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» Minimizing Convex Functions with Bounded Perturbations
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JGO
2010
100views more  JGO 2010»
14 years 4 months ago
On convex relaxations of quadrilinear terms
The best known method to find exact or at least -approximate solutions to polynomial programming problems is the spatial Branch-and-Bound algorithm, which rests on computing lower...
Sonia Cafieri, Jon Lee, Leo Liberti
FOCS
2007
IEEE
15 years 3 months ago
On the Hardness and Smoothed Complexity of Quasi-Concave Minimization
In this paper, we resolve the smoothed and approximative complexity of low-rank quasi-concave minimization, providing both upper and lower bounds. As an upper bound, we provide th...
Jonathan A. Kelner, Evdokia Nikolova
EOR
2008
159views more  EOR 2008»
14 years 9 months ago
A survey on the continuous nonlinear resource allocation problem
Our problem of interest consists of minimizing a separable, convex and differentiable function over a convex set, defined by bounds on the variables and an explicit constraint des...
Michael Patriksson
91
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CRV
2006
IEEE
223views Robotics» more  CRV 2006»
15 years 3 months ago
Disparity Map Estimation Using A Total Variation Bound
This paper describes a new variational method for estimating disparity from stereo images. The stereo matching problem is formulated as a convex programming problem in which an ob...
Wided Miled, Jean-Christophe Pesquet
JOTA
2010
117views more  JOTA 2010»
14 years 8 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...