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CVPR
2010
IEEE
15 years 11 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
145
Voted
ALMOB
2006
113views more  ALMOB 2006»
15 years 4 months ago
Inverse bifurcation analysis: application to simple gene systems
Background: Bifurcation analysis has proven to be a powerful method for understanding the qualitative behavior of gene regulatory networks. In addition to the more traditional for...
James Lu, Heinz W. Engl, Peter Schuster
CVPR
2010
IEEE
15 years 8 months ago
Bayes Optimal Kernel Discriminant Analysis
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
Di You, Aleix Martinez
IJON
2008
88views more  IJON 2008»
15 years 4 months ago
Neural network construction and training using grammatical evolution
The term neural network evolution usually refers to network topology evolution leaving the network's parameters to be trained using conventional algorithms. In this paper we ...
Ioannis G. Tsoulos, Dimitris Gavrilis, Euripidis G...
ML
2006
ACM
121views Machine Learning» more  ML 2006»
15 years 3 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung