to appear |
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7 | Benoît Frénay, Mark van Heeswijk, Yoan Miche, Michel Verleysen, and Amaury Lendasse. Feature selection for nonlinear models using extreme learning machines. Neurocomputing, to appear. accepted for presentation at International Symposium on Extreme Learning Machines. |
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6 | Qi Yu, Emil Eirola, Mark van Heeswijk, Eric Séverin, and Amaury Lendasse. Regularized extreme learning machine for regression with missing data. Neurocomputing, to appear. accepted for presentation at International Symposium on Extreme Learning Machines. |
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2011 |
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5 | Mark van Heeswijk, Yoan Miche, Erkki Oja, and Amaury Lendasse. GPU-accelerated and parallelized ELM ensembles for large-scale regression. Neurocomputing, 74(16):2430–2437, September 2011. |
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4 | Yoan Miche, Mark van Heeswijk, Patrick Bas, Olli Simula, and Amaury Lendasse. TROP-ELM: a double-regularized ELM using LARS and tikhonov regularization. Neurocomputing, 74(16):2413–2421, September 2011. |
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3 | Alberto Guillén, Mark van Heeswijk, DuÅĦan Sovilj, Maribel García Arenas, Luis Javier Herrera, Hector Pomares, and Ignacio Rojas. Variable selection in a GPU cluster using delta test. In IWANN (1), pages 393–400, 2011. |
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2010 |
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2 | Mark van Heeswijk, Yoan Miche, Erkki Oja, and Amaury Lendasse. Solving large regression problems using an ensemble of GPU-accelerated ELMs. In Michel Verleysen, editor, ESANN2010: 18th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pages 309–314, Bruges, Belgium, April 28–30 2010. d-side Publications. |
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2009 |
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1 | Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutila, Peter A.J. Hilbers, Timo Honkela, Erkki Oja, and Amaury Lendasse. Adaptive ensemble models of extreme learning machines for time series prediction. In Cesare Alippi, Marios M. Polycarpou, Christos G. Panayiotou, and Georgios Ellinas, editors, ICANN 2009, Part II, volume 5769 of LNCS, pages 305–314, Heidelberg, 2009. Springer. |
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