-
2
-
-
0001160588
-
What size net gives valid generalization?
-
Baum, E.B. & Haussler, D. (1989) What size net gives valid generalization? Neural Computation, 1, pp. 151-160.
-
(1989)
Neural Computation
, vol.1
, pp. 151-160
-
-
Baum, E.B.1
Haussler, D.2
-
3
-
-
0003979410
-
What size neural network gives optimal generalization? Convergence properties of backpropagation
-
Institute for Advanced Computer Studies, Univ, of Maryland
-
Lawrence, S., Giles, C. L., & Tsoi, A. C. (1996). What Size Neural Network Gives Optimal Generalization ? Convergence Properties of Backpropagation. In Technical Report UMIACS-TR-96-22 and CS-TR-3617, Institute for Advanced Computer Studies, Univ, of Maryland.
-
(1996)
Technical Report
, vol.UMIACS-TR-96-22 AND CS-TR-3617
-
-
Lawrence, S.1
Giles, C.L.2
Tsoi, A.C.3
-
4
-
-
84898932856
-
Overfitting in neural networks: Backpropagation, conjugate gradient, and early stopping
-
Leen, T. K., Dietterich, T. G. & Tresp, V. editors, MIT Press
-
Caruana, R., Lawrence, S., & Giles, C.L. (2001). Overfitting in Neural Networks: Backpropagation, Conjugate Gradient, and Early Stopping. In Leen, T. K., Dietterich, T. G. & Tresp, V. editors, Advances in Neural Information Processing Systems, MIT Press, 13, pp. 402-408.
-
(2001)
Advances in Neural Information Processing Systems
, vol.13
, pp. 402-408
-
-
Caruana, R.1
Lawrence, S.2
Giles, C.L.3
-
5
-
-
0000029122
-
A simple weight decay can improve generalization
-
J.E. Moody, S. J. Hanson, & R. P. Lippmann editors, San Mateo, CA
-
Krogh, A. & Hertz,J.A. (1992) A simple weight decay can improve generalization. In J.E. Moody, S. J. Hanson, & R. P. Lippmann editors, Advances in Neural Information Processing Systems Morgan Kaufmann, San Mateo, CA, 4, pp. 950 957.
-
(1992)
Advances in Neural Information Processing Systems Morgan Kaufmann
, vol.4
, pp. 950957
-
-
Krogh, A.1
Hertz, J.A.2
-
6
-
-
0032099978
-
Automatic early stopping using cross validation: Quantifying the criteria
-
Prechelt, L. (1998). Automatic Early Stopping Using Cross Validation: Quantifying the Criteria. Neural Networks, 11, pp.761-767.
-
(1998)
Neural Networks
, vol.11
, pp. 761-767
-
-
Prechelt, L.1
-
7
-
-
0035654279
-
Feedforward neural network construction using cross-validation
-
Setiono,R. (2001) Feedforward neural network construction using cross-validation, Neural Computation, 13, pp. 2865-2877.
-
(2001)
Neural Computation
, vol.13
, pp. 2865-2877
-
-
Setiono, R.1
-
8
-
-
84898957627
-
For valid generalization the size of the weights is more important than the size of the network
-
M.C, Mozer, M. I. Jordan, & T. Petsche, editors, MIT Press
-
Bartlett,P.L. (1997). For valid generalization the size of the weights is more important than the size of the network. In M.C, Mozer, M. I. Jordan, & T. Petsche, editors, Advances in Neural Information Processing Systems, MIT Press, 9, pp. 134-140.
-
(1997)
Advances in Neural Information Processing Systems
, vol.9
, pp. 134-140
-
-
Bartlett, P.L.1
-
10
-
-
33646505428
-
Generalization ability of Boolean functions implemented in feedforward neural networks
-
In Press
-
Franco, L. Generalization ability of Boolean functions implemented in feedforward neural networks. Neurocomputing. (2006), In Press.
-
(2006)
Neurocomputing
-
-
Franco, L.1
-
11
-
-
33646527957
-
The influence of oppositely classified examples on the generalization complexity of Boolean functions
-
In Press
-
Franco, L. and Anthony, M. The influence of oppositely classified examples on the generalization complexity of Boolean functions, IEEE Transactions on Neural Networks. (2006), In Press.
-
(2006)
IEEE Transactions on Neural Networks
-
-
Franco, L.1
Anthony, M.2
-
13
-
-
0026367608
-
Depth-size tradeoff's for neural computation
-
Siu, K.Y., Roychowdhury, V.P., & Kailath, T. (1991) Depth-Size Tradeoff's for Neural Computation IEEE Transactions on Computers, 40, pp. 1402-1412.
-
(1991)
IEEE Transactions on Computers
, vol.40
, pp. 1402-1412
-
-
Siu, K.Y.1
Roychowdhury, V.P.2
Kailath, T.3
-
14
-
-
0346846404
-
Non glassy ground-state in a long-range antiferromagnetic frustrated model in the hypercubic cell
-
Franco, L. & Cannas, S.A. (2004), Non glassy ground-state in a long-range antiferromagnetic frustrated model in the hypercubic cell Physica A, 382, pp. 337-348.
-
(2004)
Physica A
, vol.382
, pp. 337-348
-
-
Franco, L.1
Cannas, S.A.2
-
15
-
-
0034293035
-
Generalization and selection of examples in feedforward neural networks
-
Franco, L. & Cannas, S.A. (2000). Generalization and Selection of Examples in Feedforward Neural Networks. Neural Computation, 12, 10, pp. 2405-2426.
-
(2000)
Neural Computation
, vol.12
, Issue.10
, pp. 2405-2426
-
-
Franco, L.1
Cannas, S.A.2
-
16
-
-
0035505551
-
Generalization properties of modular networks: Implementing the parity function
-
Franco, L. & Cannas, S.A. (2001). Generalization Properties of Modular Networks: Implementing the Parity Function, IEEE Transactions on Neural Networks, 12, pp. 1306-1313.
-
(2001)
IEEE Transactions on Neural Networks
, vol.12
, pp. 1306-1313
-
-
Franco, L.1
Cannas, S.A.2
-
17
-
-
0038313118
-
Strong association rules mining for large-scale gene-expression data analysis: A case study on human SAGE data
-
Becquet, C. & Blachon, S. & Jeudy, B. & Boulicaut, J.F. & Gandrillon, O. (2002). Strong association rules mining for large-scale gene-expression data analysis: A case study on human SAGE data. Genome Biology, 3, pp. 1-16.
-
(2002)
Genome Biology
, vol.3
, pp. 1-16
-
-
Becquet, C.1
Blachon, S.2
Jeudy, B.3
Boulicaut, J.F.4
Gandrillon, O.5
-
18
-
-
0037245822
-
Mining gene expressions databases for association rules
-
Creighton, C. & Hanash, S. (2003). Mining gene expressions databases for association rules, Bioinformatics, 19, pp. 79-86.
-
(2003)
Bioinformatics
, vol.19
, pp. 79-86
-
-
Creighton, C.1
Hanash, S.2
-
21
-
-
25144436369
-
Role of function complexity and network size in the generalization ability of feedforward networks
-
Franco, L. & Jerez, J.M. & Bravo. J.M (2005). Role of function complexity and network size in the generalization ability of feedforward networks. LNCS, 3512, pp. 1-8.
-
(2005)
LNCS
, vol.3512
, pp. 1-8
-
-
Franco, L.1
Jerez, J.M.2
Bravo, J.M.3
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