4 citations · 10 across the 7 of their papers we have counts for
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cs.LG2021★ 1 cited
Mining Drifting Data Streams on a Budget: Combining Active Learning with Self-Labeling
Łukasz Korycki, Bartosz Krawczyk
Mining data streams poses a number of challenges, including the continuous and non-stationary nature of data, the massive volume of information to be processed and constraints put…
cs.LG2021★ 1 cited
Class-Incremental Experience Replay for Continual Learning under Concept Drift
Łukasz Korycki, Bartosz Krawczyk
Modern machine learning systems need to be able to cope with constantly arriving and changing data. Two main areas of research dealing with such scenarios are continual learning an…
cs.LG2021★ 1 cited
Concept Drift Detection from Multi-Class Imbalanced Data Streams
Łukasz Korycki, Bartosz Krawczyk
Continual learning from data streams is among the most important topics in contemporary machine learning. One of the biggest challenges in this domain lies in creating algorithms t…