Lukasz Korycki

According to our database, Lukasz Korycki authored at least 14 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Adversarial concept drift detection under poisoning attacks for robust data stream mining.

Lukasz Korycki, Bartosz Krawczyk

Mach. Learn., October, 2023

Class-Incremental Mixture of Gaussians for Deep Continual Learning.

Lukasz Korycki, Bartosz Krawczyk

CoRR, 2023

2022

Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams.

Lukasz Korycki, Bartosz Krawczyk

Pattern Recognit., 2022

2021

Mining Drifting Data Streams on a Budget: Combining Active Learning with Self-Labeling.

Lukasz Korycki, Bartosz Krawczyk

CoRR, 2021

Streaming Decision Trees for Lifelong Learning.

Lukasz Korycki, Bartosz Krawczyk

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Low-Dimensional Representation Learning from Imbalanced Data Streams.

Lukasz Korycki, Bartosz Krawczyk

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Concept Drift Detection from Multi-Class Imbalanced Data Streams.

Lukasz Korycki, Bartosz Krawczyk

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Class-Incremental Experience Replay for Continual Learning Under Concept Drift.

Lukasz Korycki, Bartosz Krawczyk

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

Adaptive Deep Forest for Online Learning from Drifting Data Streams.

Lukasz Korycki, Bartosz Krawczyk

CoRR, 2020

Online Oversampling for Sparsely Labeled Imbalanced and Non-Stationary Data Streams.

Lukasz Korycki, Bartosz Krawczyk

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Unsupervised Drift Detector Ensembles for Data Stream Mining.

Lukasz Korycki, Bartosz Krawczyk

Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019

Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams.

Lukasz Korycki, Alberto Cano, Bartosz Krawczyk

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Clustering-Driven and Dynamically Diversified Ensemble for Drifting Data Streams.

Lukasz Korycki, Bartosz Krawczyk

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Combining Active Learning and Self-Labeling for Data Stream Mining.

Lukasz Korycki, Bartosz Krawczyk

Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017, 2017