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» A Bayesian Approach to Tackling Hard Computational Problems
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GECCO
2007
Springer
151views Optimization» more  GECCO 2007»
14 years 4 months ago
Solving real-valued optimisation problems using cartesian genetic programming
Classical Evolutionary Programming (CEP) and Fast Evolutionary Programming (FEP) have been applied to realvalued function optimisation. Both of these techniques directly evolve th...
James Alfred Walker, Julian Francis Miller
ICCAD
1997
IEEE
108views Hardware» more  ICCAD 1997»
14 years 2 months ago
Negative thinking by incremental problem solving: application to unate covering
We introduce a new technique to solve exactly a discrete optimization problem, based on the paradigm of “negative” thinking. The motivation is that when searching the space of...
Evguenii I. Goldberg, Luca P. Carloni, Tiziano Vil...
SIBGRAPI
2005
IEEE
14 years 4 months ago
Particle Filter-Based Predictive Tracking for Robust Fish Counting
In this paper we study the use of computer vision techniques for for underwater visual tracking and counting of fishes in vivo. The methodology is based on the application of a B...
Erikson F. Morais, Mario Fernando Montenegro Campo...
ICTAI
2010
IEEE
13 years 8 months ago
Combining Mixed Integer Programming and Supervised Learning for Fast Re-planning
We introduce a new plan repair method for problems cast as Mixed Integer Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the ...
Emmanuel Rachelson, Ala Ben Abbes, Sebastien Dieme...
CLUSTER
2007
IEEE
14 years 4 months ago
Dynamic scheduling of multi-processor tasks on clusters of clusters
— In this article we tackle the problem of scheduling a dynamically generated DAG of multi-processor tasks (M-tasks). At first, we outline the need of such a scheduling approach...
Sascha Hunold, Thomas Rauber, Gudula Rünger