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» Solving Hierarchical Optimization Problems Using MOEAs
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ICML
2009
IEEE
14 years 11 months ago
Sparse Gaussian graphical models with unknown block structure
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
Benjamin M. Marlin, Kevin P. Murphy
ICCAD
1999
IEEE
101views Hardware» more  ICCAD 1999»
14 years 2 months ago
Efficient model reduction of interconnect via approximate system gramians
Krylov-subspace based methods for generating low-order models of complicated interconnect are extremely effective, but there is no optimality theory for the resulting models. Alte...
Jing-Rebecca Li, Jacob White
PR
2010
151views more  PR 2010»
13 years 9 months ago
Coupled region-edge shape priors for simultaneous localization and figure-ground segmentation
We propose a new algorithm for simultaneous localization and figure-ground segmentation where coupled region-edge shape priors are involved with two different but complementary ...
Cheng Chen, Guoliang Fan
ICIP
2010
IEEE
13 years 8 months ago
3D augmented Markov random field for object recognition
In this paper, we propose to use 3D information to augment the Markov random field (MRF) model for object recognition. Conventional MRF for image-based object recognition usually ...
Wei Yu, Ahmed Bilal Ashraf, Yao-Jen Chang, Congcon...
EVOW
2010
Springer
14 years 5 months ago
Parameter Tuning of Evolutionary Algorithms: Generalist vs. Specialist
Abstract. Finding appropriate parameter values for Evolutionary Algorithms (EAs) is one of the persistent challenges of Evolutionary Computing. In recent publications we showed how...
Selmar K. Smit, A. E. Eiben