Emil Eirola

According to our database, Emil Eirola authored at least 24 papers between 2008 and 2019.

Collaborative distances:

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

2019

Extreme Learning Tree.

Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Amaury Lendasse

CoRR, 2019

Incremental ELMVIS for unsupervised learning.

Anton Akusok, Emil Eirola, Yoan Miche, Ian Oliver, Kaj-Mikael Björk, Andrey Gritsenko, Stephen Baek, Amaury Lendasse

CoRR, 2019

Rhythmicity of health information behaviour.

Jonas Tana, Emil Eirola, Kristina Eriksson-Backa

Aslib J. Inf. Manag., 2019

2018

ELM-SOM: A Continuous Self-Organizing Map for Visualization.

Renjie Hu, Venous Roshdibenam, Hans J. Johnson, Emil Eirola, Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Comparison of Classification Methods for Very High-Dimensional Data in Sparse Random Projection Representation.

Anton Akusok, Emil Eirola

Proceedings of ELM 2018, 2018

2017

A pragmatic android malware detection procedure.

Paolo Palumbo, Luiza Sayfullina, Dmitriy Komashinskiy, Emil Eirola, Juha Karhunen

Comput. Secur., 2017

Brute-force Missing Data Extreme Learning Machine for Predicting Huntington's Disease.

Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Yoan Miché, Hans J. Johnson, Amaury Lendasse

Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments, 2017

Solve Classification Tasks with Probabilities. Statistically-Modeled Outputs.

Andrey Gritsenko, Emil Eirola, Daniel Schupp, Edward R. Ratner, Amaury Lendasse

Proceedings of the Hybrid Artificial Intelligent Systems - 12th International Conference, 2017

Advanced query strategies for Active Learning with Extreme Learning Machines.

Anton Akusok, Emil Eirola, Yoan Miché, Andrey Gritsenko, Amaury Lendasse

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016

Extreme learning machine for missing data using multiple imputations.

Dusan Sovilj, Emil Eirola, Yoan Miche, Kaj-Mikael Björk, Rui Nian, Anton Akusok, Amaury Lendasse

Neurocomputing, 2016

A new application of machine learning in health care.

Kaj-Mikael Björk, Emil Eirola, Yoan Miché, Amaury Lendasse

Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments, 2016

Android Malware Detection: Building Useful Representations.

Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Juha Karhunen

Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

2015

Efficient Detection of Zero-day Android Malware Using Normalized Bernoulli Naive Bayes.

Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Yoan Miché, Amaury Lendasse, Juha Karhunen

Proceedings of the 2015 IEEE TrustCom/BigDataSE/ISPA, 2015

Extreme Learning Machines for Multiclass Classification: Refining Predictions with Gaussian Mixture Models.

Emil Eirola, Andrey Gritsenko, Anton Akusok, Kaj-Mikael Björk, Yoan Miche, Dusan Sovilj, Rui Nian, Bo He, Amaury Lendasse

Proceedings of the Advances in Computational Intelligence, 2015

2014

Mixture of Gaussians for distance estimation with missing data.

Emil Eirola, Amaury Lendasse, Vincent Vandewalle, Christophe Biernacki

Neurocomputing, 2014

Variable selection for regression problems using Gaussian mixture models to estimate mutual information.

Emil Eirola, Amaury Lendasse, Juha Karhunen

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

The delta test: The 1-NN estimator as a feature selection criterion.

Emil Eirola, Amaury Lendasse, Francesco Corona, Michel Verleysen

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

2013

Distance estimation in numerical data sets with missing values.

Emil Eirola, Gauthier Doquire, Michel Verleysen, Amaury Lendasse

Inf. Sci., 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

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

Gaussian Mixture Models for Time Series Modelling, Forecasting, and Interpolation.

Emil Eirola, Amaury Lendasse

Proceedings of the Advances in Intelligent Data Analysis XII, 2013

2010

Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs.

Yoan Miche, Emil Eirola, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse, Michel Verleysen

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

Ensembles of Locally Linear Models: Application to Bankruptcy Prediction.

Laura Kainulainen, Qi Yu, Yoan Miche, Emil Eirola, Eric Séverin, Amaury Lendasse

Proceedings of The 2010 International Conference on Data Mining, 2010

2008

Using the Delta Test for Variable Selection.

Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona, Michel Verleysen

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008