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ORCIDMark van Heeswijk
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2010 – 2019
- 2019
[j10]Topi Toosi, Miki Sirola, Jarkko Laukkanen, Mark van Heeswijk, Juha Karhunen:
Method for Detecting aging Related Failures of Process Sensors via noise signal Measurement. Int. J. Comput. 18: 135-146 (2019)- 2017
- [c7]Topi Toosi, Miki Sirola, Jarkko Laukkanen, Mark van Heeswijk, Juha Karhunen:
Detecting aging of process sensors with noise signal measurement. IDAACS 2017: 35-40 - 2016
- [c6]Chen Zhao, Mark van Heeswijk, Juha Karhunen:
Air quality forecasting using neural networks. SSCI 2016: 1-7 - 2015
- [b1]Mark van Heeswijk:
Advances in Extreme Learning Machines. Aalto University, Helsinki, Finland, 2015 - [j9]Mark van Heeswijk, Yoan Miche:
Binary/ternary extreme learning machines. Neurocomputing 149: 187-197 (2015) - 2014
- [j8]Bo He, Dongxun Xu, Rui Nian, Mark van Heeswijk, Qi Yu, Yoan Miche
, Amaury Lendasse:
Fast Face Recognition Via Sparse Coding and Extreme Learning Machine. Cogn. Comput. 6(2): 264-277 (2014) - [j7]Alberto Guillén, M. Isabel García Arenas, Mark van Heeswijk, Dusan Sovilj, Amaury Lendasse, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas:
Fast Feature Selection in a GPU Cluster Using the Delta Test. Entropy 16(2): 854-869 (2014) - [j6]Rui Nian, Bo He, Bing Zheng, Mark van Heeswijk, Qi Yu, Yoan Miche, Amaury Lendasse:
Extreme learning machine towards dynamic model hypothesis in fish ethology research. Neurocomputing 128: 273-284 (2014) - [j5]Qi Yu, Mark van Heeswijk, Yoan Miche, Rui Nian, Bo He, Eric Séverin, Amaury Lendasse:
Ensemble delta test-extreme learning machine (DT-ELM) for regression. Neurocomputing 129: 153-158 (2014) - [c5]Mark van Heeswijk, Amaury Lendasse, Yoan Miché:
Compressive ELM: Improved Models through Exploiting Time-Accuracy Trade-Offs. EANN 2014: 165-174 - 2013
- [j4]Qi Yu, Yoan Miche, Emil Eirola, Mark van Heeswijk, Eric Séverin, Amaury Lendasse:
Regularized extreme learning machine for regression with missing data. Neurocomputing 102: 45-51 (2013) - [j3]Benoît Frénay, Mark van Heeswijk, Yoan Miche, Michel Verleysen, Amaury Lendasse:
Feature selection for nonlinear models with extreme learning machines. Neurocomputing 102: 111-124 (2013) - [c4]Amaury Lendasse, Anton Akusok, Olli Simula, Francesco Corona, Mark van Heeswijk, Emil Eirola, Yoan Miche:
Extreme Learning Machine: A Robust Modeling Technique? Yes! IWANN (1) 2013: 17-35 - 2012
- [p1]Alberto Guillén, Dusan Sovilj, Mark van Heeswijk, Luis Javier Herrera, Amaury Lendasse, Héctor Pomares, Ignacio Rojas:
Evolutive Approaches for Variable Selection Using a Non-parametric Noise Estimator. Parallel Architectures and Bioinspired Algorithms 2012: 243-266 - 2011
- [j2]Yoan Miche, Mark van Heeswijk, Patrick Bas, Olli Simula, Amaury Lendasse:
TROP-ELM: A double-regularized ELM using LARS and Tikhonov regularization. Neurocomputing 74(16): 2413-2421 (2011) - [j1]Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse:
GPU-accelerated and parallelized ELM ensembles for large-scale regression. Neurocomputing 74(16): 2430-2437 (2011) - [c3]Alberto Guillén, Mark van Heeswijk, Dusan Sovilj, Maribel García Arenas, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas:
Variable Selection in a GPU Cluster Using Delta Test. IWANN (1) 2011: 393-400 - 2010
- [c2]Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse:
Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs. ESANN 2010
2000 – 2009
- 2009
- [c1]Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutila, Peter A. J. Hilbers, Timo Honkela, Erkki Oja, Amaury Lendasse:
Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction. ICANN (2) 2009: 305-314
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