INFORMATION PROCESSING USING INTELLIGENT ALGORITHMSBY SOLVING WCCI 2010 TASKS
- Авторлар: Engel EА1, Kovalev IV1, Engel' E.A.1, Kovalev I.V.1
-
Мекемелер:
- Шығарылым: Том 12, № 3 (2011)
- Беттер: 4-8
- Бөлім: Articles
- URL: https://journals.eco-vector.com/2712-8970/article/view/516387
- ID: 516387
Дәйексөз келтіру
Толық мәтін
Аннотация
The article focused on the urgent problem of selection of strategies to deal with ill-structured problems involving
the processing of both quantitative and qualitative data, high dimensionality and omissions in the data.
This article provides a detailed analysis of the prediction models for data processing. Experiments confirm the
effectiveness of intelligent algorithms, developed by the authors.
the processing of both quantitative and qualitative data, high dimensionality and omissions in the data.
This article provides a detailed analysis of the prediction models for data processing. Experiments confirm the
effectiveness of intelligent algorithms, developed by the authors.
Негізгі сөздер
Авторлар туралы
E Engel
I Kovalev
Ekaterina Engel'
Email: ekaterina.en@mail.com
Igor' Kovalev
Email: kovalev.fsu@mail.ru
Әдебиет тізімі
- Caruana R. Multitask learning // Machine Learning. 1997. Vol. 28. № 1. P. 41-75.
- Pan S. J., Yang Q. A survey on transfer learning // IEEE Trans. on Knoweledge and Data Engineering. 2010. Vol. 22. № 10. P. 1345-1359.
- Collobert R., Weston J. A unified architecture for natural language processing: Deep neural networks with multitask learning // Intern. Conf. on Machine Learning (ICML). 2008. Р. 160-167.
- Bengio Y. Learning deep architectures for AI // Foundations and Trends in Machine Learning. 2009. Vol. 2. № 1. P. 1-127.
- Gutstein S. M. Transfer learning techniques for deep neural nets : Ph. D. dissertation. The University of Texas at El Paso, 2010.
- Why does unsupervised pre-training help deep learning? / D. Erhan, Y. Bengio, A. Courville et al. // JMLR. 2010. Vol. 11. P. 625-660.
- Efficient sparse coding algorithms / H. Lee, A. Battle, R. Raina, A. Y. Ng // Advances in Neural Information Processing Systems. 2007. Vol. 19. P. 801-808.
- Self-taught learning: Transfer learning from unlabeled data / R. Raina, A. Battle, H. Lee et al. // Proc. of the Twenty-fourth Intern. Conf. on Machine Learning, 2007. P. 759-766.
- Signature verification using a "siamese" time delay neural network / J. Bromley, I Guyon., Y. LeCun et al. // NIPS. 1993. P. 737-744.
- Learning the kernel matrix with semi-definite programming // G. Lanckriet, N. Cristianini, P. Bartlett, L. E. Ghaoui // J. of Machine Learning Research. 2004. Vol. 5. P. 27-72.
- Weinberger K. Q., Saul L. K. Distance metric learning for large margin nearest neighbor classification // J. Machine Learning Research. 2009. Vol. 10 P. 207-244.
- Yang L., Jin R. Distance metric learning: A comprehensive survey [Electronic resource] : Techn. Rep. Michigan State University. 2006. URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1. 91.4732 (data of visit: 30.07.2011).
- Yang L. An overview of distance metric learning [Electronic resource] : Techn. Rep. Carnegie Mellon University. 2007. URL: http://www.cs.cmu.edu/~liuy/ dist_overview.pdf (data of visit: 30.07.2011).
- Learning to Learn / S. Thrun, L.Y. Pratt (ed.). Boston, MA : Kluwer Academic Publishers, 1998.
- Regularized principal manifolds / A. J. Smola, S. Mika, B. Schlkopf, R. C. Williamson // JMLR. 2001. Vol. 1. P. 179-209.
- Out-of-sample extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering / Y. Bengio, J.-F. Paiement, P. Vincent et al. // NIPS. 2003. P. 177-184.
- Globerson A., Tishby N. Sufficient dimensionality reduction // J. Machine Learning Research. 2003. Vol. 3. P. 1307-1331.
- Ghahramani Z. Unsupervised Learning // Advanced Lectures in Machine Learning. Lecture Notes in Computer Sci. Berlin : Springer-Verlag, 2004. Vol. 3176. P. 72-112.
- Luxburg U. A tutorial on spectral clustering // Statistics and Computing. 2007. Vol. 17. P. 395-416.
- Jain A. K., Murty M. N., Flynn P. J. Data clustering : A review ACM Computing Surveys. 1999. P. 264-323.
- Performance prediction challenge / I. Guyon, A. Saffari, G. Dror, J. Buhmann // IEEE/INNS conf. IJCNN 2006. Vancouver, Canada, July 16-21. 2006. P. 1649-1656.
- Engel E. A. Modified artificial neural network for information processing with the selection of essential connections : Ph. D. thesis. Krasnoyarsk, 2004.
- Engel E. A. Graphic information processing using intelligent algorithms // Vestnik. Sci. J. of Siberian State Aerospace Univ. № 4(25). 2009. Р. 85-90.
- Engel E. A. The hierarchical model of decisionmaking based on fuzzy neural networks for information processing, Vestnik. Sci. J. of Siberian State Aerospace Univ. № 1 (33). 2011. Р. 83-86.