-
1
-
-
84945797434
-
Dynamic node creation in backpropagation networks
-
T. Ash Dynamic node creation in backpropagation networks Connect. Sci. 1 4 1989 365-375
-
(1989)
Connect. Sci.
, vol.1
, Issue.4
, pp. 365-375
-
-
Ash, T.1
-
3
-
-
0001160588
-
What size net gives valid generalization?
-
E.B. Baum D. Haussler What size net gives valid generalization? Neural Comput. 1 1 1989 151-160
-
(1989)
Neural Comput.
, vol.1
, Issue.1
, pp. 151-160
-
-
Baum, E.B.1
Haussler, D.2
-
4
-
-
0026453958
-
Training a 3-node neural network is NP-complete
-
A. Blum R.L. Rivest Training a 3-node neural network is NP-complete Neural Networks 5 1 1992 117-128
-
(1992)
Neural Networks
, vol.5
, Issue.1
, pp. 117-128
-
-
Blum, A.1
Rivest, R.L.2
-
5
-
-
0003578240
-
An empirical study of learning speed in backpropagation networks
-
Technical Report, CMU-CS-88-162, Carnegie-Mellon University
-
S.E. Fahlman, An empirical study of learning speed in backpropagation networks, Technical Report, CMU-CS-88-162, Carnegie-Mellon University, 1988.
-
(1988)
-
-
Fahlman, S.E.1
-
6
-
-
0000155950
-
The cascade-correlation learning architecture
-
D.S. Touretzky (Ed.) Morgan Kaufmann Publishers CA
-
S.E. Fahlman C. Lebiere The cascade-correlation learning architecture in: D.S. Touretzky (Ed.) Advances in Neural Information Processing Systems vol. 2 1990 Morgan Kaufmann Publishers CA 524-532
-
(1990)
Advances in Neural Information Processing Systems
, vol.2
, pp. 524-532
-
-
Fahlman, S.E.1
Lebiere, C.2
-
7
-
-
0035576171
-
Incremental learning with respect to new incoming input attributes
-
S.-U. Guan S. Li Incremental learning with respect to new incoming input attributes Neural Process. Lett. 14 3 2001 241-260
-
(2001)
Neural Process. Lett.
, vol.14
, Issue.3
, pp. 241-260
-
-
Guan, S.-U.1
Li, S.2
-
8
-
-
3242774399
-
Incremental learning in terms of output attributes
-
S.-U. Guan P. Li Incremental learning in terms of output attributes J Intell. Systems 13 2 2004 95-122
-
(2004)
J. Intell. Systems
, vol.13
, Issue.2
, pp. 95-122
-
-
Guan, S.-U.1
Li, P.2
-
9
-
-
0742321252
-
Incremental ordered neural network training
-
S.-U. Guan J. Liu Incremental ordered neural network training J. Intell. Systems 12 3 2002 137-172
-
(2002)
J. Intell. Systems
, vol.12
, Issue.3
, pp. 137-172
-
-
Guan, S.-U.1
Liu, J.2
-
10
-
-
2442628430
-
Incremental neural network training with an increasing input dimension
-
S.-U. Guan J. Liu Incremental neural network training with an increasing input dimension J Intell. Systems 13 1 2004 45-70
-
(2004)
J Intell. Systems
, vol.13
, Issue.1
, pp. 45-70
-
-
Guan, S.-U.1
Liu, J.2
-
11
-
-
0001940458
-
Adaptive mixtures of local experts
-
R.A. Jacobs M.I. Jordan et al. Adaptive mixtures of local experts Neural Comput. 3 1 1991 79-87
-
(1991)
Neural Comput.
, vol.3
, Issue.1
, pp. 79-87
-
-
Jacobs, R.A.1
Jordan, M.I.2
-
12
-
-
0031236099
-
Objective functions for training new hidden units in constructive neural networks
-
T.Y. Kwok D.Y. Yeung Objective functions for training new hidden units in constructive neural networks IEEE Trans. Neural Networks 8 5 1997 1131-1148
-
(1997)
IEEE Trans. Neural Networks
, vol.8
, Issue.5
, pp. 1131-1148
-
-
Kwok, T.Y.1
Yeung, D.Y.2
-
13
-
-
33645589873
-
Bayesian approach for neural networks
-
April
-
J. Lampinen, A. Vehtari, Bayesian approach for neural networks, Neural Networks April (2001) 7-24
-
(2001)
Neural Networks
, pp. 7-24
-
-
Lampinen, J.1
Vehtari, A.2
-
14
-
-
0032795250
-
Modelling with constructive backpropagation
-
M. Lehtokangas Modelling with constructive backpropagation Neural Networks 12 1999 707-716
-
(1999)
Neural Networks
, vol.12
, pp. 707-716
-
-
Lehtokangas, M.1
-
15
-
-
0025514862
-
Problem decomposition and subgoaling in artificial neural networks
-
Los Angeles, CA
-
P. Liang, Problem decomposition and subgoaling in artificial neural networks, IEEE International Conference on Systems, Man and Cybernetics, Los Angeles, CA, 1990, pp.178-181.
-
(1990)
IEEE International Conference on Systems, Man and Cybernetics
, pp. 178-181
-
-
Liang, P.1
-
16
-
-
0003748256
-
Bayesian methods for adaptive models
-
Ph.D. Thesis, California Institute of Technology
-
D.J.C. Mackay, Bayesian methods for adaptive models, Ph.D. Thesis, California Institute of Technology, 1991.
-
(1991)
-
-
Mackay, D.J.C.1
-
17
-
-
0002704818
-
A practical bayesian framework for backpropagation
-
D.J.C. Mackay A practical bayesian framework for backpropagation Neural Comput. 4 1992 448-472
-
(1992)
Neural Comput.
, vol.4
, pp. 448-472
-
-
Mackay, D.J.C.1
-
18
-
-
0025056697
-
Regularization algorithms for leaning that are equivalent to multi-layer networks
-
T. Poggio F. Girosi Regularization algorithms for leaning that are equivalent to multi-layer networks Science 247 1990 978-982
-
(1990)
Science
, vol.247
, pp. 978-982
-
-
Poggio, T.1
Girosi, F.2
-
19
-
-
0004042460
-
PROBEN1: A set of neural network benchmark problems and benchmarking rules
-
Technical Report 21/94, Department of Informatics, University of Karlsruhe, Germany
-
L. Prechelt, PROBEN1: A set of neural network benchmark problems and benchmarking rules, Technical Report 21/94, Department of Informatics, University of Karlsruhe, Germany, 1994.
-
(1994)
-
-
Prechelt, L.1
-
20
-
-
0031193357
-
Investigation of the CasCor family of learning algorithms
-
L. Prechelt Investigation of the CasCor family of learning algorithms Neural Networks 10 5 1997 885-896
-
(1997)
Neural Networks
, vol.10
, Issue.5
, pp. 885-896
-
-
Prechelt, L.1
-
21
-
-
0027662338
-
Pruning algorithm - A survey
-
R. Reed Pruning algorithm - a survey IEEE Trans. Neural Networks 4 5 1993 740-747
-
(1993)
IEEE Trans. Neural Networks
, vol.4
, Issue.5
, pp. 740-747
-
-
Reed, R.1
-
23
-
-
0027809638
-
Divide and conquer neural networks
-
S.G. Romaniuk L.O. Hall Divide and conquer neural networks Neural Networks V6 1993 1105-1116
-
(1993)
Neural Networks
, vol.V6
, pp. 1105-1116
-
-
Romaniuk, S.G.1
Hall, L.O.2
-
24
-
-
0000646059
-
Learning internal representations by error propagation
-
D.E. Rumelhart J.L. McClelland (Eds.) MIT Press Cambridge, MA
-
D.E. Rumelhart G. Hinton R. Williams Learning internal representations by error propagation in: D.E. Rumelhart J.L. McClelland (Eds.) Parallel Distributed Processing, Foundations vol. I 1986 MIT Press Cambridge, MA 318-362
-
(1986)
Parallel Distributed Processing, Foundations
, vol.1
, pp. 318-362
-
-
Rumelhart, D.E.1
Hinton, G.2
Williams, R.3
-
25
-
-
0031516467
-
Modularity, combining and artificial neural nets
-
A.J.C. Sharkey Modularity, combining and artificial neural nets Connect. Sci. 9 1 1997 3-10
-
(1997)
Connect. Sci.
, vol.9
, Issue.1
, pp. 3-10
-
-
Sharkey, A.J.C.1
-
27
-
-
2542563695
-
Experimental analysis of aspects of the cascade-correlation learning architecture
-
Machine Learning Research Group Working Paper 91-1, Computer Science Department, University of Wisconsin-Madison
-
C.S. Squires, J.W. Shavlik, Experimental analysis of aspects of the cascade-correlation learning architecture, Machine Learning Research Group Working Paper 91-1, Computer Science Department, University of Wisconsin-Madison, 1991
-
(1991)
-
-
Squires, C.S.1
Shavlik, J.W.2
-
28
-
-
0025593679
-
Supersab: Fast adaptive backpropagation with good scaling properties
-
T. Tollenaere Supersab: Fast adaptive backpropagation with good scaling properties Neural Networks 3 5 1990 561-573
-
(1990)
Neural Networks
, vol.3
, Issue.5
, pp. 561-573
-
-
Tollenaere, T.1
-
29
-
-
0005995498
-
A review of parallel implementations of backpropagation neural networks
-
N. Sundararajan P. Saratchandran (Eds.) IEEE Computer Society Press Los Alamitos, California
-
J. Torresen O. Landsvek A review of parallel implementations of backpropagation neural networks in: N. Sundararajan P. Saratchandran (Eds.) Parallel Architectures for Artificial Neural Networks: Paradigms and Implementations 1998 IEEE Computer Society Press Los Alamitos, California 25-63
-
(1998)
Parallel Architectures for Artificial Neural Networks: Paradigms and Implementations
, pp. 25-63
-
-
Torresen, J.1
Landsvek, O.2
-
30
-
-
0003420912
-
Experiments with cascade-correlation algorithm
-
Technical Report 91-16, Department of Computer Science, Iowa State University
-
J. Yang, V. Honavar, Experiments with cascade-correlation algorithm, Technical Report 91-16, Department of Computer Science, Iowa State University, 1991.
-
(1991)
-
-
Yang, J.1
Honavar, V.2
-
31
-
-
33645608355
-
A neural network approach to constructive induction
-
Proceedings of the Eighth International Workshop on Machine Learning, Evanston, Illinois, USA
-
D.Y. Yeung, A neural network approach to constructive induction, Proceedings of the Eighth International Workshop on Machine Learning, Evanston, Illinois, USA, 1991.
-
(1991)
-
-
Yeung, D.Y.1
|