-
1
-
-
0002035566
-
Reducing bias and inefficiency in the selection algorithm
-
J. Grefenstette, editor, Lawrence Erlbaum Associates
-
J. E. Baker. Reducing bias and inefficiency in the selection algorithm. In J. Grefenstette, editor, International Conference on Genetic Algorithms, pages 14-21. Lawrence Erlbaum Associates, 1987.
-
(1987)
International Conference on Genetic Algorithms
, pp. 14-21
-
-
Baker, J.E.1
-
2
-
-
0001955592
-
Using optimal dependency-trees for combinatorial optimization: Learing the structure of the search space
-
D. Fisher, editor
-
S. Baluja and S. Davies. Using optimal dependency-trees for combinatorial optimization: Learing the structure of the search space. In D. Fisher, editor, International Conference on Machine Learning, pages 30-38, 1997.
-
(1997)
International Conference on Machine Learning
, pp. 30-38
-
-
Baluja, S.1
Davies, S.2
-
3
-
-
34548079946
-
Reducing genetic drift in steady state evolutionary algorithms
-
Wolfgang Banzhaf et al, editors, Morgan Kaufmann
-
J. Branke, M. Cutaia, and H. Dold. Reducing genetic drift in steady state evolutionary algorithms. In Wolfgang Banzhaf et al., editors, Genetic and Evolutionary Computation Conference, pages 68-74. Morgan Kaufmann, 1999.
-
(1999)
Genetic and Evolutionary Computation Conference
, pp. 68-74
-
-
Branke, J.1
Cutaia, M.2
Dold, H.3
-
4
-
-
0000848576
-
Analyzing the population based incremental learning algorithm by means of discrete dynamical systems
-
C. Gonzalez, J. Lozano, and P. Larrañaga. Analyzing the population based incremental learning algorithm by means of discrete dynamical systems. Complex Systems, 12(4):465-479, 2001.
-
(2001)
Complex Systems
, vol.12
, Issue.4
, pp. 465-479
-
-
Gonzalez, C.1
Lozano, J.2
Larrañaga, P.3
-
7
-
-
84937437750
-
Optimal mutation rate using bayesian priors for estimation of distribution algorithms
-
Stochastic Algorithms: Foundations and Applications, of
-
T. Mahnig and H. Mühlenbein. Optimal mutation rate using bayesian priors for estimation of distribution algorithms. In Stochastic Algorithms: Foundations and Applications, volume 2264 of LNCS, 2001.
-
(2001)
LNCS
, vol.2264
-
-
Mahnig, T.1
Mühlenbein, H.2
-
8
-
-
84958959530
-
From recombination of genes to the estimation of distributions i: Binary parameters
-
H. Mühlenbein and G. Paaß. From recombination of genes to the estimation of distributions i: Binary parameters. In Parallel Problem Solving from Nature, pages 178-187, 1999.
-
(1999)
Parallel Problem Solving from Nature
, pp. 178-187
-
-
Mühlenbein, H.1
Paaß, G.2
-
9
-
-
0036180213
-
A survey of optimization by building and using probabilistic models
-
M. Pelikan, D. E. Goldberg, and F. Lobo. A survey of optimization by building and using probabilistic models. Computational Optimization and Applications, 21(1):5-20, 2002.
-
(2002)
Computational Optimization and Applications
, vol.21
, Issue.1
, pp. 5-20
-
-
Pelikan, M.1
Goldberg, D.E.2
Lobo, F.3
-
10
-
-
84898960693
-
Scaling of probability-based optimization algorithms
-
Klaus Obermayer, editor, MIT Press
-
J. L. Shapiro. Scaling of probability-based optimization algorithms. In Klaus Obermayer, editor, Advances in Neural Information Processing Systems 15, pages 399-406. MIT Press, 2003.
-
(2003)
Advances in Neural Information Processing Systems 15
, pp. 399-406
-
-
Shapiro, J.L.1
-
11
-
-
15544377453
-
The detailed balance principle in estimation of distribution algorhithm
-
J. L. Shapiro. The detailed balance principle in estimation of distribution algorhithm. Evolutionary Computation, 13(1):99-124, 2005.
-
(2005)
Evolutionary Computation
, vol.13
, Issue.1
, pp. 99-124
-
-
Shapiro, J.L.1
-
12
-
-
33750227208
-
Diversity loss in general estimation of distribution algorithms
-
Parallel Problem Solving from Nature, of, Springer
-
J. L. Shapiro. Diversity loss in general estimation of distribution algorithms. In Parallel Problem Solving from Nature, volume 4193 of LNCS, pages 92-101. Springer, 2006.
-
(2006)
LNCS
, vol.4193
, pp. 92-101
-
-
Shapiro, J.L.1
-
13
-
-
33750234378
-
Does overfitting affect performance in estimation of distribution algorithms
-
ACM
-
H. Wu and J. L. Shapiro. Does overfitting affect performance in estimation of distribution algorithms. In Genetic and Evolutionary Computation Conference, pages 433-434. ACM, 2006.
-
(2006)
Genetic and Evolutionary Computation Conference
, pp. 433-434
-
-
Wu, H.1
Shapiro, J.L.2
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