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» Classification with Sums of Separable Functions
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CDC
2008
IEEE
124views Control Systems» more  CDC 2008»
14 years 4 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
DAS
2010
Springer
14 years 28 days ago
Improved classification through runoff elections
We consider the problem of dealing with irrelevant votes when a multi-case classifier is built from an ensemble of binary classifiers. We show how run-off elections can be used to...
Oleg Golubitsky, Stephen M. Watt
SIAMIS
2011
13 years 4 months ago
Gradient-Based Methods for Sparse Recovery
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
William W. Hager, Dzung T. Phan, Hongchao Zhang
ICPR
2008
IEEE
14 years 4 months ago
Tree-serial dynamic programming for image processing
A lot of image analysis problems lend themselves to a unified mathematical formulation as optimization problems. Tree-serial dynamic programming is a particular case of the so-cal...
Andrey Kopylov
AAAI
2008
13 years 12 months ago
Classification by Discriminative Regularization
Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...