Concept Drift Detection from Multi-Class Imbalanced Data Streams Ł Korycki, B Krawczyk 37th IEEE International Conference on Data Engineering (ICDE 2021), 2021 | 47 | 2021 |
Class-Incremental Experience Replay for Continual Learning under Concept Drift Ł Korycki, B Krawczyk IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021 …, 2021 | 39 | 2021 |
Active learning with abstaining classifiers for imbalanced drifting data streams Ł Korycki, A Cano, B Krawczyk 2019 IEEE International Conference on Big Data (Big Data 2019), 2334-2343, 2019 | 37 | 2019 |
Adversarial concept drift detection under poisoning attacks for robust data stream mining Ł Korycki, B Krawczyk Machine Learning, 1-36, 2022 | 26 | 2022 |
Online Oversampling for Sparsely Labeled Imbalanced and Non-Stationary Data Streams Ł Korycki, B Krawczyk 2020 International Joint Conference on Neural Networks (IJCNN 2020), 1-8, 2020 | 23 | 2020 |
Combining active learning and self-labeling for data stream mining Ł Korycki, B Krawczyk Proceedings of the 10th International Conference on Computer Recognition …, 2018 | 17 | 2018 |
Unsupervised Drift Detector Ensembles for Data Stream Mining Ł Korycki, B Krawczyk 2019 IEEE International Conference on Data Science and Advanced Analytics …, 2019 | 15 | 2019 |
Streaming Decision Trees for Lifelong Learning Ł Korycki, B Krawczyk European Conference on Machine Learning (ECML PKDD 2021), 2021 | 12 | 2021 |
Low-Dimensional Representation Learning from Imbalanced Data Streams Ł Korycki, B Krawczyk 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2021), 2021 | 12 | 2021 |
Clustering-Driven and Dynamically Diversified Ensemble for Drifting Data Streams Ł Korycki, B Krawczyk 2018 IEEE International Conference on Big Data (Big Data 2018), 1037-1044, 2018 | 6 | 2018 |
Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams Ł Korycki, B Krawczyk Pattern Recognition, 108749, 2022 | 4 | 2022 |
Mining Drifting Data Streams on a Budget: Combining Active Learning with Self-Labeling Ł Korycki, B Krawczyk arXiv preprint arXiv:2112.11019, 2021 | 1 | 2021 |
Class-Incremental Mixture of Gaussians for Deep Continual Learning Ł Korycki, B Krawczyk arXiv preprint arXiv:2307.04094, 2023 | | 2023 |
Continual learning from stationary and non-stationary data Ł Korycki | | 2022 |