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CDC
2008
IEEE
124views Control Systems» more  CDC 2008»
14 years 3 months ago
A proximal center-based decomposition method for multi-agent convex optimization
— In this paper we develop a new dual decomposition method for optimizing a sum of convex objective functions corresponding to multiple agents but with coupled constraints. In ou...
Ion Necoara, Johan A. K. Suykens
ESA
2006
Springer
131views Algorithms» more  ESA 2006»
14 years 22 days ago
Finding Total Unimodularity in Optimization Problems Solved by Linear Programs
A popular approach in combinatorial optimization is to model problems as integer linear programs. Ideally, the relaxed linear program would have only integer solutions, which happ...
Christoph Dürr, Mathilde Hurand
MP
2002
195views more  MP 2002»
13 years 8 months ago
Nonlinear rescaling vs. smoothing technique in convex optimization
We introduce an alternative to the smoothing technique approach for constrained optimization. As it turns out for any given smoothing function there exists a modification with part...
Roman A. Polyak
NIPS
2007
13 years 10 months ago
Boosting Algorithms for Maximizing the Soft Margin
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...
ICALP
1990
Springer
14 years 1 months ago
Determining the Separation of Preprocessed Polyhedra - A Unified Approach
We show how (now familiar) hierarchical representations of (convex) polyhedra can be used to answer various separation queries efficiently (in a number of cases, optimally). Our e...
David P. Dobkin, David G. Kirkpatrick