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» Learning low dimensional predictive representations
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CVPR
2001
IEEE
14 years 9 months ago
Learning Probabilistic Distribution Model for Multi-View Face Detection
Modeling subspaces of a distribution of interest in high dimensional spaces is a challenging problem in pattern analysis. In this paper, we present a novel framework for pose inva...
Lie Gu, Stan Z. Li, HongJiang Zhang
NIPS
2001
13 years 8 months ago
Global Coordination of Local Linear Models
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinto...
CORR
2011
Springer
150views Education» more  CORR 2011»
13 years 2 months ago
Total variation regularization for fMRI-based prediction of behaviour
—While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional MRI ...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
JMLR
2010
119views more  JMLR 2010»
13 years 2 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, ...
AAAI
2008
13 years 9 months ago
Dimension Amnesic Pyramid Match Kernel
With the success of local features in object recognition, feature-set representations are widely used in computer vision and related domains. Pyramid match kernel (PMK) is an effi...
Yi Liu, Xulei Wang, Hongbin Zha