| Learning from imbalanced data sets with boosting and data generation: the databoost-im approach H Guo, HL Viktor ACM Sigkdd Explorations Newsletter 6 (1), 30-39, 2004 | 780 | 2004 |
| Molecular dynamics, monte carlo simulations, and langevin dynamics: a computational review E Paquet, HL Viktor BioMed research international 2015, 2015 | 169 | 2015 |
| Fast hoeffding drift detection method for evolving data streams A Pesaranghader, HL Viktor Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 147 | 2016 |
| SCUT: Multi-class imbalanced data classification using SMOTE and cluster-based undersampling A Agrawal, HL Viktor, E Paquet 2015 7Th international joint conference on knowledge discovery, knowledge …, 2015 | 107 | 2015 |
| McDiarmid drift detection methods for evolving data streams A Pesaranghader, HL Viktor, E Paquet 2018 International joint conference on neural networks (IJCNN), 1-9, 2018 | 72 | 2018 |
| Reservoir of diverse adaptive learners and stacking fast hoeffding drift detection methods for evolving data streams A Pesaranghader, H Viktor, E Paquet Machine Learning 107 (11), 1711-1743, 2018 | 67 | 2018 |
| Long-term preservation of 3-D cultural heritage data related to architectural sites E Paquet, HL Viktor Proceedings of the ISPRS Working Group 4, 1-8, 2005 | 64 | 2005 |
| Multirelational classification: a multiple view approach H Guo, HL Viktor Knowledge and Information Systems 17, 287-312, 2008 | 57 | 2008 |
| Computational methods for ab initio molecular dynamics E Paquet, HL Viktor Adv. Chem 2018, 9839641, 2018 | 52 | 2018 |
| Learning from imbalanced data using ensemble methods and cluster-based undersampling P Sobhani, H Viktor, S Matwin New Frontiers in Mining Complex Patterns: Third International Workshop …, 2015 | 51 | 2015 |
| Boosting with data generation: improving the classification of hard to learn examples H Guo, HL Viktor International Conference on Industrial, Engineering and Other Applications …, 2004 | 40 | 2004 |
| Reduction of symbolic rules from artificial neural networks using sensitivity analysis HL Viktor, AP Engelbrecht, I Cloete Proceedings of ICNN'95-International Conference on Neural Networks 4, 1788-1793, 1995 | 37 | 1995 |
| Exploring anthropometric data through cluster analysis O Abdali, H Viktor, E Paquet, M Rioux SAE transactions, 241-244, 2004 | 32 | 2004 |
| Long-term digital preservation: preserving authenticity and usability of 3-D data J Doyle, H Viktor, E Paquet International journal on digital libraries 10, 33-47, 2009 | 31 | 2009 |
| Mining relational databases with multi-view learning H Guo, HL Viktor Proceedings of the 4th international workshop on Multi-relational mining, 15-24, 2005 | 30 | 2005 |
| Use of Performance Metrics to Forecast Success in the National Hockey League. J Weissbock, HL Viktor, D Inkpen MLSA@ PKDD/ECML, 39-48, 2013 | 25 | 2013 |
| Dynamic adaptation of online ensembles for drifting data streams MK Olorunnimbe, HL Viktor, E Paquet Journal of Intelligent Information Systems 50, 291-313, 2018 | 24 | 2018 |
| Machine-generated text: A comprehensive survey of threat models and detection methods E Crothers, N Japkowicz, HL Viktor IEEE Access, 2023 | 23 | 2023 |
| Catering for unique tastes: Targeting grey-sheep users recommender systems through one-class machine learning R Alabdulrahman, H Viktor Expert Systems with Applications 166, 114061, 2021 | 23 | 2021 |
| The PerfSim algorithm for concept drift detection in imbalanced data DK Antwi, HL Viktor, N Japkowicz 2012 IEEE 12th International Conference on Data Mining Workshops, 619-628, 2012 | 22 | 2012 |
Eric PaquetNational Research CouncilVerified email at nrc-cnrc.gc.ca
