Baum, E.B., Boneh, D., Garrett, C.: Where genetic algorithms excel. In: Proceedings COLT 1995, Santa Cruz, California (1995)  Home/Search Document Details and Download
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MIMIC: Finding Optima by Estimating Probability Densities - De Bonet, Isbell, Jr., Viola (1996) (40 citations) (Correct)
....only when its randomly chosen clusters happen to closely match the underlying structure of the problem. Because of the rarity of such a fortuitous occurrence, the benefit of the crossover operation is greatly diminished. As as result, GAs have a checkered history in function optimization (Baum, Boneh and Garrett, 1995; Lang, 1995) One of our goals is to incorporate insights from GAs in a principled optimization framework. There have been other attempts to capture the advantages of GAs. Population Based Incremental Learning (PBIL) attempts to incorporate the notion of a candidate population by replacing it ....
Baum, E. B., Boneh, D., and Garrett, C. (1995). Where genetic algorithms excel. In Proceedings of the Conference on Computational Learning Theory, New York. Association for Computing Machinery.
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Baum, E.B., Boneh, D., Garrett, C.: Where genetic algorithms excel. In: Proceedings COLT 1995, Santa Cruz, California (1995)
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Eric B. Baum, Dan Boneh, and Charles Garrett. Where Genetic Algorithms Excel. In Proceedings COLT 1995, pp. 230--239, Santa Cruz, California. http://crypto.stanford.edu/~dabo/abstracts/ga.html
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Baum, E., Boneh, D., Garrett, C.: Where genetic algorithms excel. Evolutionary Computation 9 (2001) 93--124
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