Endoscopic Video Manifolds
Postprocedural analysis of gastrointestinal (GI) endoscopic videos is a difficult task because the videos often suffer from a large number of poor-quality frames due to the motion...
Selen Atasoy, Diana Mateus, Joe Lallemand, Alexand...
ACML
2009
Springer
15 years 4 months ago
Robust Discriminant Analysis Based on Nonparametric Maximum Entropy
In this paper, we propose a Robust Discriminant Analysis based on maximum entropy (MaxEnt) criterion (MaxEnt-RDA), which is derived from a nonparametric estimate of Renyi’s quadr...
Ran He, Bao-Gang Hu, Xiaotong Yuan
ICMCS
2006
IEEE
181views Multimedia» more  ICMCS 2006»
15 years 4 months ago
Toward Intelligent Use of Semantic Information on Subspace Discovery for Image Retrieval
Image retrieval has been widely used in many fields of science and engineering. The semantic concept of user interest is obtained by a learning process. Traditional techniques oft...
Jie Yu, Qi Tian