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» Sparse Kernels for Bayes Optimal Discriminant Analysis
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ICCV
1999
IEEE
13 years 9 months ago
Epipolar Geometry Estimation by Tensor Voting in 8D
We present a novel, efficient, initializationfree approach to the problem of epipolar geometry estimation, by formulating it as one of hyperplane inference from a sparse and noisy...
Chi-Keung Tang, Gérard G. Medioni, Mi-Suen ...
SIAMIS
2010
156views more  SIAMIS 2010»
13 years 1 days ago
Learning the Morphological Diversity
This article proposes a new method for image separation into a linear combination of morphological components. Sparsity in fixed dictionaries is used to extract the cartoon and osc...
Gabriel Peyré, Jalal Fadili, Jean-Luc Starc...
TNN
2010
234views Management» more  TNN 2010»
13 years 18 hour ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
BMCBI
2007
194views more  BMCBI 2007»
13 years 5 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
BMCBI
2006
173views more  BMCBI 2006»
13 years 5 months ago
Kernel-based distance metric learning for microarray data classification
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Huilin Xiong, Xue-wen Chen