| Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study M Choraś, K Demestichas, A Giełczyk, Á Herrero, P Ksieniewicz, ... Applied Soft Computing 101, 107050, 2021 | 119 | 2021 |
| How to design the fair experimental classifier evaluation K Stapor, P Ksieniewicz, S García, M Woźniak Applied Soft Computing 104, 107219, 2021 | 84 | 2021 |
| Sentiment analysis for fake news detection by means of neural networks S Kula, M Choraś, R Kozik, P Ksieniewicz, M Woźniak Computational Science–ICCS 2020: 20th International Conference, Amsterdam …, 2020 | 81 | 2020 |
| Stream-learn—Open-source Python library for difficult data stream batch analysis P Ksieniewicz, P Zyblewski Neurocomputing 478, 11-21, 2022 | 48 | 2022 |
| Machine learning methods for fake news classification P Ksieniewicz, M Choraś, R Kozik, M Woźniak Intelligent Data Engineering and Automated Learning–IDEAL 2019: 20th …, 2019 | 44 | 2019 |
| Data stream classification using active learned neural networks P Ksieniewicz, M Woźniak, B Cyganek, A Kasprzak, K Walkowiak Neurocomputing 353, 74-82, 2019 | 38 | 2019 |
| Fake news detection from data streams P Ksieniewicz, P Zyblewski, M Choraś, R Kozik, A Giełczyk, M Woźniak 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 36 | 2020 |
| Classifier Selection for Highly Imbalanced Data Streams with Minority Driven Ensemble P Zyblewski, P Ksieniewicz, M Woźniak International conference on artificial intelligence and soft computing, 626-635, 2019 | 36 | 2019 |
| Application of imbalanced data classification quality metrics as weighting methods of the ensemble data stream classification algorithms W Wegier, P Ksieniewicz Entropy 22 (8), 849, 2020 | 33 | 2020 |
| Machine learning assisted optimization of dynamic crosstalk-aware spectrally-spatially flexible optical networks M Klinkowski, P Ksieniewicz, M Jaworski, G Zalewski, K Walkowiak Journal of Lightwave Technology 38 (7), 1625-1635, 2020 | 26 | 2020 |
| Active learning classification of drifted streaming data M Woźniak, P Ksieniewicz, B Cyganek, A Kasprzak, K Walkowiak Procedia Computer Science 80, 1724-1733, 2016 | 23 | 2016 |
| Ensemble of Extreme Learning Machines with trained classifier combination and statistical features for hyperspectral data P Ksieniewicz, B Krawczyk, M Woźniak Neurocomputing 271, 28-37, 2018 | 21 | 2018 |
| Active weighted aging ensemble for drifted data stream classification M Woźniak, P Zyblewski, P Ksieniewicz Information Sciences 630, 286-304, 2023 | 19 | 2023 |
| Ensembles of heterogeneous concept drift detectors-experimental study M Woźniak, P Ksieniewicz, B Cyganek, K Walkowiak Computer Information Systems and Industrial Management: 15th IFIP TC8 …, 2016 | 19 | 2016 |
| Statistical drift detection ensemble for batch processing of data streams J Komorniczak, P Zyblewski, P Ksieniewicz Knowledge-Based Systems 252, 109380, 2022 | 17 | 2022 |
| SMOTE algorithm variations in balancing data streams B Gulowaty, P Ksieniewicz Intelligent Data Engineering and Automated Learning–IDEAL 2019: 20th …, 2019 | 16 | 2019 |
| Alphabet flatting as a variant of n-gram feature extraction method in ensemble classification of fake news P Ksieniewicz, P Zyblewski, W Borek-Marciniec, R Kozik, M Choraś, ... Engineering Applications of Artificial Intelligence 120, 105882, 2023 | 15 | 2023 |
| Prior probability estimation in dynamically imbalanced data streams J Komorniczak, P Zyblewski, P Ksieniewicz 2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021 | 15 | 2021 |
| Glaucoma classification based on scanning laser ophthalmoscopic images using a deep learning ensemble method D Sułot, D Alonso-Caneiro, P Ksieniewicz, P Krzyzanowska-Berkowska, ... Plos one 16 (6), e0252339, 2021 | 15 | 2021 |
| Imbalanced data classification based on feature selection techniques P Ksieniewicz, M Woźniak Intelligent Data Engineering and Automated Learning–IDEAL 2018: 19th …, 2018 | 15 | 2018 |
Michal WozniakWroclaw University of Science and Technology (Politechnika Wrocławska)Verified email at pwr.edu.pl
