Result 1 to 20 of 33 total
Time-dependent series variance estimation via recurrent neural networks. (English)
Honkela, Timo (ed.) et al., Artificial neural networks and machine learning ‒ ICANN 2011. 21st international conference on artificial neural networks, Espoo, Finland, June 14‒17, 2011. Proceedings, Part I. Berlin: Springer (ISBN 978-3-642-21734-0/pbk). Lecture Notes in Computer Science 6791, 176-184 (2011).
1
Time-dependent series variance estimation via recurrent neural networks (English)
ICANN (1), 176-184 (2011).
2
Single-stacking conformity approach to reliable classification. (English)
Dicheva, Darina (ed.) et al., Artificial intelligence: methodology, systems, and applications. 14th international conference, AIMSA 2010, Varna, Bulgaria, September 8‒10. 2010. Proceedings. Berlin: Springer (ISBN 978-3-642-15430-0/pbk). Lecture Notes in Computer Science 6304. Lecture Notes in Artificial Intelligence, 161-170 (2010).
3
$k$-version-space multi-class classification based on $k$-consistency tests. (English)
Balcázar, José Luis (ed.) et al., Machine learning and knowledge discovery in databases. European conference, ECML PKDD 2010, Barcelona, Spain, September 20‒24, 2010. Proceedings, Part III. Berlin: Springer (ISBN 978-3-642-15938-1/pbk). Lecture Notes in Computer Science 6323. Lecture Notes in Artificial Intelligence, 277-292 (2010).
4
Efficient online recurrent connectionist learning with the ensemble Kalman filter. (English)
Neurocomputing 73, No. 4-6, 1024-1030 (2010).
5
Recursive Bayesian recurrent neural networks for time-series modeling (English)
IEEE Transactions on Neural Networks 21, No. 2, 262-274 (2010).
6
$k$-version-space multi-class classification based on $k$-consistency tests (English)
ECML/PKDD (3), 277-292 (2010).
7
Unscented grid filtering and elman recurrent networks (English)
IJCNN, 1-7 (2010).
8
Single-stacking conformity approach to reliable classification (English)
AIMSA, 161-170 (2010).
9
Recurrent expectation maximization neural modeling (English)
CIMCA/IAWTIC/ISE, 674-679 (2008).
10
Dynamic modeling with ensemble Kalman filter trained recurrent neural networks (English)
ICMLA, 843-848 (2008).
11
Output control of some nonlinear system with unknown parameters and nonlinearity. (English)
Autom. Remote Control 68, No. 6, 1069-1074 (2007); translation from Avtom. Telemekh. 2007, No. 6, 150-156 (2007).
12
A one-step unscented particle filter for nonlinear dynamical systems (English)
ICANN (1), 747-756 (2007).
13
Recursive Bayesian levenberg-marquardt training of recurrent neural networks (English)
IJCNN, 282-287 (2007).
14
Adaptive learning of polynomial networks. Genetic programming, backpropagation and Bayesian methods. (English)
Genetic and Evolutionary Computation. New York, NY: Springer (ISBN 0-387-31239-0/hbk). xiv, 316~p. EUR~67.36 (2006).
15
Generalizing version space support vector machines for non-separable data (English)
ICDM Workshops, 744-748 (2006).
16
Polynomial harmonic GMDH learning networks for time series modeling. (English)
Neural Netw. 16, No. 10, 1527-1540 (2003).
17
Learning polynomial feedforward neural networks by genetic programming and backpropagation (English)
IEEE Transactions on Neural Networks 14, No. 2, 337-350 (2003).
18
Genetic programming of polynomial harmonic networks using the discrete Fourier transform. (English)
Int. J. Neural Syst. 12, No. 5, 399-410 (2002).
19
Regularization approach to inductive genetic programming. (English)
IEEE Trans. Evol. Comput. 5, No. 4, 359-375 (2001).
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Result 1 to 20 of 33 total
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