Emil Eirola - RankMe

27 papers B 7C 1Misc 1Journal 10Unranked 7

Year	Rank	Type	Title / Venue / Authors
2020	J	`jnl`	Exploring temporal variations of depression-related health information behaviour in a discussion forum: the case of Suomi24. Inf. Res. Jonas Tana, Emil Eirola, Kristina Eriksson-Backa
2019	J	`jnl`	Comparison of Classification Methods for Very High-Dimensional Data in Sparse Random Projection Representation. CoRR Anton Akusok, Emil Eirola
2019	J	`jnl`	Extreme Learning Tree. CoRR Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Amaury Lendasse
2019	J	`jnl`	Incremental ELMVIS for unsupervised learning. CoRR Anton Akusok, Emil Eirola, Yoan Miche, Ian Oliver, Kaj-Mikael Björk, Andrey Gritsenko, Stephen Baek, Amaury Lendasse
2019	J	`jnl`	Rhythmicity of health information behaviour. Aslib J. Inf. Manag. Jonas Tana, Emil Eirola, Kristina Eriksson-Backa
2018	—	`conf`	Comparison of Classification Methods for Very High-Dimensional Data in Sparse Random Projection Representation. ELM Anton Akusok, Emil Eirola
2018	B	`conf`	ELM-SOM: A Continuous Self-Organizing Map for Visualization. IJCNN Renjie Hu, Venous Roshdibenam, Hans J. Johnson, Emil Eirola, Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse
2017	J	`jnl`	A pragmatic android malware detection procedure. Comput. Secur. Paolo Palumbo, Luiza Sayfullina, Dmitriy Komashinskiy, Emil Eirola, Juha Karhunen
2017	B	`conf`	Advanced query strategies for Active Learning with Extreme Learning Machines. ESANN Anton Akusok, Emil Eirola, Yoan Miché, Andrey Gritsenko, Amaury Lendasse
2017	—	`conf`	Brute-force Missing Data Extreme Learning Machine for Predicting Huntington's Disease. PETRA Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Yoan Miché, Hans J. Johnson, Amaury Lendasse
2017	Misc	`conf`	Solve Classification Tasks with Probabilities. Statistically-Modeled Outputs. HAIS Andrey Gritsenko, Emil Eirola, Daniel Schupp, Edward R. Ratner, Amaury Lendasse
2016	—	`conf`	A new application of machine learning in health care. PETRA Kaj-Mikael Björk, Emil Eirola, Yoan Miché, Amaury Lendasse
2016	C	`conf`	Android Malware Detection: Building Useful Representations. ICMLA Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Juha Karhunen
2016	J	`jnl`	Extreme learning machine for missing data using multiple imputations. Neurocomputing Dusan Sovilj, Emil Eirola, Yoan Miche, Kaj-Mikael Björk, Rui Nian, Anton Akusok, Amaury Lendasse
2015	—	`conf`	Efficient Detection of Zero-day Android Malware Using Normalized Bernoulli Naive Bayes. TrustCom/BigDataSE/ISPA (1) Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Yoan Miché, Amaury Lendasse, Juha Karhunen
2015	—	`conf`	Extreme Learning Machines for Multiclass Classification: Refining Predictions with Gaussian Mixture Models. IWANN (2) Emil Eirola, Andrey Gritsenko, Anton Akusok, Kaj-Mikael Björk, Yoan Miche, Dusan Sovilj, Rui Nian, Bo He, Amaury Lendasse
2014	—	`—`	Machine learning methods for incomplete data and variable selection ; Metoder för ofullständiga datamängder och attributval i maskininlärning. Emil Eirola
2014	J	`jnl`	Mixture of Gaussians for distance estimation with missing data. Neurocomputing Emil Eirola, Amaury Lendasse, Vincent Vandewalle, Christophe Biernacki
2014	B	`conf`	The delta test: The 1-NN estimator as a feature selection criterion. IJCNN Emil Eirola, Amaury Lendasse, Francesco Corona, Michel Verleysen
2014	B	`conf`	Variable selection for regression problems using Gaussian mixture models to estimate mutual information. IJCNN Emil Eirola, Amaury Lendasse, Juha Karhunen
2013	J	`jnl`	Distance estimation in numerical data sets with missing values. Inf. Sci. Emil Eirola, Gauthier Doquire, Michel Verleysen, Amaury Lendasse
2013	—	`conf`	Extreme Learning Machine: A Robust Modeling Technique? Yes! IWANN (1) Amaury Lendasse, Anton Akusok, Olli Simula, Francesco Corona, Mark van Heeswijk, Emil Eirola, Yoan Miche
2013	B	`conf`	Gaussian Mixture Models for Time Series Modelling, Forecasting, and Interpolation. IDA Emil Eirola, Amaury Lendasse
2013	J	`jnl`	Regularized extreme learning machine for regression with missing data. Neurocomputing Qi Yu, Yoan Miche, Emil Eirola, Mark van Heeswijk, Eric Séverin, Amaury Lendasse
2010	B	`conf`	Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs. ESANN Yoan Miche, Emil Eirola, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse, Michel Verleysen
2010	—	`conf`	Ensembles of Locally Linear Models: Application to Bankruptcy Prediction. DMIN Laura Kainulainen, Qi Yu, Yoan Miche, Emil Eirola, Eric Séverin, Amaury Lendasse
2008	B	`conf`	Using the Delta Test for Variable Selection. ESANN Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona, Michel Verleysen