| Deep learning with microfluidics for biotechnology J Riordon, D Sovilj, S Sanner, D Sinton, EWK Young Trends in biotechnology 37 (3), 310-324, 2019 | 208 | 2019 |
| Extreme learning machine for missing data using multiple imputations D Sovilj, E Eirola, Y Miche, KM Björk, R Nian, A Akusok, A Lendasse Neurocomputing 174, 220-231, 2016 | 138 | 2016 |
| Using extreme learning machine for intrusion detection in a big data environment J Xiang, M Westerlund, D Sovilj, G Pulkkis Proceedings of the 2014 workshop on artificial intelligent and security …, 2014 | 60 | 2014 |
| Minimising the delta test for variable selection in regression problems A Guillen, D Sovilj, A Lendasse, F Mateo, I Rojas International Journal of High Performance Systems Architecture 1 (4), 269-281, 2008 | 45 | 2008 |
| OPELM and OPKNN in long-term prediction of time series using projected input data D Sovilj, A Sorjamaa, Q Yu, Y Miche, E Séverin Neurocomputing 73 (10-12), 1976-1986, 2010 | 29 | 2010 |
| A comparative evaluation of unsupervised deep architectures for intrusion detection in sequential data streams D Sovilj, P Budnarain, S Sanner, G Salmon, M Rao Expert Systems with Applications 159, 113577, 2020 | 24 | 2020 |
| Investigating the Influence of Feature Sources for Malicious Website Detection A Chaiban, D Sovilj, H Soliman, G Salmon, X Lin Applied Sciences 12 (6), 2806, 2022 | 19 | 2022 |
| Climate induced changes in benthic macrofauna—a non-linear model approach K Junker, D Sovilj, I Kröncke, JW Dippner Journal of Marine Systems 96, 90-94, 2012 | 19 | 2012 |
| Approximate k-NN delta test minimization method using genetic algorithms: Application to time series F Mateo, D Sovilj, R Gadea Neurocomputing 73 (10), 2017-2029, 2010 | 18 | 2010 |
| Fast feature selection in a gpu cluster using the delta test A Guillén, MIG Arenas, M Van Heeswijk, D Sovilj, A Lendasse, LJ Herrera, ... Entropy 16 (2), 854-869, 2014 | 15 | 2014 |
| Extreme learning machines for multiclass classification: refining predictions with gaussian mixture models E Eirola, A Gritsenko, A Akusok, KM Björk, Y Miche, D Sovilj, R Nian, B He, ... Advances in Computational Intelligence: 13th International Work-Conference …, 2015 | 14 | 2015 |
| Comparison of combining methods using Extreme Learning Machines under small sample scenario D Sovilj, KM Björk, A Lendasse Neurocomputing 174, 4-17, 2016 | 10 | 2016 |
| Measuring and mitigating the costs of attentional switches in active network monitoring for cybersecurity SW Kortschot, D Sovilj, GA Jamieson, S Sanner, C Carrasco, H Soh Human factors 60 (7), 962-977, 2018 | 8 | 2018 |
| New methodologies based on delta test for variable selection in regression problems A Guillén, D Sovilj, F Mateo, I Rojas, A Lendasse Workshop on parallel architectures and bioinspired algorithms, Toronto, Canada, 2008 | 7 | 2008 |
| Tabu search with delta test for time series prediction using OP-KNN D Sovilj, A Sorjamaa, Y Miche ESTSP, European Symposium on Time Series Prediction, 187-196, 2008 | 7 | 2008 |
| Rank: Ai-assisted end-to-end architecture for detecting persistent attacks in enterprise networks HM Soliman, D Sovilj, G Salmon, M Rao, N Mayya IEEE Transactions on Dependable and Secure Computing, 2023 | 6 | 2023 |
| An open source adaptive user interface for network monitoring SW Kortschot, D Sovilj, H Soh, GA Jamieson, S Sanner, C Carrasco, ... 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017 | 6 | 2017 |
| RCGA-S/RCGA-SP methods to minimize the delta test for regression tasks F Mateo, D Sovilj, R Gadea, A Lendasse Bio-Inspired Systems: Computational and Ambient Intelligence: 10th …, 2009 | 6 | 2009 |
| Collaborative filtering with behavioral models D Sovilj, S Sanner, H Soh, H Li Proceedings of the 26th Conference on User Modeling, Adaptation and …, 2018 | 5 | 2018 |
| Evolutive approaches for variable selection using a non-parametric noise estimator A Guillén, D Sovilj, M van Heeswijk, LJ Herrera, A Lendasse, H Pomares, ... Parallel architectures and bioinspired algorithms, 243-266, 2012 | 5 | 2012 |
