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» Generalized Boosting Algorithms for Convex Optimization
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JOTA
2010
117views more  JOTA 2010»
13 years 7 months ago
Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization
We consider a distributed multi-agent network system where the goal is to minimize a sum of agent objective functions subject to a common set of constraints. For this problem, we p...
S. Sundhar Ram, Angelia Nedic, Venugopal V. Veerav...
SIAMJO
2008
85views more  SIAMJO 2008»
13 years 8 months ago
Explicit Reformulations for Robust Optimization Problems with General Uncertainty Sets
We consider a rather general class of mathematical programming problems with data uncertainty, where the uncertainty set is represented by a system of convex inequalities. We prove...
Igor Averbakh, Yun-Bin Zhao
CORR
2007
Springer
104views Education» more  CORR 2007»
13 years 8 months ago
Separable convex optimization problems with linear ascending constraints
Separable convex optimization problems with linear ascending inequality and equality constraints are addressed in this paper. An algorithm that explicitly characterizes the optimum...
Arun Padakandla, Rajesh Sundaresan
ICML
2004
IEEE
14 years 9 months ago
Leveraging the margin more carefully
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...
Nir Krause, Yoram Singer
ICPR
2006
IEEE
14 years 9 months ago
A novel SVM Geometric Algorithm based on Reduced Convex Hulls
Geometric methods are very intuitive and provide a theoretically solid viewpoint to many optimization problems. SVM is a typical optimization task that has attracted a lot of atte...
Michael E. Mavroforakis, Margaritis Sdralis, Sergi...