-
1
-
-
33745903481
-
Extreme learning machine: Theory and applications
-
Huang, G.B., Zhu, Q.Y., Siew, C.K.: Extreme learning machine: Theory and applications. Neurocomputing 70(1-3), 489-501 (2006)
-
(2006)
Neurocomputing
, vol.70
, Issue.1-3
, pp. 489-501
-
-
Huang, G.B.1
Zhu, Q.Y.2
Siew, C.K.3
-
3
-
-
84887010852
-
A methodology for building regression models using extreme learning machine: Op-elm
-
ESANN, Bruges, Belgium, April 23-25 (2008)
-
Miche, Y., Bas, P., Jutten, C., Simula, O., Lendasse, A.: A methodology for building regression models using extreme learning machine: OP-ELM. In: European Symposium on Artificial Neural Networks, ESANN 2008, Bruges, Belgium, April 23-25 (2008)
-
(2008)
European Symposium on Artificial Neural Networks
-
-
Miche, Y.1
Bas, P.2
Jutten, C.3
Simula, O.4
Lendasse, A.5
-
4
-
-
73949154686
-
OP-elm: Optimallypruned extreme learning machine
-
Miche, Y., Sorjamaa, A., Bas, P., Simula, O., Jutten, C., Lendasse, A.: OP-ELM: Optimallypruned extreme learning machine. IEEE Transactions on Neural Networks 21(1), 158-162 (2010)
-
(2010)
IEEE Transactions on Neural Networks
, vol.21
, Issue.1
, pp. 158-162
-
-
Miche, Y.1
Sorjamaa, A.2
Bas, P.3
Simula, O.4
Jutten, C.5
Lendasse, A.6
-
5
-
-
58849132454
-
-
In: K°urková, V., Neruda, R., Koutník, J. (eds.) ICANN 2008, Part I. LNCS. Springer, Heidelberg
-
Miche, Y., Sorjamaa, A., Lendasse, A.: OP-ELM: Theory, experiments and a toolbox. In: K°urková, V., Neruda, R., Koutník, J. (eds.) ICANN 2008, Part I. LNCS, vol. 5163, pp. 145-154. Springer, Heidelberg (2008)
-
(2008)
OP-ELM: Theory, Experiments and A Toolbox
, vol.5163
, pp. 145-154
-
-
Miche, Y.1
Sorjamaa, A.2
Lendasse, A.3
-
7
-
-
0016029778
-
The relationship between variable selection and data agumentation and a method for prediction
-
Allen, D.M.: The relationship between variable selection and data agumentation and a method for prediction. Technometrics 16(1), 125-127 (1974)
-
(1974)
Technometrics
, vol.16
, Issue.1
, pp. 125-127
-
-
Allen, D.M.1
-
8
-
-
3242708140
-
Least angle regression
-
Efron, B., Hastie, T., Johnstone, I., Tibshirani, R.: Least angle regression. Annals of Statistics 32, 407-499 (2004)
-
(2004)
Annals of Statistics
, vol.32
, pp. 407-499
-
-
Efron, B.1
Hastie, T.2
Johnstone, I.3
Tibshirani, R.4
-
9
-
-
32044449925
-
Generalized cross-validation as a method for choosing a good ridge parameter
-
Golub, G.H., Heath, M., Wahba, G.: Generalized cross-validation as a method for choosing a good ridge parameter. Technometrics 21(2), 215-223 (1979)
-
(1979)
Technometrics
, vol.21
, Issue.2
, pp. 215-223
-
-
Golub, G.H.1
Heath, M.2
Wahba, G.3
-
10
-
-
0002161961
-
Application of ridge analysis to regression problems
-
Hoerl, A.E.: Application of ridge analysis to regression problems. Chemical Engineering Progress 58, 54-59 (1962)
-
(1962)
Chemical Engineering Progress
, vol.58
, pp. 54-59
-
-
Hoerl, A.E.1
-
12
-
-
33646231022
-
Multiresponse sparse regression with application to multidimensional scaling
-
In: Duch, W., Kacprzyk, J., Oja, E., Zadro?zny, S. Springer, Heidelberg
-
Similä, T., Tikka, J.: Multiresponse sparse regression with application to multidimensional scaling. In: Duch, W., Kacprzyk, J., Oja, E., Zadro?zny, S. (eds.) ICANN 2005. LNCS, vol. 3697, pp. 97-102. Springer, Heidelberg (2005)
-
(2005)
ICANN 2005. LNCS
, vol.3697
, pp. 97-102
-
-
Similä, T.1
Tikka, J.2
-
13
-
-
0006345655
-
-
Technical Report 28, Division of Biostatistics, Stanford University
-
Thisted, R.A.: Ridge regression, minimax estimation, and empirical bayes methods. Technical Report 28, Division of Biostatistics, Stanford University (1976)
-
(1976)
Ridge Regression, Minimax Estimation, and Empirical Bayes Methods
-
-
Thisted, R.A.1
-
14
-
-
0001300994
-
Solution of incorrectly formulated problems and the regularization method
-
Tychonoff, A.N.: Solution of incorrectly formulated problems and the regularization method. Soviet Mathematics 4, 1035-1038 (1963)
-
(1963)
Soviet Mathematics
, vol.4
, pp. 1035-1038
-
-
Tychonoff, A.N.1
-
15
-
-
69949155103
-
Grouped and hierarchical model selection through composite absolute penalties
-
Zhao, P., Rocha, G.V., Yu, B.: Grouped and hierarchical model selection through composite absolute penalties. Annals of Statistics 37(6A), 3468-3497 (2009)
-
(2009)
Annals of Statistics
, vol.37
, Issue.6 A
, pp. 3468-3497
-
-
Zhao, P.1
Rocha, G.V.2
Yu, B.3
-
17
-
-
80051671932
-
Trop-elm: A doubleregularized elm using lars and tikhonov regularization
-
Miche, Y., van Heeswijk, M., Bas, P., Simula, O., Lendasse, A.: Trop-elm: A doubleregularized elm using lars and tikhonov regularization. Neurocomputing 74(16), 2413-2421 (2011)
-
(2011)
Neurocomputing
, vol.74
, Issue.16
, pp. 2413-2421
-
-
Miche, Y.1
Van Heeswijk, M.2
Bas, P.3
Simula, O.4
Lendasse, A.5
-
18
-
-
84880055177
-
Ensemble modeling with a constrained linear system of leave-one-out outputs
-
In: Verleysen, M. (ed April 28-30, d-side Publications, Bruges
-
Miche, Y., Eirola, E., Bas, P., Simula, O., Jutten, C., Lendasse, A., Verleysen, M.: Ensemble modeling with a constrained linear system of leave-one-out outputs. In: Verleysen, M. (ed.) ESANN 2010: 18th European Symposium on Artificial Neural Networks, Computational Intelligence andMachine Learning, April 28-30, pp. 19-24. d-side Publications, Bruges (2010)
-
(2010)
ESANN 2010: 18th European Symposium on Artificial Neural Networks, Computational Intelligence AndMachine Learning
, pp. 19-19
-
-
Miche, Y.1
Eirola, E.2
Bas, P.3
Simula, O.4
Jutten, C.5
Lendasse, A.6
Verleysen, M.7
-
19
-
-
80051584618
-
GPU-accelerated and parallelized elm ensembles for large-scale regression
-
van Heeswijk, M., Miche, Y., Oja, E., Lendasse, A.: GPU-accelerated and parallelized ELM ensembles for large-scale regression. Neurocomputing 74(16), 2430-2437 (2011)
-
(2011)
Neurocomputing
, vol.74
, Issue.16
, pp. 2430-2437
-
-
Van Heeswijk, M.1
Miche, Y.2
Oja, E.3
Lendasse, A.4
-
20
-
-
0036567392
-
Ensembling neural networks: Many could be better than all
-
Hua Zhou, Z.,Wu, J., Tang, W.: Ensembling neural networks: Many could be better than all. Artif. Intell. 137(1-2), 239-263 (2002)
-
(2002)
Artif. Intell.
, vol.137
, Issue.1-2
, pp. 239-263
-
-
Hua Zhou, Z.1
Wu, J.2
Tang, W.3
-
22
-
-
33745918399
-
Universal approximation using incremental constructive feedforward networks with random hidden nodes
-
Huang, G.B., Chen, L., Siew, C.K.: Universal approximation using incremental constructive feedforward networks with random hidden nodes. IEEE Transactions on Neural Networks 17, 879-892 (2005)
-
(2005)
IEEE Transactions on Neural Networks
, vol.17
, pp. 879-892
-
-
Huang, G.B.1
Chen, L.2
Siew, C.K.3
-
23
-
-
56549090053
-
Enhanced random search based incremental extreme learning machine
-
Huang, G.B., Chen, L.: Enhanced random search based incremental extreme learning machine. Neurocomputing 71(16-18), 3460-3468 (2008)
-
(2008)
Neurocomputing
, vol.71
, Issue.16-18
, pp. 3460-3468
-
-
Huang, G.B.1
Chen, L.2
-
24
-
-
34548158996
-
Convex incremental extreme learning machine
-
Huang, G.B., Chen, L.: Convex incremental extreme learning machine. Neurocomputing 70(16-18), 3056-3062 (2007)
-
(2007)
Neurocomputing
, vol.70
, Issue.16-18
, pp. 3056-3062
-
-
Huang, G.B.1
Chen, L.2
-
25
-
-
33645007988
-
Can threshold networks be trained directly
-
Huang, G.B., Zhu, Q.Y., Mao, K., Siew, C.K., Saratchandran, P., Sundararajan, N.: Can threshold networks be trained directly? IEEE Transactions on Circuits and Systems II: Express Briefs 53(3), 187-191 (2006)
-
(2006)
IEEE Transactions on Circuits and Systems II: Express Briefs
, vol.53
, Issue.3
, pp. 187-191
-
-
Huang, G.B.1
Zhu, Q.Y.2
Mao, K.3
Siew, C.K.4
Saratchandran, P.5
Sundararajan, N.6
-
26
-
-
22844451535
-
Fully complex extreme learning machine
-
Li,M.B., Huang, G.B., Saratchandran, P., Sundararajan, N.: Fully complex extreme learning machine. Neurocomputing 68, 306-314 (2005)
-
(2005)
Neurocomputing
, vol.68
, pp. 306-314
-
-
Li, M.B.1
Huang, G.B.2
Saratchandran, P.3
Sundararajan, N.4
-
29
-
-
79958181023
-
Random search enhancement of error minimized extreme learning machine
-
In: Verleysen, M. (ed., April 28-30. d-side Publications, Bruges
-
Yuan, L., Chai, S.Y., Huang, G.B.: Random search enhancement of error minimized extreme learning machine. In: Verleysen, M. (ed.) European Symposium on Artificial Neural Networks, ESANN 2010, April 28-30, pp. 327-332. d-side Publications, Bruges (2010)
-
(2010)
European Symposium on Artificial Neural Networks, ESANN 2010
, pp. 327-332
-
-
Yuan, L.1
Chai, S.Y.2
Huang, G.B.3
-
30
-
-
68949200808
-
Error minimized extreme learning machine with growth of hidden nodes and incremental learning
-
Feng, G., Huang, G.B., Lin, Q., Gay, R.: Error minimized extreme learning machine with growth of hidden nodes and incremental learning. IEEE Transactions on Neural Networks 20(8), 1352-1357 (2009)
-
(2009)
IEEE Transactions on Neural Networks
, vol.20
, Issue.8
, pp. 1352-1357
-
-
Feng, G.1
Huang, G.B.2
Lin, Q.3
Gay, R.4
-
31
-
-
84906951414
-
-
Group E
-
Group, E.: The op-elm toolbox (2009), http://www.cis.hut.fi/projects/ eiml/research/downloads/op-elm-toolbox
-
(2009)
The Op-elm Toolbox
-
-
-
32
-
-
0016963035
-
Minimax estimation of a multivariate normal mean under arbitrary quadratic loss
-
Berger, J.: Minimax estimation of a multivariate normal mean under arbitrary quadratic loss. Journal of Multivariate Analysis 6(2), 256-264 (1976)
-
(1976)
Journal of Multivariate Analysis
, vol.6
, Issue.2
, pp. 256-264
-
-
Berger, J.1
-
33
-
-
0003684449
-
-
Inference, and Prediction, 2nd edn. Springer
-
Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd edn. Springer (2009)
-
(2009)
The Elements of Statistical Learning: Data Mining
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.3
-
34
-
-
67650463106
-
Regularized extreme learning machine
-
March 30-April
-
Deng,W., Zheng, Q., Chen, L.: Regularized extreme learning machine. In: IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009, March 30-April 2, pp. 389-395 (2009)
-
(2009)
IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009
, vol.2
, pp. 389-395
-
-
Deng, W.1
Zheng, Q.2
Chen, L.3
-
35
-
-
0000238336
-
A simplex method for function minimization
-
Nelder, J.A., Mead, R.: A simplex method for function minimization. The Computer Journal 7(4), 308-313 (1965)
-
(1965)
The Computer Journal
, vol.7
, Issue.4
, pp. 308-313
-
-
Nelder, J.A.1
Mead, R.2
-
36
-
-
21144438694
-
Model selection with cross-validations and bootstraps-application to time series prediction with RBFN models
-
In: Kaynak, O., Alpaydin, E., Oja, E., Xu, L. (eds. Springer, Heidelberg
-
Lendasse, A., Wertz, V., Verleysen, M.: Model selection with cross-validations and bootstraps-application to time series prediction with RBFN models. In: Kaynak, O., Alpaydin, E., Oja, E., Xu, L. (eds.) ICANN/ICONIP 2003. LNCS, vol. 2714, pp. 573-580. Springer, Heidelberg (2003)
-
(2003)
ICANN/ICONIP 2003. LNCS
, vol.2714
, pp. 573-580
-
-
Lendasse, A.1
Wertz, V.2
Verleysen, M.3
|