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SIAMJO
2008
212views more  SIAMJO 2008»
13 years 4 months ago
Convergence Rate of an Optimization Algorithm for Minimizing Quadratic Functions with Separable Convex Constraints
A new active set algorithm for minimizing quadratic functions with separable convex constraints is proposed by combining the conjugate gradient method with the projected gradient. ...
Radek Kucera
MP
2002
195views more  MP 2002»
13 years 4 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
IPCO
2010
153views Optimization» more  IPCO 2010»
13 years 2 months ago
An Effective Branch-and-Bound Algorithm for Convex Quadratic Integer Programming
We present a branch-and-bound algorithm for minimizing a convex quadratic objective function over integer variables subject to convex constraints. In a given node of the enumerati...
Christoph Buchheim, Alberto Caprara, Andrea Lodi
CORR
2008
Springer
133views Education» more  CORR 2008»
13 years 4 months ago
Estimating divergence functionals and the likelihood ratio by convex risk minimization
We develop and analyze M-estimation methods for divergence functionals and the likelihood ratios of two probability distributions. Our method is based on a non-asymptotic variatio...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
CVPR
2008
IEEE
14 years 6 months ago
Interactive image segmentation via minimization of quadratic energies on directed graphs
We propose a scheme to introduce directionality in the Random Walker algorithm for image segmentation. In particular, we extend the optimization framework of this algorithm to com...
Dheeraj Singaraju, Leo Grady, René Vidal