Emil Eirola

发表

Distance estimation in numerical data sets with missing values

Michel Verleysen, Amaury Lendasse, Emil Eirola, 2013, Inf. Sci..

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

Amaury Lendasse, Kaj-Mikael Björk, Anton Akusok, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

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

Juha Karhunen, Amaury Lendasse, Emil Eirola, 2015, 2015 IEEE Trustcom/BigDataSE/ISPA.

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

Amaury Lendasse, Kaj-Mikael Björk, Bo He, 2015, IWANN.

Distance Estimation for Incomplete Data by Extreme Learning Machine

Amaury Lendasse, Anton Akusok, Emil Eirola, 2017 .

Regularized extreme learning machine for regression with missing data

Amaury Lendasse, Eric Séverin, Qi Yu, 2013, Neurocomputing.

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

Amaury Lendasse, Emil Eirola, A. Lendasse, 2013, IDA.

A new application of machine learning in health care

Amaury Lendasse, Kaj-Mikael Björk, Emil Eirola, 2016, PETRA.

Android Malware Detection: Building Useful Representations

Juha Karhunen, Emil Eirola, Luiza Sayfullina, 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

Rhythmicity of health information behaviour

Jonas Tana, Emil Eirola, Kristina Eriksson-Backa, 2019, Aslib J. Inf. Manag..

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

Amaury Lendasse, Kaj-Mikael Björk, Anton Akusok, 2017, PETRA.

Extreme Learning Tree pdf

Amaury Lendasse, Anton Akusok, Emil Eirola, 2017, Proceedings in Adaptation, Learning and Optimization.

Extreme Learning Machine: A Robust Modeling Technique? Yes!

Amaury Lendasse, Olli Simula, Anton Akusok, 2013, IWANN.

Incremental ELMVIS for unsupervised learning pdf

Amaury Lendasse, Anton Akusok, Stephen Baek, 2019, ArXiv.

Extreme learning machine for missing data using multiple imputations

Amaury Lendasse, Yoan Miche, Kaj-Mikael Björk, 2016, Neurocomputing.

Solve Classification Tasks with Probabilities. Statistically-Modeled Outputs

Amaury Lendasse, Emil Eirola, Andrey Gritsenko, 2017, HAIS.

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

Juha Karhunen, Amaury Lendasse, Emil Eirola, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

A pragmatic android malware detection procedure

Juha Karhunen, Emil Eirola, Luiza Sayfullina, 2017, Comput. Secur..

Ensembles of Locally Linear Models: Application to Bankruptcy Prediction

Amaury Lendasse, Eric Séverin, Qi Yu, 2010, DMIN.

Ensembles of Local Linear Models for Bankruptcy Analysis and Prediction

Benoît Frénay, Amaury Lendasse, Yoan Miche, 2011 .

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

Anton Akusok, Emil Eirola, Emil Eirola, 2018, ELM.

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

Michel Verleysen, Amaury Lendasse, Francesco Corona, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

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

Michel Verleysen, Amaury Lendasse, Olli Simula, 2010, ESANN.

When is prime-time in streaming media platforms and video-on-demands services? New media consumption patterns and real-time economy

Jonas Tana, Emil Eirola, Mats Nylund, 2019, European Journal of Communication.

Ensemble classifiers for bankruptcy prediction

Amaury Lendasse, Yoan Miche, Qi Yu, 2010 .

Advanced query strategies for Active Learning with Extreme Learning Machines

Amaury Lendasse, Anton Akusok, Emil Eirola, 2017, ESANN.

Proc. of The IEEE 15th Int. Conf. on Machine Learning and Applications (ICMLA 2016)

Juha Karhunen, Emil Eirola, Luiza Sayfullina, 2016 .

Probabilistic Methods for Multiclass Classification Problems

Amaury Lendasse, Emil Eirola, Edward Ratner, 2016 .

Mixture of Gaussians for distance estimation with missing data

Amaury Lendasse, Vincent Vandewalle, Christophe Biernacki, 2014, Neurocomputing.

Using the Delta Test for Variable Selection

Michel Verleysen, Amaury Lendasse, Francesco Corona, 2008, ESANN.

Machine learning methods for incomplete data and variable selection

Emil Eirola, Emil Eirola, 2014 .

14th IEEE international conference on Trust, Security, and Privacy in Computing and Communications (TrustCom), Helsinki, Finland, August 20-22, 2015

Juha Karhunen, Amaury Lendasse, Yoan Miche, 2015 .

Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data

Jyrki Kettunen, Emil Eirola, Heikki Paakkonen, 2018, JMIR mental health.

Predicting Huntington’s Disease: Extreme Learning Machine with Missing Values

Amaury Lendasse, Kaj-Mikael Björk, Anton Akusok, 2018 .