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JMLR
2006
145views more  JMLR 2006»
13 years 8 months ago
Ensemble Pruning Via Semi-definite Programming
An ensemble is a group of learning models that jointly solve a problem. However, the ensembles generated by existing techniques are sometimes unnecessarily large, which can lead t...
Yi Zhang 0006, Samuel Burer, W. Nick Street
TSP
2010
13 years 3 months ago
Optimal linear fusion for distributed detection via semidefinite programming
Consider the problem of signal detection via multiple distributed noisy sensors. We propose a linear decision fusion rule to combine the local statistics from individual sensors i...
Zhi Quan, Wing-Kin Ma, Shuguang Cui, Ali H. Sayed
CVPR
2007
IEEE
14 years 10 months ago
Solving Large Scale Binary Quadratic Problems: Spectral Methods vs. Semidefinite Programming
In this paper we introduce two new methods for solving binary quadratic problems. While spectral relaxation methods have been the workhorse subroutine for a wide variety of comput...
Carl Olsson, Anders P. Eriksson, Fredrik Kahl
ICCV
2003
IEEE
14 years 10 months ago
Camera calibration using spheres: A semi-definite programming approach
Vision algorithms utilizing camera networks with a common field of view are becoming increasingly feasible and important. Calibration of such camera networks is a challenging and ...
Motilal Agrawal, Larry S. Davis
ICML
2007
IEEE
14 years 9 months ago
Discriminant kernel and regularization parameter learning via semidefinite programming
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
Jieping Ye, Jianhui Chen, Shuiwang Ji