| OP-ELM: optimally pruned extreme learning machine Y Miche, A Sorjamaa, P Bas, O Simula, C Jutten, A Lendasse IEEE transactions on neural networks 21 (1), 158-162, 2009 | 922 | 2009 |
| Methodology for long-term prediction of time series A Sorjamaa, J Hao, N Reyhani, Y Ji, A Lendasse Neurocomputing 70 (16-18), 2861-2869, 2007 | 563 | 2007 |
| Extreme learning machines [trends & controversies] E Cambria, GB Huang, LLC Kasun, H Zhou, CM Vong, J Lin, J Yin, Z Cai, ... IEEE intelligent systems 28 (6), 30-59, 2013 | 454 | 2013 |
| High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications A Akusok, KM Bjork, Y Miche, A Lendasse Access, IEEE, 2015 | 316 | 2015 |
| Mutual information for the selection of relevant variables in spectrometric nonlinear modelling F Rossi, A Lendasse, D François, V Wertz, M Verleysen Chemometrics and Intelligent Laboratory Systems 80 (2), 215-226, 2006 | 276 | 2006 |
| TROP-ELM: a double-regularized elm using lars and tikhonov regularization Y Miche, M van Heeswijk, P Bas, O Simula, A Lendasse Neurocomputing 74 (16), 2413-2421, 2011 | 272 | 2011 |
| Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis JA Lee, A Lendasse, M Verleysen Neurocomputing 57, 49-76, 2004 | 237 | 2004 |
| GPU-accelerated and parallelized ELM ensembles for large-scale regression M van Heeswijk, Y Miche, E Oja, A Lendasse Neurocomputing, 2011 | 202 | 2011 |
| Bankruptcy prediction using extreme learning machine and financial expertise Q Yu, Y Miche, E Séverin, A Lendasse Neurocomputing 128, 296-302, 2014 | 199 | 2014 |
| Non-linear financial time series forecasting-application to the bel 20 stock market index A Lendasse, E De Bodt, V Wertz, M Verleysen European Journal of Economic and Social Systems 14 (1), 81-92, 2000 | 195 | 2000 |
| A robust nonlinear projection method JA Lee, A Lendasse, N Donckers, M Verleysen Proceedings of ESANN, 13-20, 2000 | 169 | 2000 |
| Regularized extreme learning machine for regression with missing data Q Yu, Y Miche, E Eirola, M Van Heeswijk, E Séverin, A Lendasse Neurocomputing 102, 45-51, 2013 | 167 | 2013 |
| Extreme learning machine for missing data using multiple imputations D Sovilj, E Eirola, Y Miche, KM Björk, R Nian, A Akusok, A Lendasse Neurocomputing 174, 220-231, 2016 | 138 | 2016 |
| OP-ELM: theory, experiments and a toolbox Y Miche, A Sorjamaa, A Lendasse Artificial Neural Networks-ICANN 2008, 145-154, 2008 | 137 | 2008 |
| Adaptive ensemble models of extreme learning machines for time series prediction M Van Heeswijk, Y Miche, T Lindh-Knuutila, P Hilbers, T Honkela, E Oja, ... Artificial Neural Networks–ICANN 2009, 305-314, 2009 | 136 | 2009 |
| Width optimization of the Gaussian kernels in radial basis function networks N Benoudjit, C Archambeau, A Lendasse, J Lee, M Verleysen Proc. of ESANN, 425-432, 2002 | 133 | 2002 |
| Curvilinear distance analysis versus isomap JA Lee, A Lendasse, M Verleysen Proceedings of ESANN, 185-192, 2002 | 131 | 2002 |
| Time series prediction using DirRec strategy. A Sorjamaa, A Lendasse Esann 6, 143-148, 2006 | 130 | 2006 |
| Model selection with cross-validations and bootstraps—application to time series prediction with RBFN models A Lendasse, V Wertz, M Verleysen Artificial Neural Networks and Neural Information Processing—ICANN/ICONIP …, 2003 | 123 | 2003 |
| Long-term prediction of time series by combining direct and MIMO strategies S Ben Taieb, G Bontempi, A Sorjamaa, A Lendasse Neural Networks, 2009. IJCNN 2009. International Joint Conference on, 3054-3061, 2009 | 122 | 2009 |
Liliann MicheBell Labs, Nokia確認したメール アドレス: nokia-bell-labs.com
