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» Learning the Structure of Linear Latent Variable Models
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ECCV
2004
Springer
14 years 9 months ago
Dimensionality Reduction by Canonical Contextual Correlation Projections
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
Marco Loog, Bram van Ginneken, Robert P. W. Duin
AAAI
2010
13 years 9 months ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos
ISCI
2008
165views more  ISCI 2008»
13 years 7 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...
IPMI
2007
Springer
14 years 8 months ago
Shape Regression Machine
Abstract. We present a machine learning approach called shape regression machine (SRM) to segmenting in real time an anatomic structure that manifests a deformable shape in a medic...
Shaohua Kevin Zhou, Dorin Comaniciu
CVPR
2005
IEEE
14 years 9 months ago
Hallucinating Faces: TensorPatch Super-Resolution and Coupled Residue Compensation
In this paper, we propose a new face hallucination framework based on image patches, which integrates two novel statistical super-resolution models. Considering that image patches...
Wei Liu, Dahua Lin, Xiaoou Tang