Mark van Heeswijk

According to our database, Mark van Heeswijk authored at least 19 papers between 2009 and 2019.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2019

Method for Detecting aging Related Failures of Process Sensors via noise signal Measurement.

Topi Toosi, Miki Sirola, Jarkko Laukkanen, Mark van Heeswijk, Juha Karhunen

Int. J. Comput., 2019

2017

Detecting aging of process sensors with noise signal measurement.

Topi Toosi, Miki Sirola, Jarkko Laukkanen, Mark van Heeswijk, Juha Karhunen

Proceedings of the 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2017

2016

Air quality forecasting using neural networks.

Chen Zhao, Mark van Heeswijk, Juha Karhunen

Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

2015

Advances in Extreme Learning Machines.

Mark van Heeswijk

PhD thesis, 2015

Binary/ternary extreme learning machines.

Mark van Heeswijk, Yoan Miche

Neurocomputing, 2015

2014

Ensemble delta test-extreme learning machine (DT-ELM) for regression.

Qi Yu, Mark van Heeswijk, Yoan Miche, Rui Nian, Bo He, Eric Séverin, Amaury Lendasse

Neurocomputing, 2014

Extreme learning machine towards dynamic model hypothesis in fish ethology research.

Rui Nian, Bo He, Bing Zheng, Mark van Heeswijk, Qi Yu, Yoan Miche, Amaury Lendasse

Neurocomputing, 2014

Fast Feature Selection in a GPU Cluster Using the Delta Test.

Alberto Guillén, M. Isabel García Arenas, Mark van Heeswijk, Dusan Sovilj, Amaury Lendasse, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas

Entropy, 2014

Fast Face Recognition Via Sparse Coding and Extreme Learning Machine.

Bo He, Dongxun Xu, Rui Nian, Mark van Heeswijk, Qi Yu, Yoan Miche, Amaury Lendasse

Cogn. Comput., 2014

Compressive ELM: Improved Models through Exploiting Time-Accuracy Trade-Offs.

Mark van Heeswijk, Amaury Lendasse, Yoan Miché

Proceedings of the Engineering Applications of Neural Networks, 2014

2013

Regularized extreme learning machine for regression with missing data.

Qi Yu, Yoan Miche, Emil Eirola, Mark van Heeswijk, Eric Séverin, Amaury Lendasse

Neurocomputing, 2013

Feature selection for nonlinear models with extreme learning machines.

Benoît Frénay, Mark van Heeswijk, Yoan Miche, Michel Verleysen, Amaury Lendasse

Neurocomputing, 2013

Extreme Learning Machine: A Robust Modeling Technique? Yes!

Amaury Lendasse, Anton Akusok, Olli Simula, Francesco Corona, Mark van Heeswijk, Emil Eirola, Yoan Miche

Proceedings of the Advances in Computational Intelligence, 2013

2012

Evolutive Approaches for Variable Selection Using a Non-parametric Noise Estimator.

Alberto Guillén, Dusan Sovilj, Mark van Heeswijk, Luis Javier Herrera, Amaury Lendasse, Héctor Pomares, Ignacio Rojas

Proceedings of the Parallel Architectures and Bioinspired Algorithms, 2012

2011

TROP-ELM: A double-regularized ELM using LARS and Tikhonov regularization.

Yoan Miche, Mark van Heeswijk, Patrick Bas, Olli Simula, Amaury Lendasse

Neurocomputing, 2011

GPU-accelerated and parallelized ELM ensembles for large-scale regression.

Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse

Neurocomputing, 2011

Variable Selection in a GPU Cluster Using Delta Test.

Alberto Guillén, Mark van Heeswijk, Dusan Sovilj, Maribel García Arenas, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas

Proceedings of the Advances in Computational Intelligence, 2011

2010

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs.

Mark van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

2009

Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction.

Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutila, Peter A. J. Hilbers, Timo Honkela, Erkki Oja, Amaury Lendasse

Proceedings of the Artificial Neural Networks, 2009