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» Approximate algorithms for neural-Bayesian approaches
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FSTTCS
2006
Springer
15 years 1 months ago
Approximation Algorithms for 2-Stage Stochastic Optimization Problems
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
Chaitanya Swamy, David B. Shmoys
SMC
2010
IEEE
158views Control Systems» more  SMC 2010»
14 years 7 months ago
A study of genetic algorithms for approximating the longest path in generic graphs
Abstract--Finding the longest simple path in a generic undirected graph is a challenging issue that belongs to the NPComplete class of problems. Four approaches based on genetic al...
David Portugal, Carlos Henggeler Antunes, Rui Roch...
CEC
2007
IEEE
14 years 11 months ago
Multi-population approach to approximate the development of neocortical networks
— Cultured natural cortical neurons form functional networks through a complex set of developmental steps during the first weeks in vitro. The dynamic behavior of the network in...
Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana...
ICCAD
2001
IEEE
107views Hardware» more  ICCAD 2001»
15 years 6 months ago
A Convex Programming Approach to Positive Real Rational Approximation
As system integration evolves and tighter design constraints must be met, it becomes necessary to account for the non-ideal behavior of all the elements in a system. Certain devic...
Carlos P. Coelho, Joel R. Phillips, Luis Miguel Si...
CIAC
2006
Springer
100views Algorithms» more  CIAC 2006»
15 years 1 months ago
Distributed Approximation Algorithms for Planar Graphs
In this paper we construct two distributed algorithms for computing approximations of a largest matching and a minimum dominating set in planar graphs on n vertices. The approximat...
Andrzej Czygrinow, Michal Hanckowiak, Edyta Szyman...