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IEEEPACT
2008
IEEE
15 years 4 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
86
Voted
ICML
2003
IEEE
15 years 2 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens
SIGADA
2004
Springer
15 years 3 months ago
Comparative analysis of genetic algorithm implementations
Genetic Algorithms provide computational procedures that are modeled on natural genetic system mechanics, whereby a coded solution is “evolved” from a set of potential solutio...
Robert Soricone, Melvin Neville
GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
15 years 1 months ago
Domain Knowledge and Representation in Genetic Algorithms for Real World Scheduling Problems
This paper discusses the issues that arise in the design and implementation of an industrialstrength evolutionary-based system for the optimization of the monthly work schedules f...
Ioannis T. Christou, Armand Zakarian
GECCO
2004
Springer
115views Optimization» more  GECCO 2004»
15 years 3 months ago
Parameter-Less Hierarchical BOA
Abstract. The parameter-less hierarchical Bayesian optimization algorithm (hBOA) enables the use of hBOA without the need for tuning parameters for solving each problem instance. T...
Martin Pelikan, Tz-Kai Lin