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IPCO
2008
87views Optimization» more  IPCO 2008»
13 years 10 months ago
Vertex Cover Resists SDPs Tightened by Local Hypermetric Inequalities
We consider the standard semidefinite programming (SDP) relaxation for vertex cover to which all hypermetric inequalities supported on at most k vertices have been added. We show t...
Konstantinos Georgiou, Avner Magen, Iannis Tourlak...
AAAI
2006
13 years 10 months ago
Robust Support Vector Machine Training via Convex Outlier Ablation
One of the well known risks of large margin training methods, such as boosting and support vector machines (SVMs), is their sensitivity to outliers. These risks are normally mitig...
Linli Xu, Koby Crammer, Dale Schuurmans
AUTOMATICA
2008
60views more  AUTOMATICA 2008»
13 years 8 months ago
Control of nonstationary LPV systems
This paper considers control of nonstationary linear parameter-varying systems, and is motivated by interest in the control of nonlinear systems along prespecified trajectories. I...
Mazen Farhood, Geir E. Dullerud
ICIP
2009
IEEE
13 years 6 months ago
Efficient design of 2-D nonseparable filters of low complexity
By using Semi-Definite Programming (SDP) as a tool, a new deign for Two-Dimensional (2-D) Diamond-Shaped (DS) filters is developed. Surprisingly, the diamond shape of the filter is...
Kaveh Fanian, Hoang Duong Tuan, Truong Q. Nguyen
PAKDD
2004
ACM
96views Data Mining» more  PAKDD 2004»
14 years 1 months ago
Spectral Energy Minimization for Semi-supervised Learning
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
Chun Hung Li, Zhi-Li Wu