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DAGSTUHL
2007
15 years 5 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
121
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CORR
2008
Springer
129views Education» more  CORR 2008»
15 years 3 months ago
Evolving Dynamic Change and Exchange of Genotype Encoding in Genetic Algorithms for Difficult Optimization Problems
The application of genetic algorithms (GAs) to many optimization problems in organizations often results in good performance and high quality solutions. For successful and efficien...
Maroun Bercachi, Philippe Collard, Manuel Clergue,...
UAI
2008
15 years 5 months ago
Learning Inclusion-Optimal Chordal Graphs
Chordal graphs can be used to encode dependency models that are representable by both directed acyclic and undirected graphs. This paper discusses a very simple and efficient algo...
Vincent Auvray, Louis Wehenkel
110
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MICAI
2004
Springer
15 years 9 months ago
An Optimization Algorithm Based on Active and Instance-Based Learning
We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...
Olac Fuentes, Thamar Solorio
114
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RTS
2010
103views more  RTS 2010»
15 years 2 months ago
LRE-TL: an optimal multiprocessor algorithm for sporadic task sets with unconstrained deadlines
This article presents a detailed discussion of LRE-TL (Local Remaining Execution - TL-plane), an algorithm that schedules hard real-time periodic and sporadic task sets with uncon...
Shelby Funk