Result 1 to 19 of 19 total
Unsupervised linkage learner based on local optimums. (English)
Carrasco-Ochoa, Jesús Ariel (ed.) et al., Pattern recognition. 4th Mexican conference, MCPR 2012, Huatulco, Mexico, June 27‒30, 2012. Proceedings. Berlin: Springer (ISBN 978-3-642-31148-2/pbk). Lecture Notes in Computer Science 7329, 255-264 (2012).
1
Remote sensing image segmentation by active queries. (English)
Pattern Recognition 45, No. 6, 2180-2192 (2012).
2
Efficient model building in competent genetic algorithms using DSM clustering. (English)
AI Commun. 24, No. 3, 213-231 (2011).
3
Almost tight upper bound for finding Fourier coefficients of bounded pseudo-Boolean functions. (English)
J. Comput. Syst. Sci. 77, No. 6, 1039-1053 (2011).
4
Linkage learning based on local optima. (English)
Jędrzejowicz, Piotr (ed.) et al., Computational collective intelligence. Technologies and applications. Third international conference, ICCCI 2011, Gdynia, Poland, September 21‒23, 2011. Proceedings, Part I. Berlin: Springer (ISBN 978-3-642-23934-2/pbk). Lecture Notes in Computer Science 6922. Lecture Notes in Artificial Intelligence, 163-172 (2011).
5
An innovative linkage learning based on differences in local optimums. (English)
Herrero, Álvaro (ed.) et al., Computational intelligence in security for information systems. 4th international conference, CISIS 2011, held at IWANN 2011, Torremolinos-Málaga, Spain, June 8‒10, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-21322-9/pbk). Lecture Notes in Computer Science 6694, 285-292 (2011).
6
Linkage sensitive particle swarm optimization. (English)
Panigrahi, Bijaya Ketan (ed.) et al., Handbook of swarm intelligence. Concepts, principles and applications. Berlin: Springer (ISBN 978-3-642-17389-9/hbk; 978-3-642-17390-5/ebook). Adaptation, Learning, and Optimization 8, 119-132 (2011).
7
Conquering the needle-in-a-haystack: how correlated input variables beneficially alter the fitness landscape for neural networks. (English)
Pizzuti, Clara (ed.) et al., Evolutionary computation, machine learning and data mining in bioinformatics. 7th European conference, EvoBIO 2009, Tübingen, Germany, April 15‒17, 2009. Proceedings. Berlin: Springer (ISBN 978-3-642-01183-2/pbk). Lecture Notes in Computer Science 5483, 80-91 (2009).
8
Set representation and multi-parent learning within an evolutionary algorithm for optimal design of trusses. (English)
Chen, Ying-ping (ed.) et al., Linkage in evolutionary computation. Berlin: Springer (ISBN 978-3-540-85067-0/hbk). Studies in Computational Intelligence 157, 419-439 (2008).
9
Computational intelligence paradigms. Innovative applications. (English)
Studies in Computational Intelligence 137. Berlin: Springer (ISBN 978-3-540-79473-8/hbk; 978-3-540-79474-5/ebook). viii, 281~p. EUR~106.95 (2008).
10
Linkage learning via probabilistic modeling in the extended compact genetic algorithm (ECGA). (English)
Pelikan, Martin (ed.) et al., Scalable optimization via probabilistic modeling. From algorithms to applications. Berlin: Springer (ISBN 3-540-34953-7/hbk). Studies in Computational Intelligence 33, 39-61 (2006).
11
Extending the scalability of linkage learning genetic algorithms. Theory \& practice. (English)
Studies in Fuzziness and Soft Computing 190. Berlin: Springer (ISBN 3-540-28459-1/hbk). xix, 120~p. EUR~89.95/net; sFr~152.00; \sterling~69.00; \$~119.00 (2006).
12
On the inference of semi-coherent structures from data. (English)
Comput. Oper. Res. 32, No. 11, 2853-2874 (2005).
13
Incorporating linkage learning into the GeLog framework. (English)
Acta Cybern. 16, No. 2, 209-228 (2003).
14
Getting the best of both worlds: Discrete and continuous genetic and evolutionary algorithms in concert. (English)
Inf. Sci. 156, No. 3-4, 147-171 (2003).
15
Estimating episodes of care using linked medical claims data. (English)
McKay, Bob (ed.) et al., AI 2002: Advances in artificial intelligence. 15th Australian joint conference on artificial intelligence, Canberra, Australia, December 2-6, 2002. Proceedings. Berlin: Springer. Lect. Notes Comput. Sci. 2557, 660-671 (2002).
16
Distributed, collaborative data analysis from heterogeneous sites using a scalable evolutionary technique. (English)
Appl. Intell. 16, No. 1, 19-42 (2002).
17
Adaptive retrieval agents: Internalizing local context and scaling up to the web. (English)
Mach. Learn. 39, No.2-3, 203-242 (2000).
18
The complexity of vision. (English)
Signal Process. 74, No.1, 101-126 (1999).
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Result 1 to 19 of 19 total
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