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ICML
2003
IEEE
14 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
ICCV
2001
IEEE
14 years 11 months ago
Image Segmentation by Data Driven Markov Chain Monte Carlo
?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
Zhuowen Tu, Song Chun Zhu, Heung-Yeung Shum
DAGSTUHL
2004
13 years 10 months ago
Optimal algorithms for global optimization in case of unknown Lipschitz constant
We consider the global optimization problem for d-variate Lipschitz functions which, in a certain sense, do not increase too slowly in a neighborhood of the global minimizer(s). O...
Matthias U. Horn
ENC
2003
IEEE
14 years 2 months ago
Multiobjective-Based Concepts to Handle Constraints in Evolutionary Algorithms
This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of...
Efrén Mezura-Montes, Carlos A. Coello Coell...
GECCO
2005
Springer
141views Optimization» more  GECCO 2005»
14 years 2 months ago
Local and global order 3/2 convergence of a surrogate evolutionary algorithm
A Quasi-Monte-Carlo method based on the computation of a surrogate model of the fitness function is proposed, and its convergence at super-linear rate 3/2 is proved under rather ...
Anne Auger, Marc Schoenauer, Olivier Teytaud