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Items: 1 to 20 of 103

1.

A New Surrogate-Assisted Interactive Genetic Algorithm With Weighted Semisupervised Learning.

Sun X, Gong D, Jin Y, Chen S.

IEEE Trans Cybern. 2013 Apr;43(2):685-98. doi: 10.1109/TSMCB.2012.2214382. Epub 2013 Mar 7.

PMID:
23014759
2.

Evolution by adapting surrogates.

Le MN, Ong YS, Menzel S, Jin Y, Sendhoff B.

Evol Comput. 2013 Summer;21(2):313-40. doi: 10.1162/EVCO_a_00079. Epub 2012 Jun 25.

PMID:
22564044
3.

On Using Surrogates with Genetic Programming.

Hildebrandt T, Branke J.

Evol Comput. 2015 Fall;23(3):343-67. doi: 10.1162/EVCO_a_00133. Epub 2014 Nov 24.

PMID:
24967694
4.

Real-time tumor motion estimation using respiratory surrogate via memory-based learning.

Li R, Lewis JH, Berbeco RI, Xing L.

Phys Med Biol. 2012 Aug 7;57(15):4771-86. doi: 10.1088/0031-9155/57/15/4771. Epub 2012 Jul 6.

5.

Improved semisupervised adaptation for a small training dataset in the brain-computer interface.

Meng J, Sheng X, Zhang D, Zhu X.

IEEE J Biomed Health Inform. 2014 Jul;18(4):1461-72. doi: 10.1109/JBHI.2013.2285232. Epub 2013 Oct 9.

PMID:
24122610
6.

Multi-objective optimization with controlled model assisted evolution strategies.

Braun J, Krettek J, Hoffmann F, Bertram T.

Evol Comput. 2009 Winter;17(4):577-93. doi: 10.1162/evco.2009.17.4.17408.

PMID:
19916780
7.

Interactive evolutionary computation with minimum fitness evaluation requirement and offline algorithm design.

Ishibuchi H, Sudo T, Nojima Y.

Springerplus. 2016 Feb 27;5:192. doi: 10.1186/s40064-016-1789-1. eCollection 2016.

8.

Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach.

Yang J, Singh H, Hines EL, Schlaghecken F, Iliescu DD, Leeson MS, Stocks NG.

Artif Intell Med. 2012 Jun;55(2):117-26. doi: 10.1016/j.artmed.2012.02.001. Epub 2012 Apr 12.

9.

A new evolutionary algorithm for solving many-objective optimization problems.

Zou X, Chen Y, Liu M, Kang L.

IEEE Trans Syst Man Cybern B Cybern. 2008 Oct;38(5):1402-12. doi: 10.1109/TSMCB.2008.926329.

PMID:
18784020
10.

A Hybrid Constructive Algorithm for Single-Layer Feedforward Networks Learning.

Wu X, Rózycki P, Wilamowski BM.

IEEE Trans Neural Netw Learn Syst. 2015 Aug;26(8):1659-68. doi: 10.1109/TNNLS.2014.2350957. Epub 2014 Sep 9.

PMID:
25216485
11.

A multiscale expectation-maximization semisupervised classifier suitable for badly posed image classification.

Baraldi A, Bruzzone L, Blonda P.

IEEE Trans Image Process. 2006 Aug;15(8):2208-25.

PMID:
16900677
12.

Initialization independent clustering with actively self-training method.

Nie F, Xu D, Li X.

IEEE Trans Syst Man Cybern B Cybern. 2012 Feb;42(1):17-27. doi: 10.1109/TSMCB.2011.2161607. Epub 2011 Nov 11.

PMID:
22086542
13.

Bregman divergences and surrogates for learning.

Nock R, Nielsen F.

IEEE Trans Pattern Anal Mach Intell. 2009 Nov;31(11):2048-59. doi: 10.1109/TPAMI.2008.225.

PMID:
19762930
14.

Overtaking method based on sand-sifter mechanism: Why do optimistic value functions find optimal solutions in multi-armed bandit problems?

Ochi K, Kamiura M.

Biosystems. 2015 Sep;135:55-65. doi: 10.1016/j.biosystems.2015.06.009. Epub 2015 Jul 10.

15.

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection.

Park SH, Gao Y, Shi Y, Shen D.

Med Phys. 2014 Nov;41(11):111715. doi: 10.1118/1.4898200.

16.

An Orthogonal Evolutionary Algorithm With Learning Automata for Multiobjective Optimization.

Dai C, Wang Y, Ye M, Xue X, Liu H.

IEEE Trans Cybern. 2015 Dec 17. [Epub ahead of print]

PMID:
26685277
17.

An ordered-subsets proximal preconditioned gradient algorithm for edge-preserving PET image reconstruction.

Mehranian A, Rahmim A, Ay MR, Kotasidis F, Zaidi H.

Med Phys. 2013 May;40(5):052503. doi: 10.1118/1.4801898.

PMID:
23635293
18.

Combined unsupervised-supervised classification of multiparametric PET/MRI data: application to prostate cancer.

Gatidis S, Scharpf M, Martirosian P, Bezrukov I, Küstner T, Hennenlotter J, Kruck S, Kaufmann S, Schraml C, la Fougère C, Schwenzer NF, Schmidt H.

NMR Biomed. 2015 Jul;28(7):914-22. doi: 10.1002/nbm.3329. Epub 2015 May 26.

PMID:
26014883
19.

Interactively optimizing signal-to-noise ratios in expression profiling: project-specific algorithm selection and detection p-value weighting in Affymetrix microarrays.

Seo J, Bakay M, Chen YW, Hilmer S, Shneiderman B, Hoffman EP.

Bioinformatics. 2004 Nov 1;20(16):2534-44. Epub 2004 Apr 29.

20.

An evolutionary approach for image segmentation.

Amelio A, Pizzuti C.

Evol Comput. 2014 Winter;22(4):525-57. doi: 10.1162/EVCO_a_00115.

PMID:
24256513
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